Jathurshan Pradeepkumar
CS PhD Student
University of Illinois Urbana-Champaign

I am a first-year Computer Science Ph.D. student at the University of Illinois Urbana-Champaign. My focus here involves developing machine learning methods tailored to address challenging problems in healthcare. I am deeply passionate about using Deep learning for better diagnosis, treatment, and care for individuals with cancer or neurodegenerative diseases. In alignment with this objective, my current focus spans across Large Language Models, Generative Models, Time-series Predictive Modeling, Clinical Trial Optimization, and Synthetic Data for Health. Prior to this, I worked in diverse areas, including physiological signal-based predictive modeling,  computational imaging, pathology and microscopy image analysis, sleep monitoring, behavioral studies, and computational biology. 


Outside work, I follow sports (Formula 1 and Cricket), play badminton, and travel.

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News


 Education

 Research Experiences

PhD Student

UIUC CS

2023 - Present

BSc in Biomedical Engineering

University of Moratuwa

2017 - 2022

Post-Bac Fellow

Computational Imaging / Computational Biology

Harvard University

2021 - 2023

Research Intern

University of Melbourne, Australia 

2020 - 2021

Bio (Before Grad Studies)

Previously, I was a joint post-baccalaureate fellow affiliated with the Wadduwage Lab and SO Lab at Harvard University. My current research focuses on the application of deep learning techniques for microscopy image analysis and histopathology with Dr. Dushan Wadduwage, and modeling structural ensembles that represent conformational changes of proteins with Dr. Sergey Ovchinnikov. 

Prior to my time at Harvard, I pursued my bachelor's degree in biomedical engineering at ENTC, University of Moratuwa, Sri Lanka. I did my thesis project on "Interpretable Multi-Modal Sleep Monitoring System using Ear-EEG and EOG" done under collaboration with Dr. Chamira Edussooriya, Dr. Anjula De Silva and Dr. Simon Lind Kappel. 

During my senior year, I worked on a Harvard-MIT collaborative research as a remote undergraduate researcher with Dr. Dushan Wadduwage, where I developed a deep learning based inverse solver reconstruct microscopy images such that 1) the developed deep learning algorithm is independent of the physics of microscopy and 2) the number of excitation patterns required for reconstruction is minimal.  

Previously, I pursued my remote research internship with Dr. Sam John at University of Melbourne, Australia, where I developed a mouse retinal layer segmentation algorithm for a study on Parkinson’s disease. 

HONORS AND AWARDS

Dec - 2022

Sept - 2021

Oct - 2020

First Class (Honors) - BSc in Biomedical Engineering

Second-Runners up at Video and Image Processing Cup at International Conference on Image Processing (ICIP).

IEEE SMC Winners at BR4IN.IO Hackathon at IEEE System, Man and Cybernetics Conference,Toronto.