| Biases in AI systems R Srinivasan, A Chander Communications of the ACM 64 (8), 44-49, 2021 | 107 | 2021 |
| Biases in generative art: A causal look from the lens of art history R Srinivasan, K Uchino Proceedings of the 2021 ACM Conference on Fairness, Accountability, and …, 2021 | 74 | 2021 |
| Working with beliefs: AI transparency in the enterprise. A Chander, R Srinivasan, S Chelian, J Wang, K Uchino IUI Workshops 1, 2018 | 74 | 2018 |
| Explanation perspectives from the cognitive sciences—A survey R Srinivasan, A Chander Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 46 | 2021 |
| Computerized face recognition in renaissance portrait art: A quantitative measure for identifying uncertain subjects in ancient portraits R Srinivasan, C Rudolph, AK Roy-Chowdhury IEEE Signal Processing Magazine 32 (4), 85-94, 2015 | 36 | 2015 |
| The role of empathy for artificial intelligence accountability R Srinivasan, BSM González Journal of Responsible Technology 9, 100021, 2022 | 27 | 2022 |
| Evaluating explanations by cognitive value A Chander, R Srinivasan Machine Learning and Knowledge Extraction: Second IFIP TC 5, TC 8/WG 8.4, 8 …, 2018 | 21 | 2018 |
| Generating user-friendly explanations for loan denials using gans R Srinivasan, A Chander, P Pezeshkpour arXiv preprint arXiv:1906.10244, 2019 | 18 | 2019 |
| Artsheets for art datasets R Srinivasan, E Denton, J Famularo, N Rostamzadeh, F Diaz, B Coleman Thirty-fifth conference on neural information processing systems datasets …, 2021 | 16 | 2021 |
| Textual emotion detection RM Srinivasan, A Chander US Patent 9,864,743, 2018 | 10 | 2018 |
| Faces: Faces, art, and computerized evaluation systems–a feasibility study of the application of face recognition technology to works of portrait C Rudolph, AR Chowdhury, R Srinivasan, J Kohl Artibus et historiae: an art anthology, 265-291, 2017 | 10 | 2017 |
| The Role of Arts in Shaping AI Ethics Ramya Srinivasan, Kanji Uchino Workshop on Reframing Diversity in AI: Representation, Inclusion and Power …, 2021 | 8* | 2021 |
| Crowdsourcing in the Absence of Ground Truth--A Case Study R Srinivasan, A Chander arXiv preprint arXiv:1906.07254, 2019 | 8 | 2019 |
| Recognizing the royals: Leveraging computerized face recognition for identifying subjects in ancient artworks R Srinivasan, A Roy-Chowdhury, C Rudolph, J Kohl Proceedings of the 21st ACM international conference on Multimedia, 581-584, 2013 | 8 | 2013 |
| Creation of user friendly datasets: Insights from a case study concerning explanations of loan denials A Chander, R Srinivasan arXiv preprint arXiv:1906.04643, 2019 | 7 | 2019 |
| Quantifying Confounding Bias in Generative Art: A Case Study R Srinivasan, K Uchino arXiv preprint arXiv:2102.11957, 2021 | 6 | 2021 |
| Active learning source code review framework RM Srinivasan, A Chander US Patent App. 15/468,065, 2018 | 6 | 2018 |
| Forecasting worker aptitude using a machine learning collective matrix factorization framework RM Srinivasan, JG Jetcheva, A Chander US Patent App. 15/387,605, 2018 | 6 | 2018 |
| Face recognition based on SIGMA sets of image features R Srinivasan, A Nagar, A Tewari, D Mitrani, A Roy-Chowdhury 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 6 | 2014 |
| Quantitative modeling of artist styles in Renaissance face portraiture R Srinivasan, A Roy-Chowdhury, C Rudolph, J Kohl Proceedings of the 2nd International Workshop on Historical Document Imaging …, 2013 | 6 | 2013 |
