Invited Talk by Dr Bamdev Mishra on A unified framework for structured low-rank matrix learning

Title: A unified framework for structured low-rank matrix learning
Speaker: Dr Bamdev Mishra from Microsoft R&D
Host Faculty: Dr.  Vineeth N Balasubramanian
Room No: A-119, Academic block
he vision of the Semantic Web is to provide structure and meaning to the data on the Web. Knowledge representation and reasoning plays a crucial role in accomplishing this vision. OWL (Web Ontology Language), a W3C standard, is used for representing knowledge. Reasoning over the ontologies is used to derive logical consequences. All the existing reasoners run on a single machine, possibly using multiple cores. The amount of available data is increasing at a rapid rate and single machine reasoners will not be able to keep up with this growth rate. They are constrained by the memory and computing resources available on a single machine. In this talk, I will describe my work on distributed ontology reasoning on a tractable profile of OWL with a polynomial reasoning time, called OWL 2 EL. I will also discuss my future research plan and the courses that I would be interested in teaching. 
Speaker bio:

Bamdev Mishra received the BTech and MTech degrees in Electrical Engineering from the Indian Institute of Technology Bombay, India, in 2010, and the PhD degree from the Department of Electrical Engineering and Computer Science, University of Liège, Belgium, in 2014. He was a Postdoctoral fellow at the University of Liège and a Visiting Research Associate at the University of Cambridge in 2015. He is currently a Senior Applied Scientist at Microsoft, India. Prior to that he worked as Machine Learning Scientist in the India Machine Learning Team at His primary research interests span nonlinear optimization and stochastic learning for machine learning applications. For more information, please see

Wednesday, June 6, 2018 - 11:30