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
Awards
Skills
- Python, C, Java, C#, Matlab, R
- PyTorch, Tensorflow
Publications
- Do We Really Need Gold Samples for Sample Weighting under Label Noise?
- Aritra Ghosh, and Andrew Lan.
- Proceedings of the 2021 IEEE Winter Conference on Applications of Computer Vision, 2021 (WACV).
- Code
- Skill-based Career Path Modeling and Recommendation
- Aritra Ghosh, Beverly Woolf, Shlomo Zilberstein, and Andrew Lan.
- Proceedings of the 2020 IEEE International Conference on Big Data (Big Data), 2020 (IEEE BigData).
- Best Student Paper Award Code
- 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, KDD 2020, NeurIPS 2021