CV

Education

• Ph.D in Computer Science, University of Massachusetts, 2017-2022 (expected)
  • Advisor: Professor Andrew Lan
• M.S. in Electrical Engineering, Indian Institute of Science, 2012-2014
  • Advisor: Professor P.S. Sastry

Work experience

• Research Intern, Machine Learning, Summer 2019
  • Adobe Research, San Jose, CA, USA
  • Optimal Bidding Strategy in Real-time Bidding System
  • Supervisor: Dr. Vishy Swaminathan, Dr. Saayan Mitra, Dr. Somdeb Sarkhel
• Research Intern, Data Science, Summer 2018
  • Adobe Research, San Jose, CA, USA
  • Bid landscape forecasting in Real-time Bidding System
  • Supervisor: Dr. Vishy Swaminathan, Dr. Saayan Mitra, Dr. Somdeb Sarkhel
• Software Engineer 2, July 2014 - August 2017
  • Microsoft Corporation, Bangalore, India
  • Selection and Relevance Algorithms in Sponsored Search (Bing Ads/ Microsoft Advertising)
  • Supervisor: Rahul Agrawal

Skills

• Python, C, Java, C#, Matlab, R
• PyTorch, Tensorflow

Publications

• Context-Aware Attentive Knowledge Tracing

  Aritra Ghosh, Neil Heffernan, and Andrew S Lan.

  Proceedings of the 2020 ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020 (KDD).

  Code

• Optimal Bidding Strategy without Exploration in Real-time Bidding Bidding

  Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, and Viswanathan Swaminathan.

  Proceedings of the 2020 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2020 (SIAM SDM).

• Scalable Bid Landscape Forecasting in Real-time Bidding

  Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Jason Xie, Gang Wu, and Viswanathan Swaminathan.

  Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, Cham, 2019 (ECML-PKDD).

• Generative Sequential Stochastic Model for Marked Point Processes

  Abhishek Sharma, Aritra Ghosh, and Madalina Fiterau.

  ICML Time Series Workshop. 2019.

• Robust Loss Functions for Deep Neural Networks

  Aritra Ghosh, Himanshu Kumar, and P. S. Sastry.

  Thirty-First AAAI Conference on Artificial Intelligence. 2017 (AAAI).

• On the Robustness of Decision Tree Learning Under Label Noise

  Aritra Ghosh, Naresh Manwani, and P. S. Sastry.

  Pacific-Asia Conference on Knowledge Discovery and Data Mining. Springer, Cham, 2017 (PAKDD).

• A Preference Approach to Reputation in Sponsored Search

  Aritra Ghosh, Dinesh Gaurav, and Rahul Agrawal.

  Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. ACM, 2016 (CIKM).

• Making Risk Minimization Tolerant to Label Noise

  Aritra Ghosh, Naresh Manwani, and P. S. Sastry.

  Neurocomputing 160 (2015): 93-107.

Service

• Program Committee Member: AAAI 2021, WACV 2021
• Conference Volunteer: ICML 2020, NeurIPS 2021