Dr. Mamatha Bhat MD, MSc, PhD, FRCPC
(she/her)
Hepatologist & Co-Lead of Transplant AI Initiative (TAI)
Ajmera Transplant Program Scientist, Toronto General Hospital Research Institute, University Health Network
- Associate Professor, Division of Gastroenterology & Hepatology
- Director, Clinician-Scientist Training Program (CSTP), Department of Medicine, University of Toronto
- Partnerships & Engagement Lead, Temerty Centre for AI in Research & Education in Medicine (T-CAIREM); Faculty Affiliate, Vector
Dr. Mamatha Bhat is a Hepatologist and Clinician-Scientist at the Ajmera Transplant Centre, University Health Network (UHN) and an Assistant Professor of Medicine at the University of Toronto. She is also a Scientist at the Toronto General Hospital Research Institute and holds a graduate appointment with the Institute of Medical Sciences at the University of Toronto.
Dr. Bhat completed her medical degree and residency training at McGill University, including the Clinician Investigator Program. She subsequently pursued a Transplant Hepatology fellowship at the Mayo Clinic in Rochester, Minnesota, followed by a Canadian Institutes of Health Research (CIHR) Fellowship for Health Professionals, during which she completed a PhD in Medical Biophysics at the University of Toronto.
Dr. Bhat leads an interdisciplinary research program focused on improving long-term outcomes after liver transplantation through precision medicine. Her work integrates artificial intelligence, bioinformatics, and clinical research to better understand liver disease and personalize the care of transplant recipients. By combining advanced computational methods with biological insights, her team aims to develop predictive models and biomarkers that can guide clinical decision-making and improve transplant outcomes.
Her research program has received support from numerous national funding agencies and organizations, including the Canadian Institutes of Health Research (CIHR), the Terry Fox Research Institute, the Stem Cell Network, the Canadian Donation and Transplant Research Program (CDTRP), the Natural Sciences and Engineering Research Council of Canada (NSERC), and the Canadian Liver Foundation (CLF).
Dr. Bhat has received several prestigious recognitions for her work, including the CIHR-INMD-CASL Early Career Researcher Prize (2022), the Polanyi Prize in Medicine (2020), and the American Society of Transplantation Basic Science Career Development Award (2021).
Current Lab Members
Elisa Pasini
Research Associate- Lab Manager -Transplant AI Project Manager
Elisa joined the lab in 2018. Elisa completed their Residency in Laboratory Medicine and Pathobiology in Udine, Italy, and holds an MSc in Biological Sciences in Physiopathology from Bologna, Italy. Currently, she is involved in most of the projects in their lab and assist as lab Manager. Elisa’s research focuses on the integration of multi-omics data in liver cancer and post-transplant diseases, and the molecular validation of bioinformatics predictions for liver diseases and provide support for the new Transplant AI initiative in their lab. Elisa envisions leveraging her expertise to support the team driving innovations in personalized medicine and enhance the precision of diagnostic and therapeutic strategies in transplant and liver disease care.
Sameera Rizvi
Clinical Research Coordinator
Sameera is an international medical graduate, who received her degree from Dow Medical University Karachi, Pakistan. She earned her post-graduate diploma in Clinical Research Associate at Oxford College, ON, Canada.
Sameera has been devoted to the world of research for the past 8 years, working on various projects in different disciplines, such as, infectious diseases and mental health. She joined the TGH’s Liver transplant research team in August 2022, and here she was able to combine her medical experience and passion for working in research. She is involved in many research projects but her main focus is:
- The GLP-1 agonist Semaglutide for the treatment of Metabolic Disease in Liver Transplant Recipients: A Phase IV, randomized trial
In her current role, she handles all the REB submissions for her team. Sameera aims to integrate her prior research experience to create a long-lasting impact within the field of post-transplant liver disease.
Yingji Sun
Machine Learning Analyst
Yingji Sun joined our lab as a Machine Learning Analyst in December 2021. She holds a Master of Science in Biostatistics from the Dalla Lana School of Public Health at the University of Toronto and an Honours Bachelor of Science in Physiology and Statistics from the same institution.
Yingji is deeply passionate about leveraging machine learning to enhance clinical practices, particularly focusing on improving patient outcomes in the context of multiple organ transplants by combining her expertise in biostatistics with her proficiency in machine learning. Yingji is dedicated to employing machine learning techniques to enhance the predictions of the survival trajectories of patients on the transplant waitlist, identify potential complications post-transplant, and optimize treatment strategies
Dariia Khoroshchuk
Machine Learning Analyst
Dariia completed her Bachelor’s degree in Applied Mathematics, followed by a Master’s degree in Computer Science specializing in Artificial Intelligence Systems at Lviv Polytechnic National University. For her thesis, she collaborated with Prof. Michael Brudno’s lab to develop a solution for pneumothorax detection on X-ray scans before joining Dr. Mamatha Bhat’s team.
Currently, Dariia is actively involved in developing a data-driven waitlist prioritization model aimed at predicting personalized risk of mortality or dropout more accurately to improve outcomes for patients awaiting transplant.
Being part of Dr. Mamatha Bhat’s team enables Dariia to leverage her passion and create a meaningful impact within the healthcare system.
Ghazal Azarfar
Research Associate
Dr. Ghazal Azarfar earned her PhD in Engineering, specialized in computational imaging from the University of Wisconsin. She leads the technical development of innovative multimodal AI approaches aimed at transforming healthcare.
She is a member of the Transplant AI Initiative, where she works at the intersection of clinical medicine, computer science, and biostatistics to advance transplant care, with a particular focus on pre- and post-transplant complications. Her current research focuses on the responsible deployment of a multi-agent AI tool that simulates transplant committee deliberations, aiming to generate objective consensus for equitable waitlisting decisions.
LinkedIn
https://www.linkedin.com/in/ghazal-azarfar-6691b7121/
Google Scholar
https://scholar.google.com/citations?user=p8tRKD8AAAAJ&hl=en
Post-Doctoral Fellows
Soumita Ghosh
Post-doctoral Researcher
Soumita earned her doctoral degree in biostatistics from the Saw Swee Hock School of Public Health, National University of Singapore, where she developed bioinformatics tools for large-scale visualization of multi-omics data and mining high-throughput datasets. As a Research Fellow in the Department of Medicine, Yong Loo Lin School of Medicine, Singapore, she developed tools for predicting cancer-related outcomes, integrating genotype and phenotype information. Subsequently, at the Cancer Science Institute of Singapore, she worked on developing machine learning-based drug recommendation algorithms for refractory cancer patients at the National University Hospital, Singapore. Currently, as a Schmidt AI in Science postdoctoral fellow in Dr. Bhat’s lab she is applying machine learning based methods integrating omics and clinical data for improving outcomes in liver diseases.
Linkedin:
https://www.linkedin.com/in/soumitag/
Google Scholar:
https://scholar.google.ca/citations?hl=en&user=O7HZhuwAAAAJ
David Pellow
Schmidt AI in Science Postdoctoral Fellow c- supervised with Dr. Michael Brudno
David is a postdoc in the Brudno Lab collaborating on predictive modelling in post-liver-transplant patients. David holds a PhD in computer science from Tel Aviv University and an MS from Carnegie Mellon University. His research projects involve using machine learning and AI to predict long term risk for cardiovascular events in liver transplant patients and optimize short term immunosuppression dosing. David is excited to apply machine learning in healthcare to improve patient outcomes.
Varun Kanal
Post-doctoral Researcher
Dr. Varun Kanal earned a Ph.D. in Computer Science and a MS in Biomedical Engineering from The University of Texas at Arlington. His work has revolved around leveraging computational and electronic principles to solve medicine-related problems. Varun has worked in the area of Sleep Apnea, Fatigue, Rehabilitation, Cardiovascular Diseases, and Hemorrhage. His projects involve creating computational and mathematical models using physiological and clinical data to detect and predict acute clinical conditions. His work also involves creating hardware and software systems for detection and intervention applications.
Google Scholar Link:
https://scholar.google.com/citations?user=W9iizDQAAAAJ&hl=en
Naga Karthik Enamundram
Post-doctoral Researcher
Naga Karthik is a Postdoctoral Researcher at the University Health Network and is also affiliated with the Vector Institute. He focuses on developing multimodal deep learning methods for equitable prioritization of patients awaiting liver transplantation. He received his PhD from Polytechnique Montréal and Mila – Québec AI Institute, where he worked on developing image analysis tools for improving the estimation of imaging biomarkers in spinal cord imaging data. Prior to this, he completed his Masters at Ecole de Techonologie Superieure Montreal and undergraduate studies from Shiv Nadar University, India. Outside of work, he generally spends his time staying active through running or hiking and exploring museums.
LinkedIn:
https://www.linkedin.com/in/enamundram-naga-karthik-7b1559174/
Google Scholar:
https://scholar.google.ca/citations?user=ZryIoMMAAAAJ&hl=en
Personal Website:
https://naga-karthik.github.io
Layal Jbara, MSc, PhD (she/her)
Post-doctoral Researcher
Layal Jbara earned her PhD from the University of British Columbia. Her doctoral research combined high-performance computing with deep learning architectures to learn rich representations of highly nonlinear, high-dimensional, large-scale engineering datasets. Layal joined Dr. Mamatha Bhat’s lab as a Postdoctoral Research Fellow. Her current research centers on domain-specialized foundation language models for hepatology and liver transplantation, alongside computer-vision and transformer-based approaches for digital pathology to enable personalized post-transplant care.
LinkedIn: https://www.linkedin.com/in/layal-jbara-phd-612394a8/
Google Scholar: https://scholar.google.com/citations?user=-9SG7fEAAAAJ&hl=en
Graduate Students
Ankit Ray
Master’s Student
Ankit is a current Master’s student at the University of Toronto who has been a part of the team since 2023. His work focuses on advancing projects that develop predictive machine learning models for liver disease progression. For his Master’s project, he aims to integrate epigenetic data to build a non-invasive diagnostic model for MASH. Ankit is passionate about the intersection of AI and healthcare and aspires to pursue a career in medicine.
Google Scholar
https://scholar.google.ca/citations?hl=en&user=18hCK6MAAAAJ
Ankita Ghatak
Ankita is a first year PhD student at the University of Toronto. Her work focusses on developing and validating multimodal AI models which predict the risk of liver graft fibrosis. Ankita is driven by her desire to improve clinical care and patient outcomes. In her free time, she enjoys reading and exploring the city
Michael Cooper
Michael is a Ph.D. student in Computer Science at the University of Toronto, advised by Rahul G. Krishnan, and Michael Brudno. His research focuses on designing clinical machine learning systems for implementation in national-scale, high-stakes decision-making settings like liver transplant prioritization. In this same vein, he also designs and studies algorithms to make modern machine learning methods more reliable and interpretable.
Rabab Azeem, BASc (she/her)
Rabab received her BASc in Computer Engineering from Queen’s University, where she led QMIND, an undergraduate club of AI design teams, and worked on AI consulting projects. During her undergraduate studies, she interned at Amazon as a Software Design Engineer and at Ewha Womans University in Seoul, South Korea, where she worked on neural architecture search to optimize efficiency on TPUs. For her fourth-year research project, she trained an efficient diffusion model to remove noise from X-ray images. She is currently pursuing her MASc in Industrial Engineering at the University of Toronto, combining her passions for healthcare and AI to use deep learning to predict liver transplant recipient survival and optimize donor-recipient matching. In 2025, she was awarded the Order of the White Rose scholarship.
Linkedin: https://www.linkedin.com/in/rabab-azeem/
International MD Graduate
Saba Maleki, MD
Post-doctoral Researcher
Saba Maleki is a clinical postdoctoral researcher at the Ajmera Transplant Centre (since June 2025). Her research focuses on chronic kidney disease progression and renal outcomes after conversion from immediate- to extended-release tacrolimus, using machine learning to support personalized risk prediction. She also studies multisystem effects of GLP-1 receptor agonists and collaborates with the Global Burden of Disease initiative at the University of Washington to assess global liver transplant capacity and need.
She earned her MD in 2023 from Guilan and Tehran Universities of Medical Sciences and completed her clinical training (Clerkship and Internship) at Tehran University of Medical Sciences. She subsequently practiced as a general physician and served as a research associate at Tehran Heart Center in Iran. She has a strong interest in artificial intelligence in healthcare and is proficient in R, Python, and Stata. Outside of her professional work, she enjoys practicing Ashtanga yoga, which helps her cultivate discipline, balance, and resilience.
Google Scholar
https://scholar.google.com/citations?user=_DXyotcAAAAJ&hl=en
Research Gate
https://www.researchgate.net/profile/Saba-Maleki?ev=hdr_xprf
LinkedIn
https://www.linkedin.com/in/saba-maleki-7343151b8/
Twitter
https://x.com/SabaMalekiMD
Transplant Hepatology Fellows
Eunice Tan
Niamh Mehigan Farrelly
Marius Vogelin
Khalid Alghamdi
Ahmed Altukhair
Dhari Alobaid
Melinda Nguyen
Clinical Fellows
Katina Zheng
- M.D., University of Ottawa, 2021
- She joined Bhat lab as a post-doctoral fellow in the summer of 2023.
- PSI Foundation Resident Research Grant 2023
CURRENT RESEARCH
- Using Machine Learning to Predict Long Term Graft Survival
- Effect of COVID Infection on development of cardiometabolic complications in solid organ transplant recipients
Dr. Xun Zhao
Xun Zhao received his MD from McGill University and has completely residency in internal medicine and gastroenterology at McGill University Health Center followed by a two-year fellowship at the University Health Network in liver transplantation and hepatocellular carcinoma. He is currently pursuing a PhD in clinical epidemiology at the University of Toronto under the co-supervision of Dr. Mamatha Bhat and Joseph Kim. He is also an attending hepatologist at the McGill University Health Center.
Joseph Chon
International Clinical Fellow
Dr. Bima J. Hasjim
Dr. Bima J. Hasjim is a General Surgery Resident at the University of California, Irvine and has an interest in abdominal organ transplantation. Prior to joining Dr. Bhat’s lab, he completed a Master’s of Science in Clinical Investigation and completed an NIH T32 Transplant Surgery Scientist Fellowship from Northwestern University. He also received his undergraduate and medical degrees at University of California, Irvine. His research interests include utilizing machine learning to identify risk factors for poor outcomes beyond the MELD score and identifying disparities in transplant outcomes. He is excited to utilize both machine learning and traditional biostatistical methods to optimize outcomes for all transplant patients.
Medical Students
Nilah Ahimsadasan
Research Student
Nilah is a second-year medical student at Queen’s University. She joined the Bhat Lab in 2024, with research interests in health innovation and AI/ML applications in healthcare. She plans to pursue a career in Internal Medicine. She is currently working on the CDTx project.
Devina Ramesh
Research Student
Devina is a second-year medical student at Queen’s University. She joined the Bhat Liver Lab in 2024 to pursue clinical-based research. In her free time, she enjoys reading and playing piano. She plans on pursuing academia alongside medicine in her future career. She is currently working on the sepsis project.
Sherry (Xinle) Wang
Research Student
Sherry is a first-year medical student at the University of Toronto. She received her Master of Science from the University of Toronto, with a research focus on liver transplantation immunology. She joined the Bhat Lab in 2024 and is interested in leveraging AI/ML applications to improve patient care.
Praveen Manickavel
Research Student
Praveen is a first-year medical student at Western University. He joined the Bhat Liver Lab in 2024 to pursue clinical-based research. In his free time, He enjoys reading and playing badminton. He plans on pursuing academia and implementing innovations in his future medical practice.
Xiaoting You
Nimit Vediya
Aditi Venkatraman
Anushka Patel
Yi-Hsuan Yeh
Current Undergraduate Students
Sage (Soyeon) Kim
MOTSRTP Research Student
Sage is a fourth-year undergraduate student at the University of Toronto, pursuing an Honours Bachelor of Science in Physiology and Public Health. She joined the Bhat Lab in 2024, where she has contributed to projects on sepsis, ACLF, as well as systematic reviews on drug efficacy and safety, wearables, and multi-modal AI. She is inspired by the lab’s innovative use of AI and has begun developing machine learning models as part of her research. Motivated by a passion for medicine, Sage is committed to advancing patient care while also advocating for upstream policy change.
Jennifer Lee
MOTSRTP Research Student
Jennifer is a fourth-year undergraduate student at McMaster University, currently pursuing an Honours Bachelor of Health Sciences. She joined the Bhat Lab in Fall 2023 and has been working on various projects in machine learning, liver fibrosis, and systematic reviews. Jennifer is driven by her passion for patient care and technology and hopes to pursue a career in clinical medicine.
Nima Vasigh
Undergraduate Research Student
Nima is a second-year undergraduate student at Queen’s University, pursuing an Honours Bachelor of Health Sciences. Since joining the Bhat Lab in June 2025, he has worked on advancing the lab’s liver transplant-cardiovascular disease (LT-CVD) machine learning model. He has contributed to the model’s integration into the EPIC clinical system, collecting data through patient interactions, and retrospective performance analysis. Aspiring to a career in medicine, Nima is driven to improve patient lives through the integration of clinical support systems and technology.
Muhammad Enrizky Brillian
Undergraduate Research Student
Muhammad Enrizky Brillian (Billy) is in his final year at the University of Toronto, specializing in Data Science and Machine Learning, with a major in Computer Science and a minor in Economics. He joined the lab in 2024 and has contributed to various projects in deep learning and healthcare. Currently, Billy is focused on applying advanced machine learning techniques to improve data processing and analysis in healthcare. With a strong interest in innovation and the applications of AI, he aims to make a transformative impact on data science and medical research.
Rishi Ruthiran
2025 Charles Hollenberg Summer Award Student
Rishi is a third year Health Sciences student at the University of Waterloo. Joining the Bhat lab in 2025, he is investigating the relationship between epigenetic aging and fibrosis progression in Metabolic dysfunction-associated Steatohepatitis (MASH) using Multimodal AI. With a strong interest in metabolic pathology and OMICS data, Rishi aims to make an impact on patient care via exceptional medical research in the Bhat lab.
Mert Nazlim
MOTSRTP Research Student
Mert is a third-year undergraduate student at the University of Toronto, pursuing an Honours Bachelor of Science in Pharmacology and Immunology. He joined the Bhat lab in 2025 with an interest in clinical research and its transition to patient care. In his free time, he enjoys working out and playing soccer and basketball. Mert also plans on pursuing a career in medicine in the future
Jack Leigh
MOTSRTP Research Student
Jack Leigh is a third-year student at the University of Toronto specializing in Pharmacology and Biomedical Toxicology. He joined the Bhat Lab in 2025 with a strong interest in the role of artificial intelligence in personalized medicine and its applications in clinical practice. Jack is passionate about clinical research and aspires to pursue both a master’s degree and a medical degree in the future.
Amyra El Khatib
MOTSRTP Research Student
Amyra is a third-year undergraduate student at the University of Toronto pursuing an Honours Bachelor of Science in Human Biology with minors in Physiology and Immunology. She joined the Bhat Lab in 2025 with an interest in precision and translational medicine, focusing on how liver transplantation research can improve patient outcomes. Amyra intends to pursue a career in medicine and clinical research.
Ayesha Rivera
MOTSRTP Research Student
Ayesha is a third-year undergraduate student at the University of Toronto, pursuing an Honours Bachelor of Science in Health and Disease and Physiology. She joined the Bhat lab in 2025 with an interest in improving patient care through clinical research. In the future, she hopes to pursue a career in medicine. During her free time, she enjoys reading and rock climbing.