Atanu R Sinha

Principal Scientist


Atanu R Sinha is a Principal Scientist at Adobe Research, Bangalore. He received a Ph.D. from the Stern School of Business at the New York University. His Professorial career started at the Anderson School of Management, UCLA. He then moved to the Leeds School of Business, University of Colorado, Boulder, where he is an Emeritus. Foreseeing the impact of Machine Learning (ML), he switched to Adobe Research in 2016 from his tenured academic position. Since then, he has been working in different aspects of ML and AI. He has published in AAAI, CHI, CIKM, WSDM, ICDAR, ISMAR, Management Science, Marketing Science, Psychometrika, among others. His current primary research focus is user behavior modeling, where the user could be individuals, groups, or firms. Theoretical modeling of Mechanism Design and Designing Experimental Studies for Evaluation are other areas of current research. Learning from user behavior logs, he offers ML and AI methods to address new problems. Broadly, his research interests span theoretical and empirical modeling of consumer decision making, and firm decision making, by recognizing strategic behaviors of both consumers and firms, institutional practices, and behaviors laced with cognitive biases. The research draws from base disciplines of economics, game theory, statistics, and cognitive and social psychology. His expertise covers predictive user segmentation, cost conscious optimization of segmentation and channel delivery, customer experience measurement, two-sided platform markets, pricing, auctions, negotiations, social networks, coalitions and alliances, reward programs, new products, augmented reality, among others. He has taught courses at the PhD, MBA, MS and UG programs across University of Colorado, UCLA, Indian School of Business, Korea University, and Indian Institute of Management, Bangalore. He has offered executive programs across US, India, Germany, and Korea and had consulted with many large US companies, including tech companies. After completing Bachelors and Masters, pursuing Statistics and Mathematics, from the Indian Statistical Institute, he was instrumental in starting the market research function for Tata Motors (then, Telco).


Delivery Optimized Discovery in Behavioral User Segmentation under Budget Constraint

Chopra, H., Sinha, A., Choudhary, S., Rossi, R., Indela, P., Parwatala, V., Paul, S., Maiti, A. (Oct. 21, 2023)

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM)

The Role of Unattributed Behavior Logs in Predictive User Segmentation

Sinha, A., Chopra, H., Maiti, A., Ganesh, A., Kapoor, S., Myana, S., Mahapatra, S. (Oct. 21, 2023)

ACM International Conference on Information and Knowledge Management (CIKM)

DataPilot: Utilizing Quality and Usage Information for Subset Selection during Visual Data Preparation

Narechania, A., Du, F., Sinha, A., Rossi, R., Hoffswell, J., Guo, S., Koh, E., Navathe, S., Endert, A. (Apr. 23, 2023)

CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, April 2023

Personalized Detection of Cognitive Biases in Actions of Users from Their Logs: Anchoring and Recency Biases

Sinha, A., Goyal, N., Dhamnani, S., Asija, T., Dubey, R., Raja, M., Theocharous, G. (Feb. 13, 2023)

AAAI 2023 Workshop AI4BC: AI for Behavior Change

B2B Advertising: Joint Dynamic Scoring of Account and Users

Sinha, A., Choudhary, G., Agarwal, M., Bindal, S., Pande, A., Girabawe, C. (Aug. 15, 2022)

AdKDD '22: The 28th ACM SIGKDD Conference

Data-Sharing Economy: Value-Addition from Data meets Privacy

Bagad, P., Mitra, S., Dhamnani, S., Sinha, A., Gautam, R., Khanna, H. (Mar. 8, 2021)

WSDM '21: ACM International Conference on Web Search and Data Mining

Uncovering relations for marketing knowledge representation

Aditya, S., Sinha, A. (Feb. 7, 2020)

AAAI '20 Workshop StarAI

Mentor Pattern Identification from Product Usage Logs

Garg, A., Kharb, A., Malviya, Y., Sagar, J., Sinha, A., Burhanuddin, I., Choudhary, S. (Mar. 20, 2019)

23rd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD)

Surveys Without Questions: A Reinforcement Learning Approach

Sinha, A., Jain, D., Sheoran, N., Khosla, S., Sasidharan, R. (Jan. 27, 2019)

33rd AAAI Conference on Artificial Intelligence (AAAI)

Forecasting Granular Audience Size for Online Advertising

Sinha, R., Singal, D., Maneriker, P., Chawla, K., Shrivastava, Y., Pai, D., Sinha, A. (Aug. 19, 2018)

Workshop AdKDD & TargetAd, at 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Measurement of Users’ Experience on Online Platforms from Their Behavior Logs

Jain, D., Sinha, A., Gupta, D., Sheoran, N., Khosla, S. (Jun. 19, 2018)

Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)

Automatic Assignment of Topical Icons to Documents for Faster File Navigation

Roy, R., Singh, A., Chawla, P., Saxena, S., Sinha, A. (Nov. 13, 2017)

Document Analysis and Recognition (ICDAR), 2017 14th IAPR International Conference on (Vol. 1, pp. 1338-1345). IEEE.

[POSTER] Enhanced Personalized Targeting Using Augmented Reality

Hiranandani, G., Ayush, K., Varsha, C., Sinha, A., Maneriker, P., Maram, S. (Oct. 1, 2017)

Mixed and Augmented Reality (ISMAR-Adjunct), 2017 IEEE International Symposium on (pp. 69-74). IEEE.

Anti-Ad Blocking Strategy: Measuring Its True Impact

Sinha, A., Macha, M., Maneriker, P., Khosla, S., Samdariya, A., Singh, N. (Aug. 14, 2017)