Dr. Divya Padmanabhan

Designation : Assistant Professor

Broad Area of Expertise : Computer Science and Engineering

Email : divya{at}iitgoa.ac.in

Contact Number :

Address : F-13, Mining Building, IIT Goa

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Educational Qualifications

  1. PhD from Indian Institute of Science (IISc), Bangalore
  2. MTech from IIT Madras
  3. BTech from NIT Calicut

Areas of Research

Distributionally Robust Optimization, Extremal probability bounds, Operations Research, Machine Learning, Game Theory

Courses Taught

CS 330 Artificial Intelligence

CS 431 Optimization: Theory and Algorithms

Professional Appointments

  1. Assistant Professor, IIT Goa (Dec 2020 - present)
  2. Post Doctoral Research Fellow, Singapore University of Technology and Design (SUTD) Singapore (2017- 2020)
  3. Research Intern, IBM IRL, Bangalore (Summer, 2014)
  4. Research Intern, Xerox Research Centre India, Chennai (Summer 2011)
  5. Applications Engineer, Oracle India Private Limited (2008 - 2010)

Recent Publications

  1. Extremal Probability Bounds in Combinatorial Optimization - with Selin Damla Ahipasaoglu, Arjun Ramachandra and Karthik Natarajan, SIAM Journal of Optimization, 2022
  2. Admission Control in the Presence of Arrival Forecasts with Blocking-based Policy Optimization - with Karthyek Murthy and Satyanath Bhat, Winter Simulation Conference (WSC) 2022
  3. Dominant Strategy Truthful, Deterministic Multi-armed Bandit Mechanisms with Logarithmic Regret for Sponsored Search Auctions" - with Satyanath Bhat, Prabuchandran K. J., Shirish Shevade and Y. Narahari, Applied Intelligence, 2022
  4. "Tree Bounds for Sums of Bernoulli Random Variables: A Linear Optimization Approach", INFORMS Journal of Optimization, 2021 - with Karthik Natarajan
  5. "Exploiting Partial Correlations in Distributionally Robust Optimization", Mathematical Programming, 2021 - with Karthik Natarajan and Karthyek Murthy.
  6. ''Correlation Robust Influence Maximization", NeurIPS 2020- with Louis Chen, Lim Chee Chin and Karthik Natarajan
  7. "Multi-Label Classification from Multiple Noisy Sources Using Topic Models" , Information, 2017 - with Satyanath Bhat, Shirish Shevade and Y. Narahari
  8. "A Dominant Strategy Truthful, Deterministic Multi-armed Bandit Mechanism with Logarithmic Regret", AAMAS, 2017 - with Satyanath Bhat, Prabuchandran K. J., Shirish Shevade and Y. Narahari
  9. "Topic Model Based Multi-Label Classification",IEEE ICTAI, 2016 - with Satyanath Bhat, Shirish Shevade and Y. Narahari.
  10. "A Robust UCB Scheme for Active Learning in Regression from Strategic Crowds", IJCNN 2016 - with Satyanath Bhat, Dinesh Garg, Shirish Shevade and Y. Narahari.
  11. "A Truthful Mechanism with Biparameter Learning for Online Crowdsourcing", AAMAS, 2016 - with Satyanath Bhat, Shweta Jain and Y. Narahari.
  12. Mechanism Design for Stochastic Multi-armed Bandit Problems", Indian Journal of Pure and Applied Mathematics (IJPAM) - Special issue, 2016 - with Shweta Jain, Satyanath Bhat, Ganesh Ghalme, and Y. Narahari.

Recognition and Awards

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