Dr. Sujoy Chatterjee
Dr. Sujoy Chatterjee is currently working as an Assistant Professor in the Department of Informatics, University of Petroleum and Energy Studies (UPES), Dehradun, India. Before joining in UPES, he was a Post-doctoral Research Fellow (UNIST Research Scientist) in Ulsan National Institute of Science and Technology (UNIST), South Korea. Previously, he did another Post-doc from I3S laboratory, University of Cote d'Azur, Sophia-Antipolis, France. He also performed research as short-term visiting researcher in DIBRIS Lab, University of Genova, Italy. Prior to this, he completed B.Sc (honours) in Physics from University of Calcutta, India in 2006, Master of Computer Applications (MCA) from West Bengal University of Technology, India in 2010, and Master of Technology (M.Tech) in Computer Science and Engineering from University of Kalyani, India in 2013. He obtained his Ph.D from University of Kalyani in 2018. His research interests includes human computer interaction, data mining, machine learning, etc. He has published several papers in different reputed international conferences like CHI, ICDE, AAAI HCOMP, AAAI Symposium Series, ACM IKDD CODS and journals. He received several student travel grant awards and best paper award in various conferences in India and abroad. He visited Stanford University and San Diego, USA for presenting his papers in ICDE 2017, AAAI Spring SSS 2017, etc. He visited Indian Institute of Science at Bangalore in WINE 2017, IIT Madras in IKDD CODS 2017 to present papers in different conferences. He was selected among 15 Young Researchers to receive Young Investigator Training Program Funding (YITP) to visit 1 month Research in Italy from IEEE AIKE Conference Organizing Committee.
1. Weighted Rank Aggregation of Crowd in Knowledge-Based Systems
2. A Probablistic Model for Group Decision Making in CHI Extended Abstract
3. Smart City Planning using Constrained Crowd Judgment Analysis in AAAI Spring Symposium
4. Judgment Analysis Based on Crowdsourced Opinions in IEEE ICDE
5. Dependent Judgment Analysis Based on Crowdsourced Opinions in Information Sciences
6. A Review of Judgment Analysis Algorithms for Crowdsourced Opinions, IEEE Transactions on Knowledge and Data Engineering