Can we learn temporal models even with some missing observations? We offer an efficient neural point process named IMTPP in this paper, which can accurately predict next events in a temporal event stream.
I am an associate professor and the DS Chair of Artificial Intelligence at the Department of Computer Science and Engineering at IIT Delhi. Until recently I worked as a research scientist at IBM Research as part of their AI Research team. Before joining IBM in 2014, I worked as a faculty member at IIIT Delhi, where I founded the Max-Planck Partner Group on Large-scale Graph Search and Mining. Even before joining IIIT-D, I was a senior researcher at the Max-Planck Institute for Informatics (MPII) as part of the Databases and Informatics Systems department. My PhD (2005) was from the Indian Institute of Science, Bangalore.
Interests
- Large-scale graph data management
- Influence Propagation and Community Formation on Location- and Activity-based Social Networks
- Knowledge-bases - infrastructure, modelling and practical usage
- Data wrangling - data integration, relationship discovery and visualization
- Information Retrieval using KB and neural models
Education
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PhD, 1998-2005
IISc
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BE, 1991-1995
Bangalore University
