Dr. Niloy Ganguly is a Professor in the Dept. of Computer Science and Engineering at IIT Kharagpur and a Fellow of Indian Academy of Engineering. He spent 2 years as a Research Scientist in Technical University, Dresden, before joining IIT Kharagpur in 2005, and has risen to the rank of Professor in 2014. He has done his Btech from IIT Kharagpur and his Phd from IIEST, Shibpur. His research interests lie primarily in Social Computing, Machine Learning, and Network Science. He has published in 60 journals and 160 conferences, several of which are in reputed international venues such as NeurIPS, KDD, ICDM, IJCAI, WWW, CSCW, EMNLP, CHI, ICWSM, INFOCOM, Physical Reviews, IEEE and ACM Transaction etc. He has served in the program committee of COMSNETS, NetSciCom, JCDL, WWW, DEBS and CODS. Prof Ganguly’s work has been recognized through awards by NSF, Cisco, NetApp, Samsung, and Yahoo!, among others. He has received prestigious research grants and projects, notably from Data Transparency Lab, IMPRINT, ITRA, Intel, HPE, Adobe, Microsoft Research, Accenture, BEL, and TCS. He has guided 17 Ph.D. and 8 M.S. students during this tenure. He is the founding member of the Complex Networks Research Group (CNeRG), comprising faculty members, research scholars, and other students affiliated to the department. The group is a success story in itself, with several long-standing impactful collaborations, and presence in reputed venues across domains such as Social Computing, Machine Learning and Deep Learning, Natural Language Processing, Network Science, Networked Systems, etc.
Prof. Ganguly is one of the earlier computer scientists worldwide, who have made outstanding contributions in contextualizing the initial theories on complex networks proposed by physicists, and building customized services over them. He has applied network science on large dynamic social networks including Online Social Networks (OSN), Peer-to-peer (P2P) Networks, and Transportation Network. His recent notable works include building expert identification system in Twitter whereby trustworthy content can be recommended. He has also developed several classification and summarization tools to facilitate efficient utilization of Social Media during disasters. One of his important contributions is to build up a probabilistic modeling framework of opinion dynamics, and investigate to which extent incentivized users on social media can steer others’ opinions to a given state. He has also worked extensively on transportation Network to develop several services to enhance the quality of service of public transport in India. Applying network science in analyzing the physical infrastructure and traffic patterns of Indian Railways, and by modeling delays, he has identified most accident prone zones in India, and highlighted the systemic shortcomings in the current state of infrastructures. He has also worked on several theoretical problems pertaining to large complex network like growth of bipartite network, resilience of dynamic peer-to-peer networks etc.