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 UHN’s Ajmera Transplant Centre, and an Assistant Professor of Medicine at the University of Toronto. She is also a Scientist at Toronto General Hospital Research Institute and has a graduate appointment with the Institute of Medical Sciences. Dr. Bhat completed her medical school and residency training, including the Clinician Investigator Program, at McGill University. She then completed a Transplant Hepatology fellowship at the Mayo Clinic in Rochester, Minnesota, followed by a Canadian Institutes of Health Research (CIHR) Fellowship for Health Professionals, through which she completed a PhD in Medical Biophysics (U of T).
The goal of Dr. Bhat’s research program is to improve long-term outcomes of liver transplantation through a precision medicine approach. Her program is unique in using tools of Artificial Intelligence with bioinformatics to personalize the care of liver transplant recipients based on an improved biological understanding of the liver and disease after transplant. Her interdisciplinary program and team have been supported by CIHR, Terry Fox Research Institute, Stem Cell Network, Canadian Donation and Transplant Research Program, Natural Sciences and Engineering Research Council (NSERC), Canadian Liver Foundation (CLF), among others. Dr. Bhat is on the Executive committee of the CDTRP; Vice-Chair of the International Liver Transplant Society Basic and Translational Science Research committee; and is an Associate Editor for the American Journal of Transplantation. Dr. Bhat has also been the recipient of recognitions such as the 2022 CIHR-INMD-CASL Early Career Researcher prize, the 2020 Polanyi Prize and the 2021 American Society of Transplantation Basic Science Career Development Award.
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.
Cristina Baciu
Scientific Associate II
Cristina completed her PhD degree in Bioinformatics and Computational Biology at UNCC, NC, USA. Previously she graduated with Master of Science in Biochemistry/Computational Chemistry at University of Windsor, ON, Canada. She has developed a passion for cancer research, epigenomics, non-invasive biomarker discovery, multi-omics data integration, network and pathway analysis, among others. Her vision is to use her experience in bioinformatics to help in developing machine learning tools for medicine.
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
Shiyi Chen
Biostatistician
Shiyi Chen joined Dr Mamatha Bhat’s lab as a full time Biostatistician in January 2024. Shiyi earned her Master of Science degree in Biostatistics from the Dalla Lana School of Public Health at the University of Toronto, ON, Canada. She has statistical research background in liver transplant, bone marrow transplant (BMT), pediatric diseases as well as HIV related outcomes. Shiyi is currently actively involved in the study design, statistical modelling development and data analysis of various clinical research studies in Dr Bhat’s team. She is well versed in various statistical techniques and is experienced in analyzing liver transplant related survival, treatment efficacy and disease prevention. Her vision is to use her experience in statistics to tell meaningful stories, drive clinical insights and enable long-term positive impacts.
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.
Post-Doctoral Fellows
Nadia Prayitno
- Doctor of Natural Sciences (Dr. rer. nat) in Molecular Biology, Chromatin Biology – Ludwig-Maximilians-Universität München, Germany
- Master of Science in Molecular Medicine – Georg-August-Universität Göttingen, Germany
- Honours BSc in Immunology, Molecular Genetics & Microbiology – University of Toronto, Canada
Nadia holds a doctoral degree for her work on the role of roX RNA in Dosage Compensation during Drosophila melanogaster embryogenesis, where she utilized a variety of molecular and cellular biology, biochemistry, NGS, and bioinformatic techniques. She joined the lab in July 2021 and is a trainee of the Canadian Donation and Transplantation Research Program.
Current Research:
- Elucidating the epigenetic effects of environmental factors on an aggressive form of NASH by integrating multi-comics data of post-transplant NASH
- Evaluating novel approaches for the treatment of NASH
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.
Ghazal Azarfar
Post-doctoral Researcher
Ghazal earned her PhD from the University of Wisconsin, where she specialized in analytical chemistry and bioanalysis, employing machine learning to analyze chemical images and study the response of single cells to environmental stress. Passionate about leveraging innovative multimodal AI solutions to enhance clinical practice, Ghazal has joined Dr. Bhat’s lab as part of the Transplant AI Initiative. Here, she applies the team expertise in clinical knowledge, computer science, and data analytics to drive advancements in transplant medicine, focusing on managing and understanding post-transplant complications such as the recurrence of hepatocellular carcinoma, sepsis, and lymphoproliferative disorders.
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.
Graduate Students
Nilah Ahimsadasan
Nilah Ahimsadasan completed her Honors Bachelor of Medical Sciences with a Double Major in Physiology and Interdisciplinary Medical Sciences at the University of Western Ontario. She is currently in her third year of medical school at Queen’s University.
International MD Graduate
Maryam Shojaee
Clinical Research Volunteer
Maryam Shojaee is an international MD-MPH graduate who received her degree from Tehran University of Medical Sciences. She joined Dr. Bhat’s lab in May 2024. Maryam is interested in the field of transplant and post-transplant disease research. She is currently involved in data extraction and writing papers focusing on post-liver transplant fibrosis.
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.
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.
Rachel Zhu
MOTSRTP Research Student
Rachel is a fourth-year undergraduate student at Western University, studying pathology and pharmacology. She joined the Bhat lab in 2024 with an interest in research focused on improving patient outcomes. She hopes to pursue a career in digital pathology and diagnostics to support early disease detection.
Xiaoting You
Nimit Vediya
Aditi Venkatraman
Anushka Patel
Yi-Hsuan Yeh
Current Undergraduate Students
Ankit Ray
MOTSRTP Research Student
Ankit is a fourth-year undergraduate student at the University of Western Ontario studying Medical Bioinformatics. He joined the team in 2023 and worked on data collection for different clinical studies. Ankit hopes to further his knowledge on the intersectionality of AI and healthcare, and pursue a career in medicine.
Quynh Phi
MOTSRTP Research Student
Quynh is a fourth-year undergraduate student at the University of Western Ontario with an Honours Bachelor’s of Medical Sciences, specializing in Physiology and Pharmacology. She joined the Bhat lab in 2024 with an interest in clinical research. Quynh hopes to pursue a career in academic medicine, conducting patient care, research, and teaching.
Mouaid Alim
Undergraduate Researcher
Mouaid is in his fourth-year at the University of Toronto, specializing in Bioinformatics and Computational Biology, with a double major in Computer Science and Human Biology. He joined the lab in Fall 2021 and has worked on various projects, including publishing reviews on Artificial Intelligence, Bioinformatics, and Liver Disease. Currently, Mouaid is focused on applying deep learning models to predict patient state evolution on the liver transplant waitlist. With a strong interest in innovation and the applications of AI in healthcare, he is driven to pursue a career in medicine, aiming to make a transformative impact on patient care and medical research.
Sage (Soyeon) Kim
MOTSRTP Research Student
Sage is a third-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 focuses on clinical research and social determinants of health disparities in transplantation. Driven by a passion for medicine, Sage is committed to making an impact in direct patient care while advocating for upstream policy changes.
Jennifer Lee
MOTSRTP Research Student
Jennifer is a third-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.
Muhammad Enrizky Brillian
MOTSRTP 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.
Asher Wiggins
Undergraduate Researcher
Asher is a fourth-year undergraduate Honours Bachelor of Health Science student with a specialization in health research at the University of Waterloo. He joined the Bhat lab in 2024, with research interests in bioinformatics, machine learning, and ethnic disparities in liver transplant. In the future, Asher plans to further pursue his passions through medicine and public health.
Rachel Zhu
MOTSRTP Research Student
Rachel is a fourth-year undergraduate student at Western University, studying pathology and pharmacology. She joined the Bhat lab in 2024 with an interest in research focused on improving patient outcomes. She hopes to pursue a career in digital pathology and diagnostics to support early disease detection.