Dr. Mamatha Bhat MD, MSc, PhD, FRCPC


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

Elisa Pasini

Residency in Laboratory Medicine and Pathobiology, Udine, Italy.
MSc in Biological Sciences with Pathophysiology Specialty, Bologna, Italy.

 Current Research:
  • Analyst involved in most of the projects in the lab and helps in student supervision
  • Integration of multi-omics data in liver cancer and post-transplant diseases
  • Network analysis and graphical visualization of protein-protein-interactions in liver cancer and post-transplant diseases
  • Molecular validation of bioinformatics predictions for liver diseases

Cristina Baciu

Scientific Associate

PhD in Bioinformatics and Computational Biology – UNC Charlotte, USA
MS in Biochemistry / Computational Chemistry – Univ. of Windsor, ON
BSc in Chemical Engineering – Technical Univ. Ghe. Asachi -Iasi, Romania

Current Research:
  • Contributing to developing a machine learning tool leveraging methylation patterns in cell free DNA and clinical data, as non-invasive biomarker for graft pathology and liver diseases in general.
  • Overseeing the basic research projects in the lab, helps with grant applications, collaborative projects and bioinformatics analyses. She has extensive experience in cancer research, biomarker discovery in various diseases, multi-omics data integration, network and pathway analysis.


Sameera Rizvi

Clinical Research Coordinator

Graduated from Medical school at Dow Medical University, Karachi, Pakistan
Post Graduate Diploma in Clinical Research Associates- 1994.

Current Research:
  • The GLP-1 agonist Semaglutide for the treatment of Metabolic Disease in Liver Transplant Recipients: A Phase IV, randomized trial
  • Plasma cell-free methylated DNA (cfMeDIP-seq): A non-invasive, Specific Marker for Liver Disease and Graft Pathology
  • Screening for Post-Transplant NAFLD to Optimize Outcomes
  • Prevention of Metabolic Disease Post-Transplant with Prebiotics: A Randomized, Placebo-controlled Crossover Trial

Yingji Sun

(Co –supervised with Prof. Michael Brudno and Dr Aman Sidhu) TAI Initiative

Yingji Sun is a Machine Learning Analyst who joined our lab as in December 2021. With a Master of Science in Biostatistics – Dalla Lana School of Public Health, University of Toronto
Honours BSc in Physiology and Statistics – University of Toronto

Current Research:
  • Employing machine learning methods to predict the survival trajectories of NASH patients and PSC patients on liver transplant waitlist

Post-Doctoral Fellows

Anh Thu Nguyen

Anh Thu Nguyen-Lefebvre

  • PhD in Cellular, Molecular Biology, and Oncology, Universite Claude Bernard Lyon, France
  • Master of Science in Functional Genetics and Cellular Pathologies, Universite Claude Bernard Lyon, France
  • BSc in Genetics – Universite Claude Bernard Lyon, France
Current Research:
  • Delineating different cell populations, biological markers, and signaling pathways driving liver regeneration in post liver transplantation/resection patients. We use single nucleus profiling and image mass cytometry to answer this question.
  • The lifespan of the liver grafts is finite and graft fibrosis is accelerated in the presence of de novo or recurrent disease. In this project, she aims to identify specific cell types and molecular signatures driving liver graft fibrosis using single nucleus profiling and to examine markers and cellular microenvironment of graft fibrosis in a longitudinal study.

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

  • (Co –supervised with Prof. Michael Brudno) Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Award
  • PhD (Bioinformatics), Saw Swee Hock School of Public Health, National University of Singapore
  • Master of Science in Digital Media Technology, School of Computer Science and Engineering, Nanyang Technological University, Singapore
  • Bachelor of Technology in Information Technology, West Bengal University of Technology, India
Current Research:
  • Machine learning for multi-modal data integration to predict clinical outcomes in liver transplantation settings

Chong Wa To (Jeffrey) 

  • PhD in Cellular, Molecular Biology, and Oncology, The Hong Kong Polytechnic University, Hong Kong
  • BSc (Honours) in Applied Biology with Biotechnology, The Hong Kong Polytechnic University, Hong Kong
Current Research:
  • Evaluating the therapeutic effect of nanoparticle-mediated siRNA delivery for HCC therapy.
  • Delineating the molecular profiles of recurrent HCC post-transplant.


Anirudh Gangadhar

  • (Co –supervised with Prof. Michael Brudno and Dr Aman Sidhu) TAI initiative
  • Ph. D. in Chemical Engineering, Texas Tech University, USA, 2022
  • M.S. in Chemical Engineering, University of Florida, USA, 2016
  • B.E. in Chemical Engineering, Manipal Institute of Technology, India, 2014
Current Research:
  • Developing Deep Learning tools using histopathological whole slide images (WSIs) to examine graft pathology in liver transplant patients.
  • Building predictive Machine Learning models to investigate survival benefit of living donor liver transplant.


Ghazal Azarfar

  • (Co –supervised with Prof. Michael Brudno and Dr Aman Sidhu) TAI initiative
  • Ph.D. in Computational Imaging, University of Wisconsin Milwaukee, Milwaukee, USA, 2019
  • M.S. in Electrical and Computer Engineering, Shahid Beheshti University, Tehran, Iran, 2014
  • B.Sc in Electrical and Computer Engineering, Shahid Beheshti University, Tehran, Iran, 2012

She joined Bhat lab as a post-doctoral fellow in the summer of 2023. She has a strong background in applying deep learning techniques to analyze pathological images and CT scans for cancer management.

Current Research:
  • Leveraging the power of deep learning to advance personalized medicine in lung and kidney transplant patients.

Graduate Students

Yilin Sun

  • DoM QEII award University of Toronto
  • Master of Science Candidate – Institute of Medical Science, University of Toronto
  • Honours BSc in Biomedical Sciences and minor in neuroscience, University of Guelph
Current Research:
  • Identifying exosomal biomarkers in plasma of normal vs abnormal liver regeneration

Alyssa Apilan

Master of Applied Science Candidate – Institute of Biomedical Engineering, University of Toronto

Previous Education: Honours BSc in Biology, McMaster University

Current Research:
  • Dexamining the role of porphysomes in the context of image-guided treatment for hepatocellular carcinoma using animal models

Medical Students

Xiaoting You

Nimit Vediya

Aditi Venkatraman

Anushka Patel

Yi-Hsuan Yeh

Current Undergraduate Students

Priya Sheth
Arya Rahmani
Mouaid Alim
Aarian Bhakoo
Rhea Varghese
Khyathi Rao
Serena Bansal
Cherry Xu
Jason Yang

Lab Alumni

Hussein Haman

Post-Doc Fellow (June 2024-November 2024).

Catherine Chen

Fall Student (2020 Sep-2021 Apr, 2019 Sep – 2020 Apr, 2018 Sep – 2019 Apr)

Shruti Misra

Fall Student (2020 Sep- 2021 Apr, 2019 Sep – 2020 Apr)
Summer Student (2019 May – 2019 Aug)

Cindy Wei

Fall Student (2020 Sep- 2021 Apr)

Peihao Li

Fall Student (2019 Sep – 2020 Apr)

Cathy Yang

Fall Student (2019 Sep – 2020 Apr), Summer Student (2019 May – 2019 Aug)

Nan Ji Suo

Fall Student (2019 Sep – 2020 Apr)

Andrew Rogalsky

Summer Student (2019 May – 2019 Aug)

Praniya Nesan

Summer Student (2019 May – 2019 Aug)

Catherine Hu

Summer Student (2019 May – 2019 Aug)

Cherie Tang

Summer Student (2019 May – 2019 Aug)

Madhumitha Rabindranath

(Sept 2021 – June 2023)

Fuad Mohammad

Transplant Hepatology fellow

Ahmed Marwan Mansour

Transplant Hepatology fellow

Maryam Naghibzadeh

(June 2022-July 2023)

Anita Bakrania

(January 2021-July 2023)

Amirhossein Azhie

(2019-2022), Post Transplant NASH

Fakhar Ali Qazi Arisar 

Machine Learning in Liver TransplantationNASH

Victor Dong 

(2019-2020), Outcomes of Liver Transplantation for Patients with NASH Cirrhosis in ICU at Time of Transplant.

Neta Gottlieb

(2020-2021), Machine Learning in Liver Transplantation

Chinmay Bera 

(2019-2021), Changes in Long-term Survival and Causes of Mortality After Liver Transplantation.

Amanpreet Brar

(2020 – 2022) – Molecular Machine Learning in HCC

Saranya Sivaraj

(2019 Apr – 2020 Nov), Probiotics to prevent the Progression of Non-alcoholic Steatohepatitis to Cirrhosis

Graziano Oldani

(2018 Dec – 2020 Jun), Pathway-based Analysis of Liver Regeneration.

Ravi Kiran

(2018 Dec – 2020 Jan), Prediction of Survival after Transplant for NASH Cirrhosis.

Raj Uchila

(2019 Aug – 2020 June), Outcomes of Liver Transplantation for Lean and Obese NASH Cirrhosis.

Saeed Almarzooqi

(2018 Dec – 2019 Oct), Cardiovascular Complications after Liver Transplantation.

Sreelakshmi Kotha

(2018 Dec – 2019), Meta-analysis of Post-transplant diabetes.

Divya Sharma

(2020 Oct – 2021 Sept), Application of ML tools for liver disease detection and analysis.

Radmehr Rahemipour

(2019 Sept – 2021 Sept), Development of Porphysomes as Treatment for Hepatocellular Carcinoma.

Anshu Malik

(2020 Dec – 2021 Sept), Probiotics to prevent the Progression of Non-alcoholic Steatohepatitis to Cirrhosis.

Marc Angeli

(2018 Dec – 2021 Sept), Post-Transplant outcomes.


This 3D image depicts the liver at the microscopic level. Liver cells are organized around the central veins to form hexagonal hepatic lobules that are powerhouses of liver metabolism and immune-metabolic regulators upon infection.