team members

Stroke Innovations - Machine Learning for QI Lab Members

Arjun Balachandar
Arjun Balachandar

Arjun is a neurology resident at the University of Toronto with a strong interest in applying computational methods and AI to clinical medicine and neuroscience. He studied neuroscience at McGill University followed by medicine at the University of Toronto, during which time he worked on research in computational neuroscience in pain network modeling (SickKids Hospital), machine learning methods to diagnose movement disorders (University Health Network) and electrophysiological studies of deep brain activity during sleep in movement disorders patients before joining the lab of Dr. Khosravani. He enjoys doing calisthenics, hiking and flying his drone in his free time.

Eptehal Nashnoush
Eptehal Nashnoush

Eptehal is a data scientist with a Master's in Data Science from the University of Toronto and a Bachelor's in Electrical Engineering from Dalhousie University. With a primary focus on research, Eptehal led Machine Learning projects at Dalhousie University, the University of Toronto and MIT. Her work covers areas like Computer Vision in Clinical Pathology, Natural Language Processing, 3D Ultrasound technology, and identifying the impact of biases in complex hospital data. Eptehal was selected as a recipient for the Google CSRMP program, where she delved into industry-specific research projects at Google. As a fun fact, Eptehal co-founded the 2023 Toronto Health Datathon, connecting AI health research with entrepreneurship.

Rami Saab
Rami Saab

Rami holds a Bachelor of Engineering (B. Eng) from McMaster University in Biomedical Engineering and a MASc from the University of Toronto. His past research experiences include EEG based brain-computer interfaces, surgical robotics, and most recently, using vocal features as a marker of neurological conditions. He has also worked in industry in health tech. Rami is now a medical student in the Temerty Faculty of Medicine at the University of Toronto where he hopes to continue working on bridging the fields of technology and health.

Hamza Mahdi
Hamza Mahdi

Hamza holds a Bachelor of Engineering in biomedical engineering (TMU) and received his master’s in electrical and computer engineering from the University of Waterloo. He is currently pursuing a degree in medicine from the Schulich School of Medicine. His past research experience includes medical physics, space robotics, human–robot interaction, rehabilitation robotics and biomedical image analysis in orthopaedics/neurosurgery. He is currently interested in clinically useful AI applications in healthcare, and in rehabilitative technologies. He likes to participate in STEM education in his free time.

Rishit Dagli
Rishit Dagli

Rishit Dagli is a Computer Science freshman at the University of Toronto. He has a passion for researching and working with Machine Learning, specifically focusing on Computer Vision and Learning Dynamics. Recently, his interests have centered mainly around generative vision models and neural rendering. In addition to his academic pursuits, Rishit also works as a research intern at Civo. He is actively involved in the open-source community, where he maintains and contributes extensively to popular open-source projects, and enjoys building new open-source projects.

Ben Tilley
Ben Tilley

Originally from the UK, Dr Bension Tilley completed his MD-PhD at Imperial College London. His PhD research focused on the neuropathology of Parkinson’s disease. He has ongoing research interests in stroke and movement disorders, and is a keen educator to both medical students and the wider public. He is currently a PGY-1 Neurology Resident at the University of Toronto. Outside of work, he loves cooking, playing golf and spending time with his wife and new kitten, Sorrel.

Lucas Perri
Lucas Perri

Lucas is a high school student with a passion for the intersection of biological sciences (chemistry), technology, and artificial intelligence. Despite the remarkable advances in these fields, there is recognition that novel treatments remain elusive - he is interested in rising to this challenge of working on the use of AI for personalized treatments at the intersection with biological sciences.

Diya Ahmad
Diya Ahmad

Diya comes from McMaster University, where she graduated from the Health Sciences’ Class of 2022. At McMaster, Diya explored research in pediatric endocrinology, specifically in helping produce a one-stop website for parents of children with diabetes during the COVID-19 pandemic. Diya is now a second-year student at the University of Toronto, where she has been involved in obstetrics research on the timing of antenatal corticosteroids. She now looks forward to learning more about neurology through clinical shadowing and academic research.

Houman Khosravani
Houman Khosravani

Houman is an Assistant Professor, Division of Neurology, University of Toronto - Principle Investigator of SiLab-ML4QI. I am a physician with expertise in stroke, internal medicine, critical care, and neurocritical care. My interests are quality improvement in health systems, human performance factors and simulation in acute medicine, and palliative medicine in clinical neurosciences. I am passionate about leveraging machine learning to improve the quality of healthcare delivery in acute and in-patient neurology.