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 was a Visiting Professor in Leibnitz University of Hannover for two years from 2021 - 2022. He has also 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.