Short Bio: Dr. Tanujit Chakraborty is currently an Associate Professor of Statistics and Data Science at Sorbonne University Abu Dhabi, UAE and Sorbonne Center for AI Paris, France. He also holds Visiting Faculty positions at Duke-NUS Medical School, National University of Singapore. He completed his PhD from Indian Statistical Institute (ISI), Kolkata, India. His thesis was focused on hybrid nonparametric models with a particular focus on their asymptotic properties. His research interests include Machine Learning, Time Series Forecasting, Econometrics, and Health Data Sciences. Dr. Tanujit Chakraborty has maintained an active consulting practice, assisting several companies (PharmaACE, ITC Limited and Bajaj Finserv Corporation) as a consultant. 
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Current Positions: 

Sept, 2024 onwards : Associate Professor of Mathematics (Statistics and Data Science) at Sorbonne University, Abu Dhabi and Paris. 
Sept, 2021 - July, 2024 : Assistant Professor of Mathematics (Statistics and Data Science) at Sorbonne University, Abu Dhabi and Paris. 
July, 2023 onwards : Visiting Professor at Duke-NUS Medical School, National University of Singapore, Singapore.
June, 2022 onwards : Adjunct Professor at Woxsen Business School, Hyderabad, India.

​Past Experiences :
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Dec, 2022 -  March, 2023 : Forecasting Consultant for Pharma Forecasting Tool Development, PharmaACE Analytics Private Limited.
July, 2021 - October, 2021 : Guest Lecturer for "Data Analytics" course (MBA) at Indian Institute of Foreign Trade (IIFT), India. 
June, 2021 - November, 2021 : Guest Professor for "Causal Inference in Statistics" course at XIM University Bhubaneswar, India. 
Dec, 2020 - Feb, 2021 : Statistical Consultant for Data Science Consulting Assignment at BIU - Advanced Analytics, Bajaj Finance Ltd.

Academic Qualifications :

July, 2016 - Nov, 2020 : Doctor of Philosophy (Ph.D.) from Indian Statistical Institute, Kolkata, India.
Thesis Title : Some Nonparametric Hybrid Predictive Models : Asymptotic Properties and Applications
July, 2014 - June, 2016 : Master of Science (M.S.) from Indian Statistical Institute, Kolkata, India.
Master's Project: Statistical Methodology for Process Efficiency Improvement in Paper Manufacturing at ITC Limited, Tribeni, India.
July, 2010 - May, 2013 : Bachelor of Science (B.Sc.) from Bidhannagar College, Kolkata, India.
Subjects : Statistics (Honours), Mathematics, Physics.
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​Awards and Grants :​​
  • Recipient of Mphasis Research Grant in Deep Learning for Climate Change (July, 2024 onwards); Role: Co-PI, Funding: 3 million INR.
  • Recipient of Mphasis Research Grant in Cognitive Computing (May, 2021 - Dec 2023); Role: Co-PI, Funding: 3 million INR.
  • Best Paper Award Winner at ACM IKDD (CODS-COMAD) in Jan, 2021.
  • Best Student Paper Award (Application Category) at 52nd Annual Convention of ORSI & International Conference held at IIM Ahmedabad in December 2019.
  • B.G. Raghavendra Memorial Award for Best Paper (Application Category) from Operational Research Society of India (ORSI) in December 2017.
  • Junior & Senior Research Fellowship Award from Indian Statistical Institute, Kolkata from July 2016 to November 2020. 

​Refereed for Journals: 
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  • I have worked as a reviewer for the following Journals (Multiple Papers for some of the Journals): Journal of American Statistical Association (JASA), Neural Networks, SIAM Journal on Applied Dynamical Systems, IEEE TNNLS, IEEE TKDE, International Journal of Forecasting (IJF), Statistics in Medicine, Reliability Engineering & System Safety, Technological Forecasting & Social Change, Journal of Applied Statistics, Journal of Computational and Applied Mathematics, Expert Systems with Applications, Scientific Reports, Finance Research Letters, Stochastic Environmental Research and Risk Assessment, Computers in Biology and Medicine, Computational Economics, Computer Networks, Engineering Applications of Artificial Intelligence (EAAI), IEEE Journal of Biomedical and Health Informatics, PLOS Digital Medicine, The American Journal of Tropical Medicine and Hygiene, PLOS One. 
  • Member of the Programme Committee for ICMLA 2021, ICMLA 2022, ICMLA 2023. ​

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