Ishanu Chattopadhyay
Assistant Professor at University of Kentucky College of Medicine
United States
Summary
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Senior🎓
Top SchoolIshanu Chattopadhyay is an Assistant Professor and leader of the ZeD lab, specializing in algorithmic foundations of automated analysis for complex biological, medical, and social systems. With over a decade of experience spanning research appointments at Penn State, Cornell, and the University of Chicago, he develops unsupervised machine learning methods to detect emergent structures, predict rare/extreme events, and map dynamical cross-talk. His work bridges theory and clinical digital health, translating principled models into AI tools for medicine and social science. Trained in mathematics and mechanical engineering (MA/MS/PhD), he combines rigorous analytical background with practical biomedical informatics expertise. Notably, his research emphasizes understanding the mechanisms that drive system fate rather than only optimizing predictive performance.
10 years of coding experience
18 years of employment as a software developer
MA (Mathematics), MS (Mech. Engg.), PhD (Mech. Engg.), MA (Mathematics), MS (Mech. Engg.), PhD (Mech. Engg.) at The Pennsylvania State UniversityBS, Mechanical Engineering, BS, Mechanical Engineering at JUCornell University
Github Skills (22)
health6
time-series4
haversine4
statistics4
discovery4
python3
angle3
earth3
feature-selection3
webscraper3
points3
coordinates3
machine-learning2
wgs842
data-science2
Programming languages (3)
Github contributions (5)
zeroknowledgediscovery/ehrzero
Apr 2019 - Sep 2019
Estimation of the risk of future diagnoses of neuropsychiatric disorders (particularly autism) in early childhood, based on the diagnostic codes recorded during doctor visits. The prediction pipeline is based on inferring optimal stochastic generators for diagnostic code sequences, and detecting subtle deviations that drive up risk of an eventual neuropsychiatric diagnoses. The out-of-sample AUC score on the Truven dataset of insurance claims (close to 3 million children in out-of-sample data) is just over 80%, for both males and females.
Contributions:1 release, 45 commits, 4 pushes in 4 months
zeroknowledgediscovery/zedstat
Aug 2022 - Dec 2022
Contributions:1 release, 142 commits, 157 pushes in 3 months
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