Three University of Toronto degrees. Individual graduation ceremonies spanning five days. One shared belief in the transformative potential of artificial intelligence.

Rayan, Mouaid and Mogtaba Alim each crossed the stage at Convocation Hall this month during three separate ceremonies (linked to their respective colleges) as they each graduate with honours bachelor’s degrees in computer science.

Raised in Sudan, the United Arab Emirates and the United Kingdom, the three siblings were all accepted into medical school in the U.K. but were drawn to the transformative potential of AI — and to U of T, home to and “godfather of AI” Geoffrey Hinton, a emeritus.

Studying in the , the trio has since conducted research into a range of AI applications — from cancer diagnosis to data governance — launched student groups and even co-founded a startup, earning them each the , among other accolades.

U of T News recently spoke with the three siblings about their academic interests, future plans and what it was like to share their undergraduate journey.

Rayan Alim — St. Michael’s College

Honours bachelor of science — computer science (with a focus in human-computer interaction), major in quantitative biology, minor in statistics and Rotman certificate in business fundamentals

Rayan’s studies explored the intersection of AI, equity and the public good.

She credits U of T’s world-class scholarship across a wide array of subjects and interdisciplinary culture with enabling her work.

“You could go from a machine-learning lab in the morning to a community roundtable in the evening,” she says.

“That proximity to researchers, policymakers, activists and founders — all within a few blocks — pushes you to stop thinking in silos and consider the bigger picture.”

That bigger picture led Rayan to conduct research on climate mobility and data governance at the and, as an fellow, create a machine-learning tool that — work recognized by United Nations Development Programme specialists and validated using education and census data in Nigeria.

She also applied her interest in ethical AI to health care, using bioinformatics and computational tools to examine racial disparities in schizophrenia diagnoses as a researcher at the .

At the , Rayan led a capstone project using machine learning to quantify biases in health data, aiming to improve equity and accuracy in clinical decision-making systems.

She also founded the Black STEM Network and the Sudanese Student Union — and served three terms as equity director of the Black Students’ Association and four terms as a board director at the University of Toronto Students' Union.

What was it like attending U of T with her two brothers?

“We’re naturally very competitive people, so being in the same class sometimes would push us all to do better,” she says, “and when you have someone who shares your values and curiosity, it becomes a great support network.”

Up next: A master’s in computer science at U of T, focusing on ethical AI and human-computer interaction.

Mouaid Alim — New College

Honours bachelor of science — specialist in bioinformatics and computational biology, double major in computer science and human biology and a Rotman certificate in business fundamentals

With a double major in computer science and human biology, Mouaid worked on several AI-related projects at Toronto General Hospital’s , part of the University Health Network (UHN).

They include: a machine-learning dashboard to optimize liver transplant allocation; AI models to predict changes in the clinical state of potential liver transplant patients; and using large language models (LLMs) to assess patients’ risk of post-transplant injuries and organ rejection. This work has been , which belongs to the British Medical Journal family.

At the Vector Institute, Mouaid completed a capstone project focused on identifying risk factors for heart failure.

“I don’t know what’s in the water or the air here, but I feel like U of T cultivates a culture of collaboration and an ecosystem where people support each other in their path to greatness,” says Mouaid, who served as vice-president of student life at the New College Student Council, a board director at the U of T Students’ Union and president at the , among other roles.

Like his sister, he says the three of them inspire one another.

“If one of us achieves something, it’s like we all achieved it by extension,” he says. “If one of us gains a unique skill set, the others feel like they have it as well. We are constantly teaching and learning from each other.”

Up next: Mouaid has been accepted to the MD program at the Temerty Faculty of Medicine. He also has an offer from the University of Cambridge’s master’s program in health data science.

Mogtaba Alim — Trinity College

Honours bachelor of science — double specialist in computer science (with a focus in artificial intelligence) and bioinformatics and computational biology, and a Rotman certificate in business fundamentals

Mogtaba explored his combined passions for AI and health care through research projects at UHN.

These included: developing databases to map gene regulatory networks in cancer at the ; and performing large-scale data extraction from computed tomography (CT) scans to support diagnostic and prognostic models at .

Drawing on insights from his lab experience, Mogtaba launched LabGPT, a project that uses LLMs to streamline lab onboarding and operations.

He also interned at Amazon Web Services, where he worked on automating data privacy, and at Amazon’s Artificial General Intelligence Lab, where he contributed to LLM development. Of course, he, too, has been an AI researcher at the Vector Institute, focusing on multi-agent reinforcement learning.

Mogtaba, who has served as both vice-president and later president of the U of T Computer Science Student Union, describes the experience of attending U of T with his siblings as “the closest thing to a superpower,” noting that their “intertwined but also independently diverse interests allowed us to learn so much from each other.”

He sees a direct link between their international upbringing and their shared interdisciplinary mindset.

“Growing up with a diversity of experiences — different cultures, beliefs and ways of life — has translated into our diversity of thought,” he says. “This allowed us to think about how anything we do can be translated across borders and be used to break down barriers.”

Up next: Mogtaba has an offer to return to Amazon — and is also collaborating with his siblings on a new business that uses AI voice agents to improve 911 calls and emergency response times.

“We’re building a startup that addresses many of these issues, allowing us to help save lives.”

— Original story by Rahul Kalvapalle for

Undergraduate Class of 2025

This year’s undergraduates leave behind more than just completed degrees — they leave a legacy of curiosity, creativity, and community. Get to know the graduates through their own words as they look back on their experiences and ahead to what comes next.

• Helen Li

  Helen Li, Computer Science Specialist with a focus in Computational Linguistics and Natural Language Processing, Artificial Intelligence and Statistics Major 

  "Choosing computer science made me feel like I wasn’t picking just one thing, because I was able to combine many different fields, as technology manifests itself in various parts of our day-to-day life."

  Read the full Q&A with Helen Li →

• Jacqueline Seal

  Jacqueline Seal, Computer Science Specialist

  "Take an elective course completely unrelated to your program of study, try out a bunch of clubs and see which ones feel the most fun and rewarding to you, and generally keep an open mind to the huge diversity of opportunities that U of T offers."

  Read the full profile on Jacqueline Seal →

• Leo Tenenbaum

  Leo Tenenbaum, Computer Science Specialist and Math Minor

  "I was already living in Toronto and had heard that U of T had a great computer science department, so it was only natural to apply."

  Read the full profile on Leo Tenenbaum → 

• Sarah Walker

  Sarah Walker, Computer Science Specialist with a Focus on Computer Vision and Artificial Intelligence

  "I thought it would be good to get a broader sense of what is out there and what people could do with computer science; that, in part, helped me decide on what I wanted to pursue or at the very least what I didn't want to pursue."

  Read the full Q&A with Sarah Walker → 

• Taylor Whatley

  Taylor Whatley, Computer Science Specialist

  "From then on, I would often see complicated or intricate programs, and I would say, 'I want to learn how to make that,' and that motivated me a lot to improve through my computer science journey." 

  Read the full Q&A with Taylor Whatley →

2025 MSc & PhD Graduates

Ben Cookson and Sara Sabour, two graduates from the research stream, reflect on their time in the program and the work that defined it. Their profiles highlight the focus, depth, and persistence required to navigate graduate-level research, from early-stage exploration to final results.

• Ben Cookson

  With a passion for theoretical computer science, Ben earned his MSc at the University of Toronto, publishing two papers at AAAI and contributing to the academic community through the Theory Student Seminar. Now pursuing a PhD at U of T, he continues to explore social choice theory and fair AI systems, aiming for a future in academia.

  Read the full Q&A with Ben Cookson →

• Sara Sabour

  Sara’s PhD journey at the University of Toronto built on her earlier master’s and groundbreaking work at Google with Geoffrey Hinton, leading to impactful research in computer vision and 3D scene understanding. Her contributions to making AI systems more robust and interpretable reflect a deep commitment to both advancing the field and mentoring the next generation of scientists.

  Read the full Q&A with Sara Sabour →

MScAC Class of 2025

Blending academic depth with industry insight, the MScAC graduates bridges innovation and application. These profiles highlight how students navigated intensive coursework, cutting-edge applied research, and real-world internships to launch impactful careers.

• Aneri Gandhi

  With a strong foundation in computer science from IIT Bhubaneswar and two years at Google, Aneri pursued the Artificial Intelligence concentration to blend research with real-world application. Their journey included an impactful internship at AMD in Toronto’s vibrant tech scene and has led to a fulfilling role as an AI Engineer at Chubb.

• Anannya Popat

  With a bachelor’s in computer science from VIT and a passion for AI-driven user experiences, Anannya leveraged internships and research to dive straight into the program’s AI concentration. Her impactful internship at UHN’s Surgical Artificial Intelligence Research Academy (SARA) led to a role developing 3D surgical planning tools — blending cutting-edge tech with real-world healthcare impact.

• Carolina Villamizar Agudelo

  With a background in electrical engineering from Colombia and a growing passion for building technology, Carolina joined the MScAC program to bridge foundational computer science with real-world impact. Her internship at D-Wave Systems led to a full-time role as a backend developer, where she continues to grow while exploring accessibility-focused tech projects on the side.

• Preet Vimalkumar Viradiya

  Graduating with top honors in AI and machine learning from Amity University, Preet joined the MScAC program to gain hands-on industry experience and broaden his technical foundation. His internship at J-Squared Technologies evolved into a full-time role blending machine learning with strategic business initiatives — fueling his growing interest in leadership and a potential future in business school.

• Barry Xue

  With a data science background from UC San Diego and early biotech internships, Barry joined the MScAC program to deepen his technical and research skills. His internship at Sanofi’s innovation hub offered hands-on experience in industry research, paving the way for a continued role in biomedical AI and a future in applied science.

CS-Can | Info-Can has recognized three University of Toronto Computer Science faculty members for their outstanding contributions to the field. These national honours celebrate excellence in research, education, and service within the Canadian computer science community.

Faith Ellen

Lifetime Achievement Award

A trailblazer in distributed computing, Professor Faith Ellen has been awarded for her lifetime contributions to computer science. Her work has shaped the theoretical foundations of the field and inspired generations of researchers.

Read more about Faith Ellen’s award → 

Diane Horton

Excellence in Teaching Award

Renowned for her dedication to teaching and curriculum development, Professor Diane Horton has been recognized for her exceptional impact on computer science education. Her leadership has transformed how students engage with computing at U of T and beyond.

Read more about Diane Horton’s award →

David Duvenaud

Outstanding Early Career Researcher Award

An innovator in machine learning and AI, Professor David Duvenaud has received the Outstanding Early Career Researcher Award. His research bridges deep learning and probabilistic modeling, with applications ranging from healthcare to generative models.

Read more about David Duvenaud’s award →

David Duvenaud has received the in recognition of his contributions to machine learning, AI safety and AI governance.

Duvenaud, an associate professor in the University of Toronto’s şŁ˝ÇĘÓƵ of Computer Science, is recognized for his contributions to machine learning, particularly through his development of neural ordinary differential equations (Neural ODEs). This research allows deep learning models to represent the continuous changes of real-world phenomena like physical systems or biological processes, earning a Best Paper Award at the .

Duvenaud's work has influenced how researchers build systems that can learn from complex, real-world data. His research group applies these methods to challenges like analyzing medical data and improving how computers make predictions.

His research also spans cancer genomics, DNA design and molecular chemistry. In collaboration with biologists and chemists, Duvenaud has developed machine learning tools to simulate tumour evolution, optimize DNA sequences and propose new molecules based on experimental data.

In 2022, Duvenaud pivoted to AI safety research. He first that allow model trainers to prove claims about their training data — essential for AI governance.

In a full-time position at Anthropic in 2023–24, Duvenaud led the AI company’s alignment evaluations team. The team developed tests for deceptive behaviors, situational awareness and coordination in large language models (LLMs). With Anthropic, Duvenaud co-authored several highly impactful papers on misalignment, including that showed how human feedback can incentivize AI systems to tell users what they want to hear rather than the truth.

Duvenaud has also served as an advisor to AI startup , helping direct research projects about personalizing LLMs.

In 2025 he was appointed to the federal Safe and Secure Advisory Group, providing guidance to the Government of Canada on AI safety, responsible development, and international collaboration on global AI standards.

Duvenaud is co-chair of the , a co-founder of the and a founding member of the . His previous honours include a Sloan Research Fellowship, a CIFAR AI Chair, a Google Faculty Award and multiple best paper awards at leading conferences.

“David’s work is a powerful example of how foundational research can shape the future of computing,” said Eyal de Lara, professor and chair of the şŁ˝ÇĘÓƵ of Computer Science. “This well-deserved honour recognizes his leadership in both technical innovation and AI safety.”

Diane Horton has received the , a national honour that recognizes exceptional teaching ability and innovation in computer science education.

Horton, a professor in the teaching stream of the şŁ˝ÇĘÓƵ of Computer Science at the University of Toronto, has earned widespread respect for her engaging teaching style, leadership in curriculum reform and commitment to student success. Her work has shaped how computer science is taught at U of T and influenced educators across Canada and beyond.

Horton pioneered a “semi-flipped” classroom model that blends pre-class preparation with in-class problem-solving. This approach enables students to engage deeply with complex material while giving instructors the flexibility to adapt their teaching within a lecture to students’ needs based on their work on active learning exercises. Her courses, including and , are known for their clarity, rigour and thoughtful design.

She also led the most significant curriculum overhaul in the department’s 60-year history, introducing new courses, eliminating redundancies and modernizing content to better prepare students for today’s challenges. Thousands of students have benefited from the changes.

In 2020, Horton co-founded the , which integrates ethics modules into computer science courses. The program, the first of its kind in Canada, has been recognized with the University of Toronto’s Northrop Frye Award and the 2025 D2L Innovation Award in Teaching and Learning.

Horton’s influence extends beyond teaching. She has helped build the department’s teaching stream faculty, mentored colleagues and led workshops on pedagogy at institutions across North America and internationally. Her work has been published in more than 20 peer-reviewed papers on computer science education.

Students consistently praise Horton for her clear explanations, interactive lectures and genuine care for their learning.

She also created several long-running programs that support students outside the classroom, including the Alumni-Student Mentorship Program, the with Mario Badr, and brought to the department.

Horton also co-created the department’s Undergraduate Summer Research Program, an initiative that enhances the research experience of undergrads by bringing them together for career and community-building events.

“Diane’s impact on our department and our students is profound,” said Professor Eyal de Lara, professor and chair of the şŁ˝ÇĘÓƵ of Computer Science. “She has not only elevated the quality of teaching at U of T but has also supported educators across Canada and beyond through her mentorship, workshops and ethics initiatives. This award is a well-deserved recognition of her leadership and vision.”

Professor Faith Ellen has spent over four decades breaking barriers and pushing the boundaries of theoretical computer science. When she joined the University of Toronto in 1986, she was the only female faculty member in the şŁ˝ÇĘÓƵ of Computer Science. Since then, she's helped shape the field of parallel and distributed computing while mentoring a generation of future scholars.

Her pioneering work has earned her a 2024 Lifetime Achievement Award from CS-Can | Info-Can, Canada’s national academic organization for computer science.

The award recognizes current or former faculty members in Canadian computer science departments, schools and faculties who have made “outstanding and sustained contributions” to the field over the course of their careers. The awards can be for achievements in research, teaching or service.

Ellen is internationally known for proving that some computational problems are either impossible to solve or require significant amounts of resources, such as time or space. This understanding helps researchers focus on simpler versions of these problems or different settings where they can be solved. She co-authored the book, Impossibility Results for Distributed Computing, which is a key resource for researchers and students.

Ellen and her students have obtained fundamental results about achieving consensus — a crucial part of many distributed systems like blockchains — and weaker versions of consensus that can be solved more easily. She developed a method to efficiently store numbers in a way that makes it quick to find the closest value, and proved no algorithm can solve this problem asymptotically faster.

Another of her innovations is a non-zero indicator, which helps processors efficiently check if a resource is being used by other processors. This algorithm is used in some computer systems to manage their memory. Her work has earned her and her students numerous best paper awards.

University Professor Allan Borodin can’t imagine a stronger candidate for this award.

“She is an exceptional scientist, a pioneer in a very important area of research, and an extremely effective mentor who has directly impacted Canadian theoretical computer science,” he said.

Ellen has been a leader in her research community, serving on committees for over 50 conferences, and holding key positions such as program committee chair for top conferences and vice president of the Association for Computing Machinery (ACM) Special Interest Group on Algorithms and Computation Theory. She also directed the CRA-W Canadian Distributed Mentorship Project for undergraduate women in computer science for ten years.

Beyond her research, Ellen is a dedicated mentor and educator, influencing a generation of researchers. Six of her former PhD students are now faculty members at Canadian universities, and one received the CS-Can | Info-Can Canadian Computer Science Distinguished Dissertation Award. She currently serves as Associate Chair, Graduate Students in the şŁ˝ÇĘÓƵ of Computer Science.

In 1992, to build community and support the retention of women researchers in the department, she founded DCSWomen, which provides a supportive environment for female graduate students, postdoctoral fellows and faculty members.

She holds the Bell Canada University Labs Chair in Information Systems and became a Fellow of the ACM in 2014.

Ellen joins 12 other faculty members from the şŁ˝ÇĘÓƵ of Computer Science who have received this award since its inception in 2014.

Eyal de Lara, professor and chair of the şŁ˝ÇĘÓƵ of Computer Science, praised Ellen for her achievements as a trailblazing researcher and mentor.

"This award is a well-deserved testament to Faith’s outstanding contributions to theoretical computer science and her passion and dedication to mentoring female students and researchers in our department,” he said.

Read the full CS-Can | Info-Can announcement→

University of Toronto computer science professors Daniel Wigdor and Tovi Grossman have announced a new initiative to help Canada benefit economically from university research and top tech talent. The pair are among the co-founders of , a Toronto-based venture studio with the ambitious goal of launching 50 artificial intelligence (AI) companies over the next five years.

“Canada has been dramatically underperforming and failing to take up the incredible innovation happening here,” . “With the right investment of community, of infrastructure, of capital and of innovation, we can really solve that problem.”

Axl is designed to bridge the gap between academic research and commercial application. By identifying real-world business problems and matching them with entrepreneurial talent and cutting-edge AI research, the studio hopes to foster a new generation of Canadian tech companies. The venture recently secured a $15-million investment fund, with Wigdor serving as chief executive and lead investor.

The studio is headquartered at the , home to the and a hub for AI research in Canada. Axl’s leadership team also includes entrepreneur Ray Sharma and former Telus executive David Sharma. The initiative has attracted support from prominent investors, including mining executive Rob McEwen and Smart Technologies co-founder David Martin.

Grossman, who serves as Axl’s chief scientist, emphasized the studio’s commitment to impactful innovation. One of its early projects, CodeAid, is an AI-powered educational tool that inverts traditional teaching models by having students teach an AI agent. Axl is also partnering with Canadian corporations to co-develop AI solutions tailored to industry needs, with Dillon Consulting announced as its first partner.

What role can Canada play in the global technology revolution? What are the factors driving optimism and concern around artificial intelligence? How are entrepreneurs harnessing AI to build new ventures?

These are some of the themes that will be addressed by Geoffrey Hinton — a U of T University Professor Emeritus of computer science, the “godfather of AI” and — at a fireside chat held at U of T’s Convocation Hall on June 25. Titled “,” the conversation will feature Hinton in dialogue with alumnus Nick Frosst — co-founder of AI language processing startup , who was Hinton’s first hire at Google Brain.

Part of the Desjardins Speaker Series, the fireside chat is one of the most highly anticipated events of the inaugural , a showcase of Toronto’s burgeoning tech and innovation sector that runs from June 23-27 (in-person tickets to the Convocation Hall event are sold out, but the discussion will be livestreamed globally).

The discussion will be followed by the , an outdoor startup showcase and networking event held at the Knox College Quad and hosted by U of T in partnership with Desjardins and Dell Technologies. The gathering will showcase the myriad ways U of T is integrated with — and drives — Toronto’s innovation ecosystem.

“We have 15 of our most impressive startups that will be demoing and exhibiting outdoors, and we’ve invited stakeholders from across the university to attend — from students and faculty members to staff and academic leaders,” said Jon French, director of .

French noted the lawn party will be attended by tech founders, corporate leaders, investors, researchers and industry partners who are looking to engage with the U of T Entrepreneurship community.

Comprising 12 campus linked-accelerators, U of T Entrepreneurship is one of the world’s leading university business incubators. U of T entrepreneurs have created more than 1,200 venture-backed companies that have generated more than 17,000 jobs and raised over $12 billion in funding in the last five years alone.

“Our students, faculty members and staff are forging companies in emerging tech spaces such as AI and quantum computing, but also increasingly in the sustainability and climate realm,” said French. “These businesses offer multi-pronged benefit to Canada, combining social impact — tackling some of the most pressing challenges of our time — while creating jobs and strengthening the economy.”

The insights and impact of U of T innovators will be on display throughout Toronto Tech Week, starting with the official kick-off event on June 23: and featuring speakers including Phil de Luna, adjunct professor of materials science and engineering at U of T. Held at Convocation Hall, the event will see BetaKit unveil the print version of its , which will highlight the individuals and organizations advancing Canada's tech sector.

On June 24, attention shifts to “şŁ˝ÇĘÓƵcoming," the , which will feature remarks from visionaries including U of T’s Raquel Urtasun, CEO of autonomous trucking startup and professor of computer science in the Faculty of Arts & Science, Sanja Fidler, vice-president of AI research at NVIDIA and associate professor of mathematical and computational sciences at U of T Mississauga, and alumnus Aidan Gomez, co-founder and CEO of Cohere.

That morning will also see U of T’s Rotman School of Management host the Super Session 2025, with top graduating ventures from CDL’s global network pitching to investors and business leaders.

Then, on June 25, the will convene a session of lightning talks on AI solutions, and a discussion on how Canadian startups can build and harness AI. Held at the Schwartz Reisman Innovation Campus, the event will culminate with a livestreaming of the Hinton-Frosst fireside chat.

In addition to shining a spotlight on cutting-edge technologies, Toronto Tech Week also features several events highlighting the people — leaders, visionaries and teams — driving innovation. These include a June 26 panel discussion featuring alumnus Mike Murchison, co-founder and CEO of AI customer service startup , that will focus on leadership, cultivating trust and how to navigate setbacks to one’s confidence.

by Sharmeen Somani

As U of T’s Class of 2025 celebrates convocation throughout June, five graduating Computer Science students reflect on their time as undergraduates.  

These spotlights showcase the diverse journeys of CS students, their varied research interests and their aspirations for the future. 

Name: Helen Li 

College: Victoria College 

Program: Computer Science Specialist with a focus in Computational Linguistics and Natural Language Processing, Artificial Intelligence; and Statistics Major

Helen Li blended research, mentorship, and industry experience at U of T, shaping a path from human-computer interaction to a future in software engineering and AI governance.

"Choosing computer science made me feel like I wasn’t picking just one thing, because I was able to combine many different fields, as technology manifests itself in various parts of our day-to-day life."

Read the full Q&A with Helen Li → 

Name: Jacqueline Seal

College: Victoria College 

Program: Computer Science Specialist, Math Minor

Jacqueline Seal bridged computer science and life sciences through research and internships in computational biology, while embracing U of T’s diverse academic and extracurricular opportunities.

"Take an elective course completely unrelated to your program of study, try out a bunch of clubs and see which ones feel the most fun and rewarding to you, and generally keep an open mind to the huge diversity of opportunities that U of T offers."

Read the full profile on Jacqueline Seal → 

Name: Leo Tenenbaum

College: University College

Program: Computer Science Specialist and Math Minor

Leo Tenenbaum explored the theoretical side of computer science at U of T, culminating in a joint first-author publication on microarchitectural side channels.

"I was already living in Toronto and had heard that U of T had a great computer science department, so it was only natural to apply."

Read the full profile on Leo Tenenbaum → 

Name: Sarah Walker

College: Victoria College 

Program: Computer Science Specialist with a focus in Computer Vision and Artificial Intelligence

At U of T, Sarah Walker discovered how computer science could intersect with creativity, community, and advocacy — leading her to pursue law with a focus on AI and tech policy. 

"I thought it would be good to get a broader sense of what is out there and what people could do with computer science; that, in part, helped me decide on what I wanted to pursue or at the very least what I didn't want to pursue."

Read the full Q&A with Sarah Walker → 

Name: Taylor Whatley

College: Woodsworth College 

Program: Computer Science Specialist

Driven by a childhood fascination with how complex programs work, Taylor Whatley pursued computer science at U of T, where his curiosity led to impactful projects like Saturn and a Nintendo Entertainment System emulator.

"From then on, I would often see complicated or intricate programs, and I would say, 'I want to learn how to make that,' and that motivated me a lot to improve through my computer science journey." 

Read the full Q&A with Taylor Whatley → 

Drawn to challenging problems and creative solutions, Taylor Whatley built an NES emulator, developed Saturn — a replacement for a legacy assembly programming tool — and collaborated with professors and peers to improve computer science education at the University of Toronto (U of T). Alongside standout academic projects, Whatley gained hands-on experience through three internships at Apple, where he will soon return full-time. As he graduates, Whatley leaves a legacy of innovation and leadership, making technology more accessible for others.

This Q&A has been edited for clarity and length.

What inspired you to study computer science at U of T?

When I was a kid, I used to really enjoy putting together small command-line games in Batch Script for my friends. The language was super simple and was fairly easy to pick up. It also ran on the school computers, so it was easy to make a bunch of changes at home and then have my friends play it once I got to school. However, I noticed that people were creating games with full interfaces and 2D or even 3D visuals — so much more complex than my simple text-based command-line games! It all seemed like wizardry to me, and I felt motivated to learn how to create something that’s on par with that. From then on, I would often see complicated or intricate programs, and I would say, “I want to learn how to make that,” and that motivated me a lot to improve through my computer science journey. 

It sounds like you’re not one to shy away from a side project. Tell us about one project that stands out, and what motivated you to take it on. 

I’ve always been fascinated by problems that seemed especially challenging to tackle. For example, the problem of emulation (running programs designed for one architecture on a completely different architecture or system) is always a complicated problem to tackle. Where would you even start? Recently, I got around to finishing an that I started back in Grade 10. My team and I ultimately used it for our final project, where we attempted to apply some unique reinforcement learning techniques to teach Mario how to complete World 1-1 faster.

Tell us about the genesis of Saturn and how it’s being used. 

When I was taking CSC258, I had a particularly challenging time with the tool used for assembly programming at the time, called MARS. MARS had a dated interface, would frequently crash and often impeded my progress. During the winter break after the course concluded, I felt like I could make a better tool than MARS. I started with a modern foundation and began writing the interpreter, assembler, debugger, and user interface. Ultimately, I felt that I had something that worked reasonably well. I shared it with my friends and professor to try it out and gather feedback, and they noticed the improvement. 

Today, Saturn has mostly replaced MARS in for the Assembly programming component. Students use it to make a game in MIPS assembly for their final project. Today, I’m working with student Milo Mighdoll, and Professors and to add RISC-V support, bring an online collaboration feature up to speed, and prepare the tool for presentation at . 

What’s next for you?

I’ll be working at Apple starting in July, which I’m really excited about! I’ve worked at this team as an intern for the last three summers, so I know them well, and they’re really smart people.  Additionally, I’m working to prepare Saturn for the ITiCSE conference. The features are quite daunting, but we're making steady progress, and I’m excited to showcase everything at the conference in June. 

Unsure of what path to take after high school, Sarah Walker chose a direction that combined her interest in math with the creative potential of programming. That choice opened doors to a wide range of experiences — from campus leadership and mentoring through the DCS Ambassadors program to founding U of T Reads, a book club that connects students across disciplines. Along the way, she gained clarity about what matters to her and where she want to make an impact. Next stop after graduation: University of Toronto (U of T) Law, where she’ll explore the intersection of technology, policy, and AI governance.

This Q&A has been edited for clarity and length.

What inspired you to study computer science at U of T?

At the end of high school, I wasn't really sure what I wanted to do. But I enjoyed my math courses, so it felt right to study something related. I also took a couple of high school computer science classes, where we had the opportunity to work on a personal project, and I appreciated the creativity that coding allowed us to explore. I settled on the program at U of T because I was interested in research and graduate school, but also because of the vast breadth of courses it offered (both computer science-related and the number of courses we could take from other Arts & Science departments). 

You have been very involved in mentorship and leadership. Why was it important to you to get involved in student life at U of T?  

Honestly, my involvement in student life kind of crept up on me. In my first year, I was not very involved. I felt like I was missing out on the club experience, so I applied to a variety of clubs and positions in my second year. I thought it would be good to get a broader sense of what is out there and what people could do with computer science; that, in part, helped me decide on what I wanted to pursue or at the very least what I didn't want to pursue. Seeing how older students were making a difference was also inspirational. Eventually, as I gained more experience, especially with different kinds of research, I thought it might be worthwhile for me to take on more of a leadership or mentorship role. 

Tell us more about your experience being a DCS Ambassador for the past three years.  

It has been truly amazing to witness how the DCS Ambassadors program has evolved, enabling students like me to take on a more impactful role in the DCS community. When I first joined, we mostly did outreach. I recall a session on teaching coding to high school students, which was actually quite enjoyable. This past year, however, it was great being able to take on a more hands-on role within the current undergraduate community, whether through drop-in sessions or supporting events. Everyone has been super supportive and fun to work with, so I've had a great time. 

You founded U of T Reads in May 2024. What inspired you to start this book club, and what impact has it had on the campus community?  

I've always been a big reader and a bit of a writer. I attempted to start the club in 2021, but it didn't quite pick up as much due to COVID-19. But as I continued to fill my course load with computer science courses and not much else, I realized that I wasn't reading as much as I used to, much less the kinds of stories that really make you want to think. This felt somewhat of a shame! (Although we do also read lighter books!) So far, it's been a really great way to discover new genres and perspectives — we're genre-agnostic and open to anyone, while getting to know some new people and enjoying some snacks. 

What’s one piece of advice that you would give to incoming students?  

Set your priorities straight, but don't be afraid to try new things. I think having a clear idea of what your goals might be really helps your time management — whether it’s how much you prioritize your courses versus extracurriculars, or how much time you should put aside to continue certain hobbies. However, being able to try new things is also a great way to gain experience and figure out what you enjoy doing. There are a few times when an event I wasn't so keen on became a really important learning moment for my future goals and path.  

What's next for you? How do you plan to intersect your computer science background with your plans of becoming a lawyer?  

I'll be returning to U of T for a JD degree. My initial interest is related to AI regulations and governance, but I'm very excited to see what the program has in store for me. 

Already living in Toronto and curious about the deeper concepts behind programming, Leo Tenenbaum chose the University of Toronto (U of T) to explore the theoretical side of computer science. What began as a one-semester research course evolved into a year-long experience that led to a joint first-author publication at ASPLOS 2025. Through their research on microarchitectural side channels, they discovered the trial-and-error nature of academic work and gained valuable hands-on experience in real-world computer science research. As they graduate, they reflect on how that journey, though intense, offered insights that will stay with them long after they leave U of T.

This Q&A has been edited for clarity and length.

What inspired you to study computer science at U of T?

I'd been interested in computer programming for many years and really wanted to learn more, especially about the more theoretical aspects of computer science. I was already living in Toronto and had heard that U of T had a great computer science department, so it was only natural to apply.

How did you get involved in research, and what did you learn from those experiences?

I got involved in research through the CSC494 Computer Science Project course. What started as a one-semester research course evolved into a year-long journey, culminating in a publication. I learned a great deal about microarchitectural side channels, as well as more broadly about the process of conducting academic research in computer science, formatting an academic paper, and navigating the review process. 

You published a paper as a joint first author at ASPLOS'25, a premier computer systems conference. Tell us more about that research experience. 

It was definitely an enlightening experience. One thing that stuck out to me is the amount of time spent on things that turned out to be dead ends. Of all the work we did, only a small fraction ended up in the final paper. However, it's impossible to know ahead of time what will work and what won't, so you simply have to keep trying new things. Overall, I found the process to be pretty stressful at times, but I'm glad I got to learn a bit about what it's like to do research in CS, even if I don't continue down that path. 

What’s one piece of advice you would give to incoming students?

Don't bite off more than you can chew. I know some people who had to miss lectures because they had so much going on, but that only made things worse as they fell behind in their courses. It's better to drop a course early on and take one in the summer than to end up drowning in work and stressed out about exams you aren't prepared for.

Jacqueline Seal combined a love of biology and programming to explore the intersection of computer science and life sciences. Originally enrolled in bioinformatics, she eventually gravitated toward computer science and mathematics, inspired by exceptional professors and hands-on experience. Through the Arts & Science Internship Program, she tackled real-world challenges ranging from antibody design in Germany to peptide therapeutics in Toronto.

Beyond academics, Seal supported first-year students as a math TA and embraced the University of Toronto’s (U of T) vibrant student life, from beekeeping to canoe portaging. After graduation, she’ll head to New York for an internship at the Flatiron Institute’s Center for Computational Biology.

This Q&A has been edited for clarity and length.

What inspired you to study computer science at U of T?

In high school, I discovered that I really enjoyed both my biology coursework and computer programming electives, and I was excited by U of T’s record of excellence in bioinformatics research, particularly the possibility of contributing to that research. I initially enrolled in both the bioinformatics and computational biology specialist (BOFO shoutout) and computer science major, but over time, I found myself gravitating more towards my pure CS and math classes. Throughout my degree, I’ve also been lucky to have had excellent computer science professors who have not only made the content approachable but also continually inspired me to do my best work.

You’re graduating with a CS specialist and math minor, and you also participated in the Arts & Science Internship Program (ASIP). Tell us more about how those areas of focus combined to shape your academic experience. How did you get involved outside of the classroom at U of T?

I’m incredibly grateful to have been part of — the two internships I completed through the program were some of the most formative experiences of my degree. The summer after my second year, I participated in the Rosetta Commons REU, working on computational antibody design at Leipzig University, and received plenty of support from ASIP staff. That opportunity led to a 16-month internship at ProteinQure in Toronto, where I helped advance computational methods for designing peptide therapeutics with non-canonical amino acids. Apart from that, one of the experiences I’ve valued most was working as a math department TA for two years. Not only was it incredibly rewarding to help first-year students navigate calculus, but being on the other side of the classroom has informed my approach to being a student myself.

What’s one piece of advice that you would give to incoming students?

Don’t worry too much about knowing *exactly* what you want to study in university or do after graduating. Take an elective course completely unrelated to your program of study, try out a bunch of clubs and see which ones feel the most fun and rewarding to you, and generally keep an open mind to the huge diversity of opportunities that U of T offers and to meeting the amazing variety of smart, kind people here. Some of my most memorable experiences at U of T were a product of stepping way outside my comfort zone and trying something new, whether it was dueling on the UC quad as Diablos in the Students' History Collective’s annual haunted campus tours, joining the archery and beekeeping clubs, or portaging a canoe 17km through downtown Toronto (twice) during the Davenportage.

What’s next for you?

I’ll be in New York City for an internship at the Flatiron Institute’s Center for Computational Biology, where I’ll be tackling interesting biomolecular design problems using computer science methods.

Drawn to the University of Toronto (U of T) for its rigorous computer science program and dynamic downtown setting, Helen Li discovered a passion for building technology that intersects with everyday life. Research internships in human-computer interaction and AI sparked her curiosity, while three internships at Microsoft helped her develop real-world engineering skills.

As she prepares to graduate, Li reflects on the meaningful experiences that have shaped her time at U of T, especially her roles in mentorship and leadership through the DCS Ambassadors program and Women in Science and Engineering (WISE), where she helped empower and support hundreds of fellow students. 

This Q&A has been edited for clarity and length.

What inspired you to study computer science at U of T?

When applying to undergraduate programs, I found it difficult to pick an area of study because I couldn’t decide on just one thing. Choosing computer science made me feel like I wasn’t picking just one thing, because I was able to combine many different fields, as technology manifests itself in various parts of our day-to-day life. I was specifically drawn to U of T for the rigour of its computer science program and its location in downtown Toronto.

You have been very involved in mentorship and leadership. Why was it important to you to get involved in student life at U of T?

Coming from a high school with less than 1,000 students in total, U of T felt huge and slightly frightening to navigate for me at first. Getting involved with student life helped me find my smaller communities within the large campus environment. Taking part in mentorship and leadership opportunities like the DCS Ambassadors program allowed me to give back by helping more students like me find their place at U of T, too!

Tell us more about how you got involved with research internships and how those experiences shaped your time as an undergraduate.

After emailing a few professors and lab groups about volunteer opportunities, I was fortunate to begin research in my second semester at U of T under the supervision of Professors and . Over the past few years, working on a variety of projects at the and the challenged me to approach problem-solving with more curiosity and flexibility. These experiences also shaped my research interests at the intersection of human-computer interaction and artificial intelligence, reinforcing my commitment to building technologies for positive impact.

As for internships, I was accepted to the Explore (Software Engineering + Product Management) program at Microsoft the summer after my first year. Since then, I interned twice more at Microsoft as a software engineer, building new, customer-facing features for several Azure (Microsoft’s cloud computing platform) product teams. These experiences provided me with valuable exposure to the engineering lifecycle in the industry, pushed me to pick up unfamiliar technologies quickly, and taught me how to build scalable, user-centred solutions in fast-paced environments.

You've been an advocate for women in tech. Can you share some of the initiatives you've been involved in and their impact?

As a four-time executive, I have spent a lot of my time at U of T with the chapter on campus. One of my favourite WISE initiatives is our annual national conference! Every January, we host over 500 delegates across Canada for a weekend filled with speaker events, workshop sessions, and networking opportunities. It’s always inspiring to see everyone come together and walk away from the conference weekend with something new, whether it's insights, opportunities, or new friends!

What’s one piece of advice that you would give to incoming students?

Always be the biggest advocate for yourself! Don’t let self-doubt get in your way of trying new things or reaching for bigger opportunities.

What's next for you?

This fall, I will start my first full-time job as a software engineer at Microsoft on their Silicon Valley campus! Concurrently, alongside my job, I will also be pursuing the master’s in computer science program at Stanford University on a part-time basis. I’m excited for the next few years in the Bay Area!

completed his MSc in computer science at the University of Toronto in March 2025. During his master’s studies in the Theory Group, he made a mark by publishing two papers in the AAAI Conference on Artificial Intelligence — a top conference in AI and social choice theory. Beyond his research, Cookson played a key role in fostering academic community by organizing the Theory Student Seminar, a student-led forum for sharing and discussing theoretical computer science research.

In this Q&A, Cookson reflects on his academic journey, the ideas driving his research and what lies ahead as he embarks on his doctoral studies.

This Q&A has been edited for clarity and length.

What initially drew you to the field of computer science, and how did you decide to pursue your MSc in CS at U of T?

I originally planned to become a software engineer, but during my undergrad I fell in love with the mathematical and theoretical side of computer science. By the time I graduated, I hadn’t done much research in theory, but I knew I’d regret not giving it a shot. That led me to apply to master’s programs focused on theoretical computer science. Once I was accepted to U of T, the decision was easy — Canada is a great country, Toronto is a great city, and U of T has an amazing CS department. I was especially excited by the research happening here in social choice theory.

What does social choice theory entail, and what got you interested in it?

Social choice theory studies how groups can make decisions when individual preferences differ. These decisions can range from organizing national elections to choosing a restaurant with friends. I find it incredibly cool because it combines everything I enjoy about theoretical computer science with ideas from economics, political science and philosophy, among other fields. Designing fair decision-making procedures requires creativity, problem-solving and deep mathematical thinking. But before you even get to that, you have to define what “fair” means in a given context, which is a fascinating challenge in itself.

What are some practical applications of your research?

My master’s research focused on resource allocation — figuring out how to fairly distribute items among people who all want them. I designed new algorithms for problems like dividing food donations among food banks or assigning shifts to nurses. More recently, I’ve been exploring how social choice theory can help design fairer AI systems. As we increasingly rely on AI to make decisions, it’s important to ensure those systems reflect people’s preferences in a fair and representative way. I think this is a really exciting and important direction for the field.

Who were your biggest mentors during your MSc studies?

I owe a lot to my advisors, and . They took a chance on me when I had little research experience in theoretical computer science and have been incredibly supportive ever since. They gave me interesting problems to work on, helped me navigate the research process and offered great advice on managing grad school. Beyond that, the CS department and Theory Group have cultivated a fantastic culture. Every faculty member I’ve interacted with has been kind, helpful and encouraging.

What advice would you give to future MSc students in computer science at U of T?

Grad school is fun and rewarding, but it’s also hard. Producing good research takes persistence, long hours and sometimes a bit of luck. You’ll have ideas that don’t work out, and that’s okay — it’s part of the process. Talk through everything with your advisor, take their advice seriously, but also don’t be afraid to explore your own ideas. One of the most valuable things you can learn in a master’s is how to generate novel ideas and creative solutions to problems.

Since graduating with your master’s degree in March, you’ve stayed on in the department as a PhD student. What motivated that decision, and where do you see your research journey taking you in the future?

Just like joining U of T for my MSc, deciding to stay for my PhD was one of the easiest decisions I’ve ever made. I love what I do and am very happy I get to continue doing it for a few more years. Right now, I think I’d like to try for a position in academia after I graduate, but I still have some time to figure out exactly what my plans are.

As she prepares to graduate with a PhD in computer science from the University of Toronto, Sara Sabour reflects on a journey that has taken her from high school programming competitions to cutting-edge research at Google and collaborations with AI pioneer Geoffrey Hinton. Her work in computer vision and machine learning, particularly in object representation and 3D scene understanding, has contributed to making artificial intelligence systems more robust, interpretable and human-like in their perception of the world. 

In this conversation, Sabour, who previously earned a Master of Science degree in computer science from U of T in 2016, shares insights into her research, the challenges of doctoral studies and the mentors and moments that shaped her path. 

This interview has been edited for clarity and length. 

What first drew you to the field of computer science (CS)? 

In high school, I competed in programming Olympiads and realized I was very good at solving problems and coming up with algorithms. I could spend hours coding without getting tired. That passion led me to study computer science in undergrad. Initially, I leaned toward theoretical CS, but a machine learning course opened my eyes to how computers could learn on their own. That fascination eventually led me to computer vision and a PhD.

After you completed a master’s degree in CS from U of T in 2016, you joined Google as a researcher and worked with Geoffrey Hinton there. How did that experience shape your academic path? 

Working with Geoff reignited my passion for research. His joy in solving problems, regardless of deadlines or recognition, was inspiring. That experience convinced me to pursue a PhD. I later joined the CS PhD program at U of T, where Geoff co-supervised my work alongside . Both were incredibly supportive and influential in shaping my research direction.

Tell us more about your PhD research. 

My work focuses on teaching AI to understand objects in images similar to how humans do. Traditional models often rely on shortcuts, like associating green backgrounds with dogs and blue backgrounds with fish, which makes them fragile. I worked on capsule networks and unsupervised learning methods that help models recognize objects based on their parts and spatial relationships. This makes them more robust and better at generalizing to new situations, like recognizing a face from different angles or in unfamiliar settings.

What are some real-world applications of your research? 

One example is smart home cameras. Current models might misidentify a spider on the lens as a package. Our methods can better detect and remove unexpected objects. In autonomous driving, this research could help identify unusual signs or obstacles. I’m also applying this to camera pose estimation — figuring out where a camera is in space — which is useful for VR and for training generative AI models that can simulate 3D environments.

What challenges did you face during your PhD, and how did you manage them? 

The most challenging aspect for me personally was the flow of work during the PhD. The workload often came in waves — quiet months followed by intense periods with deadlines, reviews and exams all at once. I learned to focus on one task at a time and accept that it’s okay not to juggle everything perfectly. That mindset helped me stay grounded.

How did your time at U of T shape you personally and academically? 

The diversity at U of T was eye-opening. I met people from all over the world with unique approaches to life and work. It helped me grow more open-minded and appreciative of a wide range of perspectives.

Who were your biggest mentors during your studies? 

Both and were incredible mentors. David was very supportive and open to students exploring outside of their very specialized areas of research. Geoff’s passion was contagious. He’d stay up all night running experiments just out of curiosity. They both taught me that genuine interest in a problem is the best motivation.

What are you most proud of from your PhD experience? 

One highlight was mentoring high school students, especially girls in STEM. Some had internalized the idea that computer science wasn’t for them. I was proud to help challenge those assumptions and show them that success in this field doesn’t require fitting a certain mould.

What advice would you give to future CS PhD students at U of T? 

Take full advantage of the learning opportunities a PhD offers. I’m glad I took courses outside my department that challenged me and broadened my perspective. Also, don’t hesitate to reach out to professors beyond your supervisor. Many are open to collaboration and happy to support students who show initiative.

What’s next for you after graduation? 

I’m taking a short break, then continuing some projects at Google. I want to scale up my research so it can have a broader impact and help push the field forward. I’m also exploring academic positions, especially because I’ve enjoyed mentoring and teaching.  

Sitting at the heart of the şŁ˝ÇĘÓƵ of Computer Science, Sarah Lavoie welcomes all who visit with a cheerful greeting and a smile.

Lavoie, who has dedicated 14 years to the department, has been honoured with the 2025 Dean’s Outstanding Administrative Service Award by the University of Toronto’s Faculty of Arts & Science.

The award is given to a Faculty of Arts & Science administrative staff member whose outstanding contributions to administrative service have made a positive impact on teaching, research or general administration.

Lavoie’s journey with the department began in 2008 as a summer student administrative assistant. After completing her degree at the Ontario College of Art & Design University (OCAD U), she joined the department full-time in 2011 as a departmental assistant.

“Sarah’s professionalism and personal touch help build a sense of community, making our large department feel more like a family,” said Eyal de Lara, professor and chair of the şŁ˝ÇĘÓƵ of Computer Science.

In her role, Lavoie is the first point of contact for students, parents, external guests, alumni, faculty and staff.

She has also navigated the department through numerous challenges, including the COVID-19 pandemic. She was one of the few administrative staff members who remained on campus, ensuring the office continued running smoothly. Her presence was a source of comfort and stability for faculty, students and staff during those uncertain times.

"Sarah Lavoie sits at the very heart of our department,” said Sara Burns, manager of the office of the chair. "In addition to supporting our faculty, staff and students, Sarah is our de facto morale officer as she always has a cheerful greeting, professional manner and a genuinely warm smile for those who pass her door."

Nominators noted that her commitment to the department's well-being is evident in her proactive approach to learning new skills.

Lavoie independently learned various software tools and plays a key role in organizing and running departmental events, from the annual holiday party to the Distinguished Lecture Series.

“Sarah embodies the best aspects of our department's culture,” said Jacqueline Smith, associate professor, teaching stream. “We are very lucky to have her.”

“I hope that my positive outlook and my kind and cheerful demeanour leave even a small impression on the people that pass through DCS,” said Lavoie. “I’m thankful for the acknowledgment from the Dean of Arts & Science, and I’m incredibly grateful for the support and recognition from the chair’s office and those who wrote letters of support for my nomination.”

is reshaping how computer science is taught at the University of Toronto, blending innovation with mentorship to create a more engaging undergraduate experience.

In recognition of his dedication, creativity and an unwavering commitment to student success, Liu has received a .

The annual award recognizes teaching excellence in undergraduate and graduate education with a focus on classroom instruction, course design and curriculum development.

Liu, an associate professor in the teaching stream in the şŁ˝ÇĘÓƵ of Computer Science, has played a key role in fostering a strong sense of community among his students, particularly through two foundational first-year courses.

These courses were intentionally created to include detailed notes and interactive mini-lectures to develop engaging and participatory sessions for students. Liu has written course notes for many other courses spanning first-, second-, and third-year.

Liu's commitment to a supportive learning environment is reflected in feedback from his students, who praise the clarity and organization of his materials.

He has led efforts to introduce a semi-flipped classroom model in several undergraduate courses. In this approach, students review some instructional content, such as videos or readings, before class, while in-person sessions explore core concepts with problem-solving activities and introduce more complex topics with mini-lectures. The hybrid format encourages more interactive learning and is an essential part of the department’s curriculum.

But Liu's impact also extends beyond the classroom. A strong advocate for interdisciplinary collaboration, he integrates computational thinking across multiple disciplines. Alongside Professor Nathan Taback in the şŁ˝ÇĘÓƵ of Statistical Sciences, he designed a new interdisciplinary minor in applied data science, which begins accepting students this summer.

Liu has received two LEAF Impact Grants for interdisciplinary computing education initiatives with the şŁ˝ÇĘÓƵ of Chemistry and the human biology program.

As a faculty lead on the , Liu has helped design modules that pair ethical concepts with technical material, enriching the learning experience for students across different fields.

Liu's commitment to interdisciplinary collaboration goes beyond curriculum — it's about preparing students for the real world.

He manages the team, which offers experiential learning opportunities to students who develop and maintain high-quality software that supports undergraduate education in the department. He has supervised over 180 undergraduate students on these software projects over the past ten years.

Beyond his innovative teaching methods and interdisciplinary initiatives, Liu is a key ambassador for cultivating and maintaining relationships across campus.

He helped redevelop the Faculty of Arts & Science’s Computer Science first-year admission category to provide a direct entry pathway to Computer Science programs, launched in 2020-2021, through extensive consultation and collaboration with departments across the university. He currently serves as associate chair, undergraduate studies in the şŁ˝ÇĘÓƵ of Computer Science.

Eyal de Lara, professor and chair of the şŁ˝ÇĘÓƵ of Computer Science, praised Liu for his contributions to the department and across campus.

“This award is a well-deserved recognition of David’s enthusiasm and his commitment to our undergraduates,” said de Lara. “His contributions have strengthened our department in countless ways, from enhancing the student experience to shaping how we teach and collaborate.”

When isn't transforming the classroom experience for his computer science students at the University of Toronto, he's co-hosting "In the Loop," a popular podcast that helps undergraduates navigate their academic journeys.

In recognition of his dedication to student success, U of T’s Faculty of Arts & Science has awarded Badr an .

The annual honour recognizes teaching excellence in undergraduate and graduate education, focusing on classroom instruction, course design and curriculum development for early career faculty members.

An assistant professor in the teaching stream, Badr joined the faculty of the şŁ˝ÇĘÓƵ of Computer Science in 2020. Since then, he has made it a priority to help students build strong support networks, whether mentoring graduate students, supervising work-study projects, or co-hosting the "In the Loop" podcast with fellow teaching stream faculty member Diane Horton.

In the classroom, Badr’s use of active learning techniques, such as embedding "worked examples" in lectures, allows students to engage more deeply with the material. This step-by-step approach has been especially effective in challenging courses, making complex concepts more accessible and boosting student confidence.

But Badr’s impact extends beyond individual courses. His leadership in curriculum development has broadened learning opportunities for students, most notably through his proposal and launch of CSC368: Computer Architecture. Drawing on his PhD research, the course quickly filled with a substantial waitlist, highlighting the demand for innovative and specialized offerings.

Badr is also a leader in strengthening the department’s learning community. He plays an active role in Computing Education Research conferences and the Arts & Science Teaching & Learning Community of Practice, sharing insights and collaborating with colleagues from various disciplines.

His work with the DCS Ambassadors program has strengthened connections between upper-year students and incoming cohorts, offering mentorship that fosters academic and personal growth.

“Mario’s enthusiasm for learning is infectious, and this award is a reflection of his significant efforts,” said Eyal de Lara, professor and chair of the şŁ˝ÇĘÓƵ of Computer Science. “Mario’s work improves the learning experience for our undergraduate students and sets a high standard for innovative course development."