Meet the mscac
ambassadors
Welcome to the MScAC Ambassador Program
Congratulations and welcome to the MScAC community! As a newly admitted student to the Master of Science in Applied Computing (MScAC) program at the University of Toronto, we encourage you to connect with our MScAC Ambassadors. They are current second-year students and alumni who are ready to share their experiences and help you prepare for the journey ahead.
Our ambassadors offer insights on academics, concentrations, internships, student life and careers in applied computing. Browse the profiles below and connect with someone whose background or experience resonates with you.
Connecting with an Ambassador
After you submit a connection request, please allow 48–72 hours for a response. Many of our ambassadors are busy working professionals, and we appreciate your patience.
To help manage their schedules, ambassadors may accept or decline connection requests. If your request is accepted, you will receive an email with their contact information so you can connect directly. If your request is declined, you’re welcome to reach out to another ambassador or contact the MScAC program team for support.
Artificial Intelligence
Keyu Bai
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Computer Science, Harbin Institute of Technology
- Internship company: Geotab Inc.
- Current position: Research Machine Learning Scientist, Layer 6
- Research interests: Machine Learning
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I recently graduated with a Master of Science in Applied Computing (AI Concentration) from the University of Toronto, where I maintained a 4.0/4.0 GPA. My research interests lie in machine learning, large language models, and scalable AI systems, with a focus on controllable inductive bias, efficient fine-tuning, and real-world deployment.
I have interned at Geotab, Tencent, and SenseTime, where I led large-scale data engineering, optimized production ML pipelines, fine-tuned LLMs with techniques such as QLoRA and continued pretraining, and integrated machine learning models into real-world systems to improve performance, efficiency, and interpretability.
Yifeng Chen
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Artificial Intelligence, Beihang University
- Internship company: Geotab Inc.
- Current position: Newly graduated
- Research interests: Agentic AI, LLM applications
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Recently graduated and officially obsessed with Agents! I spent my internship teaching Google Kubernetes Engine how to save money using autonomous agents. My research interests are all about LLM applications and building systems that can think for themselves. I’m currently in that “Newly Graduated” sweet spot — looking for my next challenge and excited to connect with the community. Whether you’re an alum with advice or a new student just starting out, let’s chat about where AI is headed!
Gayathri Girish
- Cohort: 2023-24
- Concentration: Artificial Intelligence
- Undergraduate program: Electronics and Communications, Vellore Institute of Technology (VIT)
- Internship company: Sinai Health
- Current position: Machine Learning Engineer, Sinai Health
- Research interests: NLP, LLM
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Gayathri Girish is a Machine Learning Engineer at Sinai Health in Toronto, where she builds and deploys GenAI-powered clinical tools that improve reporting efficiency and patient care. With a Master’s in Computer Science (AI focus), she specializes in LLMs, medical imaging, and end-to-end AI product development from research and modeling to deployment.
Rémi Grzeczkowicz
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Engineering, École Polytechnique, France
- Internship company: Kaliber Labs
- Current position: BNP Paribas, Data Scientist/PhD Candidate
- Research interests: Anything that has positive societal impact. I worked in cybersecurity, health care related projects and right now I’m working on Anti Money Laundering. It allows me to always learn a new field.
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Rémi Grzeczkowicz is an MScAC graduate with a concentration in Artificial Intelligence from the University of Toronto and a postgraduate engineer from École Polytechnique. His research spans explainable AI, cybersecurity, multimodal models and on-device intelligence. He is currently pursuing a PhD jointly conducted between BNP Paribas and Institut Polytechnique de Paris, focusing on agentic AI systems for anti–money laundering investigations. He has worked across Switzerland, Canada, the United States and France.
Muhan Li
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Telecommunications, Harbin Institute of Technology (Shenzhen)
- Internship company: Thomson Reuters
- Current position: Software Engineer, Cresta
- Research interests: Software Engineering, LLM, AI Agents
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Hi, I’m Muhan. Feel free to reach out to chat about MScAC or career paths in industry. For more details, please see my LinkedIn profile.
Alex Liu
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Computer Science Specialist, University of Toronto
- Internship company: AMD
- Current position: ML Research Engineer, AMD
- Research interests: Computer Vision, Computational Imaging, Deep Learning, Generative AI
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As an ML Research Engineer at AMD, I am passionate about bridging the gap between AI and the real world. My current work centres on developing cutting-edge computer vision and computational imaging technologies. On a personal level, I was born and raised in Edmonton. As a result, I’m a huge fan of the Oilers and mountains. In my free time I enjoy rock climbing, running, and playing guitar. I’m looking forward to meeting the next generation of talented MScAC students, so feel free to reach out!
Di Mu
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Computer Science, University of Leeds
- Internship company: Layer6 AI
- Current position: Machine Learning Research Scientist, Layer6 AI
- Research interests: LLM, RAG, Agentic System
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New Grad currently balancing code, coffee and life. I’ve transitioned from ‘clueless intern’ to ‘somewhat knowing what I’m doing.’ Open to connecting about course loads, industry prep or just venting about bugs.
Jiongan Mu
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Computer Science, University of Toronto
- Internship company: Ema
- Current position: ML Engineer, Ema
- Research interests: AI Agents, LLMs
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I’m an AI/ML Engineer at Ema, building the AutoBuilder, our conversational workflow builder that generates and orchestrates multi‑agent workflows from natural language. I architected it from zero to production, and it’s now used by business users to cut workflow creation and iteration from hours to seconds.
I recently completed my Master of Science in Applied Computing at the University of Toronto, focusing on computer systems and large language models. Previously, I worked as a backend software developer at Kijiji and contributed as both a research assistant and teaching assistant at U of T.
I specialize in designing custom AI systems that are efficient, reliable, and scalable for real-world business needs. Outside of work, I enjoy music — I sing and play piano and guitar.
Anannya Popat
- Cohort: 2023-24
- Concentration: Artificial Intelligence
- Undergraduate program: Bachelors of Technology in Computer Science and Engineering with Business Systems, Vellore Institute of Technology
- Internship company: University Health Network
- Current position: AI Engineer, Next Pathway
- Research interests: Computer Vision (2D and 3D) and Large Language Models (Generative AI), AI in Healthcare, Education, Data Migration, Sports and Anime
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I love taking complex technology and turning it into something intuitive, practical and genuinely enjoyable to use. I’m driven by building meaningful solutions and not recycled ideas. At UHN, I helped develop a web-based interactive 3D human anatomy platform for surgical training, contributed to gastric cancer detection research, and worked on identifying surgical tool-tissue interaction sites using CV and GenAI.
Now, at NextPathway, I help organizations modernize legacy systems and transition to Snowflake and GCP using LLM-powered workflows. I thrive at the intersection of deep technical work and clear communication; building systems that are powerful behind the scenes, yet simple and reliable for the people who use them every day.
Ujan Sen
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Computer Science, Specialization in AI & ML, Minor in Mathematics, Carleton University
- Internship company: AMD
- Current position: Software Engineer II, AMD
- Research interests: Machine Learning, Artificial Intelligence, Computer Vision, Vision Language Models, Generative AI for Visual Data
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Hey everyone, I’m Ujan. I’m originally from Kolkata, India and I’m currently working as an ML Engineer at AMD building models that actually survive production (which is harder than it sounds). I enjoy working at the intersection of ML and Computer Vision, with a focus on scalable, practical, and efficient systems.
Outside of work, I’m a proud nerd. I’m into video games, anime, soccer, history, and anything fantasy or sci-fi. I also love participating and hosting trivia. When I’m not working, I’m probably gaming, watching a match, or going down a random history rabbit hole.
Happy to chat about MScAC, careers in ML, or literally anything you wanna pick my brain about.
Samanvay Vajpayee
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Computer Engineering, University of Waterloo
- Internship company: University of Ottawa Heart Institute
- Current position: AI Scientist/Quant researcher, MUFG Securities
- Research interests: NLP, ML for Healthcare, Causal Inference, Trustworthy AI, AI safety and alignment
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Samanvay Vajpayee is an AI researcher and MScAC graduate from the University of Toronto, working at the intersection of machine learning, healthcare, and AI safety. He has conducted research with the University of Ottawa Heart Institute on cardiology-focused AI systems, including retrieval-augmented generation (RAG) pipelines and clinically grounded language models.
His work spans safety alignment, tamper-resistant fine-tuning, fairness under label noise in medical imaging, and scalable LLM evaluation frameworks. He has contributed to projects such as multi-hop biomedical QA generation, safety benchmarking for fine-tuned models, and efficient large-scale model training methods. Samanvay is also actively involved in academic leadership and cross-institutional collaborations, with a long-term focus on building robust, trustworthy AI systems for high-stakes domains like healthcare.
Steven Yuan
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Computer Science Specialist, Math Major, University of Toronto
- Internship company: XLSCOUT
- Current position: AI/ML Scientist, Vanguard
- Research interests: Natural Language Processing, Large Language Models, Agentic AI Systems
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I completed my undergrad at the University of Toronto, majoring in Computer Science and Math, and later graduated from the MScAC program (AI concentration). My work focuses on NLP, LLM post-training, and multi-agent systems, especially where research can translate into real product impact and business value. My experience spans: building a multi-agent system to detect potential product infringement from patent documents, improving low-resource machine translation using LLM pre-/post-training on small datasets, and performance engineering for a cloud-native distributed database.
Happy to chat about MScAC, AI research, internships, and career paths! Looking forward to meeting you!
Jinyang Zhao
- Cohort: 2024-25
- Concentration: Artificial Intelligence
- Undergraduate program: Computer Science, University of Toronto
- Internship company: CHAH – AI
- Current position: Software Developer, Google
- Research interests: Mainly SDE, a little bit ML & AI
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Hi everyone, I’m Jinyang Zhao. I’m currently a Software Developer at Google, working on building scalable and reliable systems. The program played a key role in shaping my transition from academia to industry. I’m happy to share my experience with coursework, internships, career preparation, and navigating the job search process. Please feel free to reach out. I’d love to connect and support incoming students!
Artificial Intelligence in Healthcare
Ashka Shah
- Cohort: 2024-25
- Concentration: Artificial Intelligence in Healthcare
- Undergraduate program: HBSc Computer Science and Biology, University of Toronto
- Internship company: Princess Margaret Cancer Centre
- Current position: Bioinformatics Data Scientist, Princess Margaret Cancer Centre
- Research interests: Circulating tumour DNA, Multi-omics data
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Ashka Shah is an MScAC alumni from the University of Toronto. She is currently a Bioinformatics Data Scientist at the Princess Margaret Cancer Centre, where she applies data science and machine learning methodologies to advance cancer diagnostics. Her work focuses on leveraging methylation profiling for the non‑invasive detection and monitoring of lymphoma, with the goal of improving patient outcomes.
Computer Science
Luc Baier-Reinio
- Cohort: 2024-25
- Concentration: Computer Science
- Undergraduate program: BSc Computer Science, McGill University
- Internship company: Vanguard
- Current position: AI/ML Scientist, Vanguard
- Research interests: AI Safety & Language Models
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Luc is an AI/ML Scientist at Vanguard and an MScAC alum (2024 cohort) from the Computer Science concentration. He also conducted his MScAC internship at Vanguard, where his work focused on LLM red teaming and post-training.
Prior to his master’s degree, Luc worked as a software developer at two separate Canadian technology firms. He holds a Bachelor of Science in Computer Science from McGill University and has experience tutoring and serving as a teaching assistant at both McGill University and the University of Toronto.
Outside of work, Luc enjoys playing squash.
Lewis Concio
- Cohort: 2024-25
- Concentration: Computer Science
- Undergraduate program: BS Computer Engineering, University of the Philippines
- Internship company: AMD
- Current position: Software Engineer 2, AMD
- Research interests: Large Language Models (LLMs), Parallel Programming, AI Model Deployment, Cloud Orchestration, Edge Computing, Medical AI
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I’m Lewis from 2024-2025 MScAC cohort, and a fun fact about me — I’m the first (and only) Filipino this program has ever admitted!
I did my internship with AMD, focusing on using LLMs for code parallelization, where I made strides using an evolutionary LLM approach. Currently, I stayed at AMD as a software engineer for AI model deployment and orchestration. Apart from academics, I also dabbled in medical research with SickKids during my masters, using both machine and deep learning techniques to determine patient outcomes.
All in all, the program was invaluable for both my academic and professional career, and made many meaningful connections along the way, and I hope you’ll be the next!
Anny Dai
- Cohort: 2024-25
- Concentration: Computer Science
- Undergraduate program: HBSc Computer Science and Mathematics, University of Toronto
- Internship company: Magna
- Current position: Bioinformatics Data Scientist, Princess Margaret Cancer Centre
- Research interests: Machine Learning, Computer Vision, Deep Learning for Industrial Inspection, Multimodal Learning, Applied AI Systems, Model Optimization, Trustworthy & Interpretable AI, Large Vision Models, and Agentic AI for Real-World Applications
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Anny Dai is a Machine Learning practitioner with a strong background in computer vision and applied AI systems. She holds a BSc in Computer Science (Specialist) with a major in Mathematics and a minor in Statistics from the University of Toronto. Her work focuses on building scalable deep learning pipelines for industrial defect detection, combining segmentation, classification, and model optimization techniques. She is particularly interested in deploying reliable, interpretable AI systems in real-world environments, including manufacturing and intelligent automation. Her broader research interests include multimodal learning, large vision models, and agentic AI systems that bridge research innovation with practical impact.
Samarendra Chandan Bindu Dash
- Cohort: 2022-23
- Concentration: Computer Science
- Undergraduate program: B.Tech in Computer Science, KIIT University
- Internship company: Huawei
- Current position:PhD in Computer Science at the University of Toronto
- Research interests: NLP, Computational Linguistics
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I’m currently a PhD student in Computer Science at the University of Toronto (UofT) under the supervision of Gerald Penn. I completed my MScAC (Masters of Science in Applied Computing) degree from UofT, which is a co-op based Masters program. I completed my B.Tech (Bacherlors in Technology) in Computer Science, from KIIT University. I am researching on Social Reading Technology. I aim to create LLM tools that can help writers to evaluate their stories and get active feedback. My research focuses on Literature Analysis, Natural Language Processing and theoretical research on Large Language Models.
Zhongkang Guo
- Cohort: 2021-22
- Concentration: Computer Science
- Undergraduate program: Bachelor of Engineering in Automation, Tsinsghua University
- Internship company: Talka AI
- Current position: Software Engineer, Robinhood
- Research interests: Backend Development, Software Development, LLM
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Zhongkang Guo is a software engineer at Robinhood, where he works on the brokerage platform, building backend systems and integrations for international products. Prior to Robinhood, he was a software engineer at Cresta, an ML startup developing AI agents for contact centers. He is from the 2021–2022 cohort of the MScAC program. Outside of work, he enjoys learning foreign languages and exploring interdisciplinary perspectives that connect technology and society.
Aditya Kharosekar
- Cohort: 2021-22
- Concentration: Computer Science
- Undergraduate program: Electrical and Computer Engineering, University of Texas at Austin
- Internship company: CrossingMinds
- Current position: Senior Data Scientist, Wealthsimple
- Research interests: I like reading about recommender systems, statistics, and machine learning. Currently interesting in learning more about MLOps (still a newbie), and getting better at deploying ML systems into production in industry.
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4 years experience as a data scientist – 1.5 at Wealthsimple, and 2.5 at Crossing Minds (a recommender systems startup).
Before the MScAC, about 3 years as a software engineer. Outside of work, I like board games, jigsaw puzzles and running half-marathons.
Tom LaMantia
- Cohort: 2015-16
- Concentration: Computer Science
- Undergraduate program: Computer Science, Wilfrid Laurier University
- Internship company: CaseWare International
- Current position: Digital Transformation Lead, Town of Bradford West Gwillimbury
- Research interests: Cloud computing, computational logic, recommendation systems, technical communication
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I’m Tom, a 2016 MScAC graduate currently in a technical leadership role at the Town of Bradford West Gwillimbury. My background includes four years building scalable media recommendation systems at CBC and an internship at CaseWare International, where I used NLP to analyze regulatory risk in financial statements.
Outside of work, I enjoy running, reading American history and brewing beer.
Yug Shah
- Cohort: 2023-24
- Concentration: Computer Science
- Undergraduate program: Bachelor of Science Honours in Computer Science and Minor in Pure Mathematics, University of Regina
- Internship company: DoraHacks
- Current position: Staff Scientist, Cryptography & Special Projects, Qorsa
- Research interests: Cryptography, Post Quantum Cryptography, Cryptographic Agility, Blockchain Security, and Protocol Design
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Yug Shah is a Staff Scientist – Cryptography & Special Projects at Qorsa, where he leads initiatives in post-quantum cryptography, cryptographic agility, and secure protocol design. He completed the MScAC program in Computer Science, focusing on applied research in post-quantum cryptography and secure systems engineering. His work spans integrating post-quantum algorithms into real-world infrastructure (TLS and distributed systems), strengthening blockchain security, and designing production-grade, quantum-secure protocols. Yug is passionate about translating cutting-edge cryptographic research into deployable engineering solutions that strengthen long-term security.
As an ambassador, he offers practical guidance on strategically navigating the MScAC program, securing research-focused internships, and building a strong foundation for research-driven roles.
Jiaqi Wang
- Cohort: 2024-25
- Concentration: Computer Science
- Undergraduate program: BEng. in Software Engineering, Beijing Univ of Posts and Telecommunications（北邮）
- Internship company: Scotiabank; as Data Scientist in GenAI
- Current position: Machine Learning Engineer (Agent & LLM) at BMO (Bank of Montreal)
- Research interests: Looking for roles in agent startups
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Congratulations!
I grew up in China’s public edu system and spent nearly 20 years in Beijing through undergrad, which shaped my cross-cultural perspective. I value honest communication and long-term, mutually supportive friendships. I care about momentum and long-term potential more than appearances or instant achievement.
My background is primarily in LLMs; I’m now exploring the agent paradigm, aiming to join an agent startup.
Outside work, I’m learning piano, French, and cooking. I enjoy the gym, anime, cosplay, in-person conversations and building more under-control routine.
Languages: English, Mandarin, Japanese, French.
Ins: jiaqi_jackywang; wechat: lovelive103538127.
Welcome!
Yuki Zhao
- Cohort: 2024-25
- Concentration: Computer Science
- Undergraduate program: Computer Science, McMaster University
- Internship company: Geotab
- Current position: Software Developer (AI Engineering), Geotab
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With a strong technical background in GenAI and Software Engineering, I currently build AI applications at Geotab. I specialize in driving innovation, taking projects from initiative POCs all the way to full-scale production deployment and long-term maintenance. My work focuses on bridging the gap between cutting-edge research and reliable industrial applications.
As an ambassador, I look forward to sharing my journey of navigating the MScAC program and thriving in a high-impact technical role.
Data Science
Nikhil Verma
- Cohort: 2021-22
- Concentration: Data Science
- Undergraduate program: Bachelor of Engineering, Thapar University, Patiala, Punjab, India
- Internship company:LG Electronics Toronto AI Lab
- Current position: AI Research Scientist, LG Electronics Toronto AI Lab
- Research interests: My focus lies at the intersection of post-training techniques, multi-modal training, multilingual adaptation, multi-agent systems and self-reflective agents. I am currently focusing on personalization, LLM memory and AI creativity, all using Reinforcement Learning techniques.
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Nikhil Verma is an AI Research Scientist at LG Toronto AI Lab, focused on building reliable and scalable language agents through domain-specific LLMs, post-training, and alignment research. His work spans reasoning, planning, and productionizing real-world AI systems.
Outside the lab, he unwinds by strumming his ukulele and chasing the next good coffee.
Yining (Harry) Zhu
- Cohort: 2021-22
- Concentration: Data Science
- Undergraduate program: Bachelor of Science, Physics, Renmin Univeristy of China
- Internship company: Soti
- Current position: Machine Learning Software Engineer, Lyft
- Research interests: Traffic prediction, MLops, Big Data, GNN
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I am an ML Engineer dedicated to building intelligent, scalable systems that solve real-world challenges. Currently at Lyft, I focus on spatio-temporal modeling and MLOps standardization. I combine a deep theoretical foundation—ranked top 1 in Physics during my undergrad —with extensive experience in Kubernetes, Spark, and LLM fine-tuning. I thrive on optimizing model performance to drive both user experience and business growth.
Data Science for Biology
Ashenafee Mandefro
- Cohort: 2024-25
- Concentration: Data Science for Biology
- Undergraduate program: Bioinformatics & Computational Biology Specialist; Computer Science Major; Neuroscience Major, University of Toronto
- Internship company: Insitro
- Current position: Newly graduated
- Research interests: Single-cell RNA sequencing (scRNA-seq), CRISPR perturbations (Perturb-seq), contrastive latent variable modelling, generative modelling, representation learning
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I’m Ashenafee, but most people know me as Ash! I’m a graduate researcher bridging deep learning and biology. My research interests centre on representation learning and generative modelling in single-cell analysis. During my MScAC internship at insitro, I focused on incorporating biologically-grounded inductive biases into generative models to improve genetic perturbation prediction.
As a byproduct of interning in the Bay Area, I picked up running and have (mostly) kept it since. Beyond that, I’m into reading and writing poetry as a slower, more reflective counterbalance to research. I’ve also got a pet cat named Anbo, who’s my whole heart 🙂
Quantum Computing
Michael Luciuk
- Cohort: 2021-22
- Concentration: Quantum Computing
- Undergraduate program: Engineering Physics & Computer Science, University of Saskatchewan
- Internship company: QEYnet
- Current position: AI Security Engineer, Amex | Founder, Cilindir
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Applied research specialist and deep tech founder working on AI, quantum, and XR. Feel free to reach out — I’d love to chat! 🤝
