Detailed CV

Abhishek Moturu

Computer Science PhD candidate at the University of Toronto working on noisy labels, sample difficulty, LLMs and vision-language models, agentic AI, socially grounded AI safety, clinical AI, education, and governance.

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Machine learning research on imperfect data, clinical evaluation, and responsible use.

I develop methods for sample weighting, label correction, fairness, and targeted synthetic data. I also work on LLMs, vision-language models, agentic AI, and socially grounded AI safety; collaborate with clinicians on pediatric imaging and automated pain assessment; and contribute to AI education and governance through T‑CAIREM.

ML methodsNoisy labels, sample difficulty, fairness, synthetic data
VisionMedical imaging, facial analysis, segmentation, classification, generative models
LLMs/VLMsMedical VLMs, multimodal reasoning, SFT/RL evaluation
AgentsAgentic AI prototypes, workflow design, socially grounded systems
EducationDSI, T‑CAIREM, resident training, neural networks, image understanding
GovernanceAI literacy, appraisal, curriculum, data governance, interdisciplinary AI work

Education

University of Toronto, St. George · PhD, Computer ScienceMay 2021–Present

Machine Learning and Computer Vision. Affiliated with the Vector Institute, The Hospital for Sick Children, Toronto Rehabilitation Institute, and UHN KITE.

Supervisors: Dr. Anna Goldenberg and Dr. Babak Taati. Committee chair: Dr. Rahul Krishnan.

Selected coursework: Software Engineering for ML, AI Alignment, Ethics of AI in Context, Probabilistic Learning.

University of Toronto, St. George · MSc, Computer ScienceSep 2019–Apr 2021

Machine Learning and Computer Vision. Supervisor: Dr. Babak Taati.

Selected coursework: AI & Ethics, Numerical Methods for Optimization, Machine Learning for Health, Algorithms for Privacy.

Trinity College, University of Toronto · Honours Bachelor of ScienceSep 2015–Apr 2019

Computer Science Specialist and Mathematics Major. Graduated with High Distinction. Dean’s List Scholar in 2016, 2017, 2018, and 2019.

Specialist focuses: Artificial Intelligence, Scientific Computing, and Theory of Computation.

University of Toronto Mississauga · Gifted Student ProgramMay 2013–Aug 2014

Took credited Computer Science and Mathematics courses part-time while attending high school.

Experience

Faculty of Information, University of Toronto · Research AssistantAug 2026–Present

Towards Socially Grounded AI Safety: Research Fellowship with Dr. Matt Ratto and Dr. Daniel Silver.

  • Build LLMs that are more socially grounded and aligned across pluralistic views.
  • Conduct literature reviews, assist with writing, build code, prototypes, and data, and perform analysis.
CoordCare · Chief Technology OfficerSep 2025–Present
  • Build prototypes for agentic AI systems in healthcare and work with founders to secure investment.
Data Sciences Institute, University of Toronto · Lecturer / Technical FacilitatorJan 2025
  • Supported the DSI Certificate Program in Git, Unix, and Shell.
  • Held office hours, organized lectures, marked assignments, and managed TA/learning support.
Department of Computer Science, University of Toronto + Vector Institute · Research AssistantMay 2021–Present
  • Develop lightweight methods to learn sample difficulty and improve noisy learning and fairness.
  • Work on label correction, time-series missingness, and vision-language reasoning.
UHN KITE Research Institute · Research AssistantSep 2019–Present
  • Developed automated facial pain detection using pairwise and contrastive learning.
  • Worked with a University of Regina team to install, debug, and maintain pain monitoring systems in long-term care homes in Regina and Saskatoon.
The Hospital for Sick Children · Research AssistantApr 2019–Present
  • Used generative, classification, and segmentation models to support pediatric cancer surveillance and renal ultrasound prediction tasks.
  • Worked with radiologists to evaluate AI tools for pediatric whole-body MRI and related clinical imaging tasks.
St. Michael's Hospital + Scientific Computing Group · Research AssistantApr 2018–Apr 2019
  • Generated realistic synthetic nodules and frontal chest radiographs from chest CT scans.
  • Trained a deep convolutional neural network to detect early-stage lung nodules from synthetic image patches.
Massey College, University of Toronto · Junior FellowSep 2023–Present

Graduate college fellowship; co-chaired committees, participated in Massey Grand Rounds, and organized dialogues and debates.

Teaching, AI education, and literacy

T‑CAIREM · Education Trainee Co‑LeadMay 2023–Present
  • Guide education and training initiatives in AI for high school, undergraduate, graduate, postgraduate, and medical audiences.
  • Organize, moderate, and adjudicate lectures and conferences; contribute to trainee hiring, trainee funding, and outreach initiatives.
  • Run AI training and appraisal sessions for medical residents.
  • Contribute to AI governance and AI literacy work, the International AI in Medicine Education Working Group, Data Governance Committee, ACAIM/PCAIM, and the TAHSN Community of Practice for AI in Healthcare.
  • Co-lead the Living Glossary in AI and Medicine subgroup and the Medical Resident Training subgroup.
University teaching
  • DSI Certificate Program: Git, Unix, and Shell — Lecturer/Technical Facilitator, Jan 2025.
  • CSC110 Foundations of Computer Science I — Teaching Assistant, Fall 2023.
  • CSC413/2516 Neural Networks and Deep Learning — Teaching Assistant, Winter 2023.
  • CSC420 Introduction to Image Understanding — Teaching Assistant, Fall 2021.
  • CSC165 Mathematical Expression and Reasoning for Computer Science — Teaching Assistant, Summer 2021.
  • CSC207 Software Design — Teaching Assistant, Winter 2019.

Manuscripts and work in submission

  1. Moturu, A.*, Postill, G.*, Rosella, L., Mamdani, M. (2026). A Pan-Canadian Plan for AI Education. Submitting to Nature Communications, AI in Education.
  2. Moturu, A.*, Postill, G.*, Rosella, L., Mamdani, M. (2026). Towards a Healthcare AI Governance Framework. Submitting to npj Digital Medicine, Exploring the impact of governance models in AI and digital health on healthcare.
  3. Postill, G.*, Moturu, A.*, Rosella, L., Mamdani, M. (2026). Towards a Healthcare AI Literacy Framework. Submitting to npj Digital Medicine, Transforming Medical Education through Artificial Intelligence.
  4. Moturu, A., Muzammil, M., Goldenberg, A.*, Taati, B.* (2026). LiLAW: Lightweight Learnable Adaptive Weighting to Learn Sample Difficulty and Improve Noisy Training. In submission.
  5. Moturu, A., Goldenberg, A.*, Taati, B.* (2026). LiBaGS: Lightweight Boundary Gap Synthesis for Targeted Synthetic Data Selection. In submission.
  6. Moturu, A., Taati, B.*, Goldenberg, A.* (2026). LiNC: Lightweight Noise Correction via Per-Sample Trust and Gaussian Mixture Modeling. In submission.
  7. Jeddi, A., Shaban, K., Baghbanzadeh, N., Sharan, N., Moturu, A., Taati, B. (2026). When Does RL Help Medical VLMs? Disentangling Vision, SFT, and RL Gains. In submission.
  8. Bestavros, S., Chen, E., Moturu, A., Rahman, S., Tyli, R., Wang, S. (2026). A Narrative Review of Artificial Intelligence-Based Imaging in Dermatology: From Potential to Practice. In submission.

Publications and workshop papers

  1. Moturu, A., Komolafe, R., Joshi, S., Doria, A., Goldenberg, A. (2025). Human–AI Interaction With AI-Assisted Tumor Overlays in Pediatric Whole-Body Magnetic Resonance Imaging: Exploratory Reader Study. JMIR Human Factors.
  2. Postill, G., Midroni, J., Moturu, A., Rosella, L., Haque, N. (2026). Moving beyond one-size-fits-all education approaches for artificial intelligence in healthcare. PLOS Digital Health, 5(5), e0001408.
  3. Midroni, J., Postill, G., Moturu, A., Haque, N., Rosella, L. (2026). Building an Interdisciplinary Centre for AI Education: Strategy and Practice. University of Toronto Medical Journal, 103(1).
  4. Ratto, M., Moturu, A., Silver, D. (2026). Socially Grounded Agentic AI: Coordinating Plural Perspectives through Social Theory. Pluralistic Alignment Workshop at ICML.
  5. Lin, L., Mehraban, S., Moturu, A., Taati, B. (2026). Pain in 3D: Generating Controllable Synthetic Faces for Automated Pain Assessment. International Conference on Pattern Recognition.
  6. Postill, G., Lomis, K., Khoury, C., Rosella, L., Krishnan, R., Moturu, A., Midroni, J., Harish, V. (2025). Artificial Intelligence in Medicine in Europe Workshop: Fostering Collaboration between Developers and Physicians to Optimize AI in Healthcare. Pavia, Italy.
  7. Taati, B., Muzammil, M., Zarghami, Y., Moturu, A., Kazerouni, A., Reimer, H., Mihailidis, A., Hadjistavropoulos, T. (2025). SynPAIN: A Synthetic Dataset of Pain and Non-Pain Facial Expressions. arXiv.
  8. Stopyn, R. J. N., Moturu, A., Taati, B., Hadjistavropoulos, T. (2025). Real-Time Evaluation of an Automated Computer Vision System to Monitor Pain Behaviour in Older Adults. Journal of Rehabilitation and Assistive Technologies Engineering.
  9. Tran, V., Moturu, A., Taati, B., Hadjistavropoulos, T. (2024). Evaluating an automated computer vision system designed to detect pain behaviours in residents living with dementia in long-term care settings. Oral presentation, AGE-WELL.
  10. Postill, G., Moturu, A. (2024). Integrating AI into Medical Education: A Curriculum for Appraising AI Studies in Clinical Practice. Workshop, International Congress on Academic Medicine.
  11. Moturu, A., Joshi, S., Doria, A., Goldenberg, A. (2022). Volume-based Performance not Guaranteed by Promising Patch-based Results in Medical Imaging. Spotlight, NeurIPS ICBINB Workshop, PMLR 187:85–93.
  12. Rezaei, S., Moturu, A., Zhao, S., Prkachin, K. M., Hadjistavropoulos, T., Taati, B. (2020). Unobtrusive Pain Monitoring in Older Adults with Dementia using Pairwise and Contrastive Training. IEEE Journal of Biomedical and Health Informatics.
  13. Rezaei, S., Moturu, A., Zhao, S., Prkachin, K. M., Hadjistavropoulos, T., Taati, B. (2020). Ambient Pain Monitoring in Older Adults with Dementia to Improve Pain Management in Long-Term Care Facilities. ACM ICMI Companion.
  14. Chang, A.*, Suriyakumar, V. M.*, Moturu, A.*, Tewattanarat, N., Doria, A., Goldenberg, A. (2020). Using Generative Models for Pediatric wbMRI. Medical Imaging with Deep Learning.
  15. Moturu, A., Chang, A. (2018). Creation of Synthetic X-Rays to Train a Neural Network to Detect Lung Cancer. Review of Undergraduate Computer Science, University of Toronto.

Reports and preprints

  1. Rosella, L. et al. (2025). Global Framework for an AI Curriculum in Medicine. International AI in Medicine Education Working Group.
  2. Rosella, L. et al. (2025). Living Glossary for AI and Medicine. International AI in Medicine Education Working Group.
  3. Dubber, M. D., Pasquale, F., Das, S. (Eds.). Moturu, A. et al. (2022). The Oxford Handbook of Ethics of AI: An Annotated Bibliography. Oxford Handbooks.
  4. Chang, A., Suriyakumar, V. M., Moturu, A., Tu, J., Tewattanarat, N., Joshi, S., Doria, A., Goldenberg, A. (2021). 3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI. arXiv.
  5. Moturu, A., Sabo, A., Jafari, D., Korhani, N. (2020). Deep Learning for View Labelling of Pediatric Renal Ultrasounds for Predicting Surgical Intervention, Vesicoureteral Reflux, and Kidney Function. Machine Learning for Healthcare course project.
  6. Chang, A., Moturu, A. (2019). Detecting Early Stage Lung Cancer using a Neural Network Trained with Patches from Synthetically Generated X-Rays. University of Toronto Numerical Analysis Technical Report.
  7. Moturu, A., Chang, A. (2018). Creation of Synthetic X-Rays to Train a Neural Network to Detect Lung Cancer. University of Toronto Numerical Analysis Technical Report.

Organizing and reviewing

2026

Canadian International Council’s Couchiching Conference (organizer); Neural Information Processing Systems; Machine Learning for Healthcare.

2025

IEEE / CVF Computer Vision and Pattern Recognition Conference; T‑CAIREM Conference: The Evolution of Generative A.I. (organizer); Machine Learning for Healthcare; International Conference on Machine Learning.

2024

International Conference on Learning Representations: Time Series for Healthcare Workshop; T‑CAIREM Symposium: Multi‑Modal Data and the Future of Health AI (organizer).

2023

T‑CAIREM AI in Medicine Conference organizer; MICCAI; MICCAI AmI4HC Workshop.

2022

NeurIPS Learning from Time Series for Health Workshop; Machine Learning for Healthcare.

2021

Machine Learning for Healthcare; IEEE Transactions on Affective Computing.

2020

Machine Learning for Healthcare.

Selected talks and events

2026
  • International Conference on Machine Learning, Seoul, South Korea — Presenter.
  • Emerging Leaders in Healthcare Conference at Cal Poly San Luis Obispo — Presenter.
  • MaLMIC Open Forum on Validating AI in Healthcare: Generalizability and Explainability — Presenter.
  • Artificial Intelligence High Table with Dr. Geoffrey Hinton at Massey College — Invited Guest.
  • (Eh)I: Artificial Intelligence in the Canadian Context with Dr. Geoffrey Hinton at Massey College.
  • CIC Bill Graham Lecture with Dr. Geoffrey Hinton at The Arcadian.
2025
  • Academic Half Day: Psychiatry and AI at T‑CAIREM — Presenter.
  • Hinton Lectures at Metro Toronto Convention Centre.
  • T‑CAIREM AI in Medicine Conference at Marriott Toronto — Adjudicator.
  • Academic Half Day: Neurology and AI at T‑CAIREM — Presenter.
  • Massey Grand Rounds with Dr. James Orbinski at Massey College.
2024
  • AGE‑WELL Conference, Edmonton — Presenter.
  • Doctoral Symposium, Conference on Health, Inference, and Learning at Cornell Tech, NYC — Presenter.
  • T‑CAIREM Symposium: Multi‑Modal Data and the Future of Health AI at Hart House.
  • Artificial Intelligence Academic Dinner at Trinity College — Organizer.
2023
  • T‑CAIREM AI in Medicine Conference — Organizer and Presenter.
  • Academic Half Day: Cardiac Surgery and AI at T‑CAIREM — Presenter.
  • Massey Dialogues on AI and Healthcare — Organizer.
  • Massey Grand Rounds with Dr. Janet Rossant at Massey College.
  • AI4Health Summer School, Paris — Presenter.
  • Machine Learning High Table at Trinity College — Organizer.
  • Gairdner Science Week at MaRS Discovery District.
Earlier selected items
  • ICBINB Workshop Presentation at NeurIPS, New Orleans — Spotlight Presenter.
  • AI in Healthcare with Drs. Babak Taati, Frank Rudzicz, and Farzad Khalvati — Organizer.
  • Dr. Jeffrey Cohn, Multimodal Measurement of Depression and Treatment-Resistant OCD at UHN KITE.
  • Computer Vision Symposium at Vector Institute — Presenter.
  • Computer Vision Journal Club: Automatic Pain Recognition at UHN KITE — Presenter.
  • Dr. Geoffrey Hinton’s Turing Lecture and Symposium — Presenter.
  • BSI Remote International Conference — Best Presentation Award.
  • Trinity College Undergraduate Research Conference — Presenter.
  • SickKids Speaker Series: Artificial Intelligence at the Globe and Mail Centre.

Awards

2026Bell Graduate Scholarship$20,000
2026Massey College OSOTF – HUDD Bursary$1,500
2026Monica Ryckman Bursary$4,000
2026Vector Institute Research Scholarship$6,000
2026Massey College Junior Fellowship
2025Frederick Hudd Scholarship, Massey College$2,000
2025T‑CAIREM Student Education Co‑Lead$4,000
2025Ontario Graduate Scholarship$15,000
2025Vector Institute Research Scholarship$6,000
2025Massey College Junior Fellowship
2024Frederick Hudd Scholarship, Massey College$3,000
2024Ontario Graduate Scholarship$15,000
2024Vector Institute Research Scholarship$6,000
2024T‑CAIREM Student Education Co‑Lead$4,000
2024Massey College Junior Fellowship
2023Ontario Graduate Scholarship$15,000
2023Vector Institute Research Scholarship$6,000
2023T‑CAIREM Student Education Co‑Lead$4,000
2023Massey College Junior Fellowship
2022Chancellor William C. Graham Award, Trinity College
2022Vector Institute Research Scholarship$6,000
2021Queen Elizabeth II Graduate Scholarship in Science & Technology$15,000
2020CIHR Frederick Banting and Charles Best Canada Graduate Scholarship-Master’s$17,500
2019NSERC Undergraduate Student Research Award, Supervisor: Dr. Anna Goldenberg$6,000
2019Platterz Prize in Computer Science$2,500
2019BSI Remote International Conference Best Presentation Award$100
2018Trinity College Drew Thompson Scholarship$300
2018NSERC Undergraduate Student Research Award, Supervisor: Dr. Ken Jackson$6,000
2016Trinity College Chancellor’s Scholarship — Frederick K. Ashbaugh$200
2015President’s Scholars of Excellence Program$10,000
2015C. David Naylor University Scholarship$20,000

Media, features, and selected appearances

Leadership, community, and affiliations

Academic and student leadership

  • Massey College: Junior Fellow; co-chaired the Lionel Massey Fund, House Committee, Computing Committee, and Junior Fellow Lecture Series Committee.
  • Trinity College: Senior Academic Don, Academic Don for Computer Science, Mathematics, and Physics, alumni reunion planning, scholarship fundraising, and event leadership.
  • UofT Computer Science: Ukraine Undergraduate Summer Exchange Program, Toronto Graduate Application Assistance Program, ProjectX domain expert, Machine Intelligence Student Team project director, DCS Ambassador, Undergraduate Theory Group VP Communications.
  • UofT Mathematics: Math Union VP Communications and Secretary, Department of Mathematics Undergraduate Committee member, Department of Mathematics Peer Mentor.

Affiliations

University of TorontoFaculty of InformationTrinity CollegeSickKidsUHN KITEVector InstituteMassey CollegeT‑CAIREMFaculty ClubData Sciences InstituteCanadian International CouncilCoordCareUniversity of Toronto MississaugaGoogle

Earlier technology programs

  • Google Trailblazer, 1st place in Hour of Code outreach contest.
  • Google CAPE / CAPE Virtual and Google-sponsored C++ iD Tech Camps at Stanford.

Skills

Areas

Machine Learning, Computer Vision, Deep Learning, Natural Language Processing, LLMs, VLMs, Reasoning, Agentic AI, AI Governance, AI Education, Health AI, Medical Imaging, Numerical Methods, Data Structures, Algorithm Design, Complexity, Probability, Calculus, Algebra, and Logic.

Programming languages

PythonJuliaMATLABJavaCC++SwiftLaTeX

Tools and libraries

PyTorchTensorFlowOpenCVNumPySciPyscikit-learnNLTKMatplotlibGitAndroidLinux

Languages

English and Telugu: native proficiency. French, Italian, and Hindi: elementary proficiency.