Ishanu Chattopadhyay

Research Summary
Ishanu Chattopadhyay’s research focuses on the theory of unsupervised machine learning and the interplay of stochastic processes and formal language theory in exploring the mathematical underpinnings of the question of inferring causality from data. His most visible contributions include the algorithms for data smashing, inverse Gillespie inference, and nonparametric nonlinear and zero-knowledge implementations of Granger causal analysis that have crucial implications for biomedical informatics, data-enabled discovery in biomedicine, and personalized precision health care. His current work focuses on analyzing massive clinical databases of disparate variables to distill patterns indicative of hitherto unknown etiologies, dependencies, and relationships, potentially addressing the daunting computational challenge of scale and making way for ab initio and de novo modeling in an age of ubiquitous data. Chattopadhyay received an MS and PhD in mechanical engineering, as well as an MA in mathematics, from the Pennsylvania State University. He completed his postdoctoral training and served as a research associate in the Department of Mechanical Engineering at Penn State. He also held a postdoctoral fellowship simultaneously at the Department of Computer Science and the Sibley School of Mechanical and Aerospace Engineering at Cornell University.
Education
  • Cornell University, NY, Postdoctoral Fellow Machine Learning 2013
  • The Pennsylvania State University, PA, Postdoctoral Fellow Robotics & Automated Decision-making 2011
  • The Pennsylvania State University, PA, PhD Mechanical Engineering 2006
  • The Pennsylvania State University, PA, MA Mathematics 2006
  • The Pennsylvania State University, PA, MS Mechanical Engineering 2005
Publications
  1. Chattopadhyay I, Kiciman E, Elliott JW, Shaman JL, Rzhetsky A. Conjunction of factors triggering waves of seasonal influenza. Elife. 2018 02 27; 7. View in: PubMed

  2. Chattopadhyay I, Lipson H. Data smashing: uncovering lurking order in data. J R Soc Interface. 2014 Dec 06; 11(101):20140826. View in: PubMed

  3. Chattopadhyay I, Kuchina A, Süel GM, Lipson H. Inverse Gillespie for inferring stochastic reaction mechanisms from intermittent samples. Proc Natl Acad Sci U S A. 2013 Aug 06; 110(32):12990-5. View in: PubMed

  4. Chattopadhyay I, Lipson H. Abductive learning of quantized stochastic processes with probabilistic finite automata. Philos Trans A Math Phys Eng Sci. 2013 Feb 13; 371(1984):20110543. View in: PubMed

  5. Chattopadhyay I, Ray A. Supervised self-organization of homogeneous swarms using ergodic projections of Markov chains. IEEE Trans Syst Man Cybern B Cybern. 2009 Dec; 39(6):1505-15. View in: PubMed

  6. Jaideep Dhanoa, Balaji Manicassamy, Ishanu Chattopadhyay. Algorithmic Bio-surveillance For Precise Spatio-temporal Prediction of Zoonotic Emergence. arXiv:1801.07807. 2018.::::

  7. Ishanu Chattopadhyay. Causality Networks. arXiv:1406.6651v1. 2014.::::