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Manjesh Kumar Hanawal

Associate Professor
Industrial Engineering and Operations Research.                                                     
IIT Bombay 

Extended homepage

Research Interests:       

  • Communication Networks
  •  Machine Learning
  • Cybersecurity

Academic Background:

  • B. E.  (2000-2004) - Department of ECE, National Institue of Technology, Bhopal, India
  • M.S (Engg) (2007-2009)  - Department of ECE, Indian Institute of Science, Bangalore, India                
  • Ph.D. (2009-2013) - Team MAESTRO, INRIA and University of Avignon, France

Professional Experience:

  • Scientist-B (2004-2007)  Center for Artificial Intelligence and Robotics, DRDO, Bangalore            
  • Visiting Research Scholar (2013) - Department of ECE, University of Arizona, Tucson, USA  
  • Postdoctoral Associate (2014-2015)- Department of ECE, Boston University, Boston, USA

Contact Information:

Office: Room 201, Second Floor, IEOR Building
Phone (O): +91 22 2576 5420
Mobile: +91 961983 5420
Fax: +91 22 572 6875, +91 22 572 3480
Email: mhanawal@iitb.ac.in

 

Selected publications: 

Manjesh K. Hanawal and S.J. Darak, 'Multi-Player Bandits: A Trekking Approach,' To appear in IEEE Transactions on Automatic Control [link]

S. J. Darak and Manjesh K. Hanawal, 'Multi-player Multi-armed Bandits for Stable Allocation in Heterogeneous Ad-Hoc Networks,' IEEE Journal on Selected Areas in Communication, vol.37, no. 10, Oct 2019 [Link]

D. Ghosh and Manjesh K. Hanawal, and N. Zlatanov, 'Learning to Optimize Energy Efficiency in Energy Harvesting Wireless Sensor Networks,'  To appear in IEEE Wireless Communication Letters. DOI:10.1109/LWC.2021.3058170

A. Verma and Manjesh K. Hanawal, 'Stochastic Multi-Armed Bandits with Control Variates,' To appear in proceeding of Neural Information Processing Systems (NeurIPS), Virtual event, Dec 2021.

A. Verma, Manjesh K. Hanawal, Csaba Szepesvari, and V. Saligrama, 'Online Algorithm for Unsupervised Sequential Selection with Contextual Information,' Proceedings of Neural Information Processing Systems (NeurIPS), Vancouver, Canada, Dec 2020.

A. Verma and Manjesh K. Hanawal, 'Stochastic Network Utility Maximization with Unknown Utilities: A Multi-Armed Bandits Approach,' Proceedings of the International Conference on Computer Communication (INFOCOM), Beijing, China, April 2020.

A. Verma, Manjesh K. Hanawal, A. Rajkumar, and R. Sankaran, 'Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback,' Proceedings of Neural Information Processing Systems (NeurIPS), Vancouver, Canada, Dec 2019.