Predictive Modelling with Applications: Supervised and Unsupervised Learning

Dr. Sayantee Jana is a Statistics Faculty at IIT Hyderabad with a diverse experience of teaching doctors, engineers, lawyers, government officers, corporate executives, MBA and undergraduate students across 3 different countries. She has worked on a few different fields of statistics and Machine Learning and collaborates with industry and academia abroad, and regularly visits Universities such as University of Toronto, University of Ottawa and University of Cambridge. Her research areas include but is not limited to ML Models and Data mining for big data from finance and healthcare industry, spatio-temporal modelling and maps, modelling of skewed and volatile data for financial data, and adaptive designs (skewed randomization) for clinical trials in the pharmaceutical industry. She did her PhD in Mathematical Statistics from McMaster University and was a Postdoctoral Fellow at the University of Toronto working on data mining for big data. She has supervised more than 20 UG & PG students in both academic and industry projects, and around 10 engineering professionals from industry in AI/ML projects.

She has received the prestigious Queen Elizabeth Scholarship and Fields Research Fellowship to visit the University of Toronto. She was also the IBS Young Ambassador to the World Statistics Congress in 2019 and the Florence Nightingale Award Winner in 2020. She has served on the Social Program Committee and Awards Committee for the International Biometrics Conference 2022 & 2024. She serves as the Chair of the Country-Representatives Committee for the Caucus for Women in Statistics and its Governing Council member. She has been on panels and organizing committees of international conferences and is an Associate Editor of Statistica Neerlandica, a peer-reviewed journal by the Netherlands Society for Statistics and Operations Research.