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Blanchard, Lancelot*, Perry Naseck*, Eran Egozy, and Joseph A. Paradiso. 2024. “Developing Symbiotic Virtuosity: AI-Augmented Musical Instruments and Their Use in Live Music Performances.” An MIT Exploration of Generative AI, September. https://doi.org/10.21428/e4baedd9.69c11de7.
Cherep*, M., Singh*, N., & Shand, J. (2024, July). Creative Text-to-Audio Generation via Synthesizer Programming. International Conference on Machine Learning (ICML)
Singh*, N., Cherep*, M., & Shand, J. (2023, December). Creative Text-to-Audio Generation via Synthesizer Programming. In NeurIPS Machine Learning for Audio Workshop
Lu, C.*, Yu, Y.*, Karimireddy, S. P., Jordan, M. I., & Raskar, R. (2023). Federated Conformal Predictors for Distributed Uncertainty Quantification. Fortieth International Conference on Machine Learning (ICML 2023)
Kumar, B.*, Lu, C.*, Gupta, G., Palepu, A., Bellamy, D., Raskar, R., & Beam, A. "Conformal Prediction with Large Language Models for Multi-Choice Question Answering." Neural Conversational AI Workshop at ICML 2023.
Kim, J., Marcus, C., Ono, R., Sadat, D., Mirzazadeh, A., Jens, M., Fernandez S. V., Zheng, S., Durak, T., Dagdeviren, C.†, “Conformable Multimodal Sensory Facemask for Decoding Biological and Environmental Signals”, Nature Electronics, 5, 794–807, 2022. [Cover Image]
Katija, K., Orenstein, E., Schlining, B. et al. FathomNet: A global image database for enabling artificial intelligence in the ocean. Sci Rep 12, 15914 (2022). https://doi.org/10.1038/s41598-022-19939-2
Image2Reverb: Cross-Modal Reverb Impulse Response Synthesis. Nikhil Singh, Jeff Mentch, Jerry Ng, Matthew Beveridge, Iddo Drori; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 286-295
Boroushaki, Tara, et al. "Robotic Grasping of Fully-Occluded Objects using RF Perception." IEEE International Conference on Robotics and Automation (ICRA 2021).
Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Xiao Zeng, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Xinghua Zhu, Jianzong Wang, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram and Salman Avestimehr. "FedML: A Research Library and Benchmark for Federated Machine Learning." NeurIPS-SpicyFL 2020. (Baidu Best Paper Award)
Narain, J.*, Johnson, K.T.*, Ferguson, C., O’Brien, A., Talkar, T., Zhang, Y., Wofford, P., Quatieri, T., Picard, R.W.,Maes, P., "Personalized Modeling of Real-World Vocalizations from Nonverbal Individuals," Proceedings of the International Conference on Multimodal Interaction (ICMI), Utrecht, Netherlands, October 2020. (*Co-first authors/Equal contribution)
@misc{sarawgi2020uncertaintyaware, title={Uncertainty-Aware Multi-Modal Ensembling for Severity Prediction of Alzheimer's Dementia}, author={Utkarsh Sarawgi and Wazeer Zulfikar and Rishab Khincha and Pattie Maes}, year={2020}, eprint={2010.01440}, archivePrefix={arXiv}, primaryClass={cs.LG} }
@misc{sarawgi2020unified, title={Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles}, author={Utkarsh Sarawgi and Wazeer Zulfikar and Rishab Khincha and Pattie Maes}, year={2020}, eprint={2009.12406}, archivePrefix={arXiv}, primaryClass={cs.LG} }
@article{sarawgi2020multimodal, title={Multimodal Inductive Transfer Learning for Detection of Alzheimer's Dementia and its Severity}, author={Sarawgi, Utkarsh and Zulfikar, Wazeer and Soliman, Nouran and Maes, Pattie}, journal={arXiv preprint arXiv:2009.00700}, year={2020} }
Vepakomma, P., Balla, J., Raskar, R., "Splintering with distributions: A stochastic decoy scheme for private computation." 6 Jul 2020.
Jones, Noah. Prediction and Analysis of Degree of Suicidal Ideation in Online Content. 2020. MIT, SM Thesis.
Taylor, Sara. Forecasting Mental Distress using Healthcare Claims Data. 2020. MIT, PhD dissertation.
Nosakhare, E., and Picard. R. 2019. Toward Assessing and Recommending Combinations of Behaviors for Improving Health and Well-Being. ACM Trans. Comput. Healthcare 1, 1, Article 4 (December 2019), 29 pages.
Narain, J.*, Johnson, K.T.*, Picard, R.W., Maes, P. "Zero-Shot Transfer Learning to Enhance Communication for Minimally Verbal Individuals with Autism using Naturalistic Data," NeurIPS Workshop on AI for Social Good, December 2019. (*Co-first authors/Equal contribution)
Ghandeharioun, A., Eoff, B., Jou, B., & Picard, R. W. (2019). Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias. arXiv preprint arXiv:1909.09285.
Rudovic, O., Zhang, M, Schuller, B., Picard, R. "Multi-modal Active Learning From Human Data: A Deep Reinforcement Learning Approach", In 2019 International Conference on Multimodal Interaction (ICMI ’19), October 14–18, 2019, Suzhou, China. ACM, New York, NY, USA.
Nosakhare, E., Picard, R. W. Probabilistic Latent Variable Modeling for Assessing Behavioral Influences on Well-Being," ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19), August 4–8, 2019, Anchorage, AK, USA. ACM, New York, NY, USA. https://doi.org/10.1145/3292500.3330738
Doorley, Ronan & Noyman, Ariel & Sakai, Yasushi & Larson, Kent. (2019). What's your MoCho? Real-time Mode Choice Prediction Using Discrete Choice Models and a HCI Platform. UrbComp SIGKDD 2019
Diverse data selection via combinatorial quasi-concavity of distance covariance: A polynomial time global minimax algorithm, Praneeth Vepakomma, Yulia Kempner
Umematsu, T., Sano, A., Taylor, S., and Picard, R. "Improving Students' Daily Life Stress Forecasting using LSTM Neural Networks." IEEE International Conference on Biomedical and Health Informatics (BHI), Chicago, Illinois, May 2019. (BEST PAPER AWARD - 1st Prize)
Rahwan, Iyad, Manuel Cebrian, Nick Obradovich, Josh Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W. Crandall, et al. “Machine Behaviour.” Nature 568, no. 7753 (April 2019): 477. https://doi.org/10.1038/s41586-019-1138-y.
Aman Rana, Yauney G, Lowe A, Shah P. IEEE Xplore, Proceedings of 17th International Conference on Machine Learning and Applications (2018) (Conference acceptance rate: 14%). DOI: 10.1109/ICMLA.2018.00133
Perikumar Javia, Rana A, Shapiro NI, Shah P. IEEE Xplore, Proceedings of 17th International Conference on Machine Learning and Applications (2018) (Conference acceptance rate: 14%). DOI: 10.1109/ICMLA.2018.00097
Noriega-Campero, A., Bakker, M., Garcia-Bulle, B., & Pentland, A. (2018). Active Fairness in Algorithmic Decision Making. arXiv preprint arXiv:1810.00031.
Rudovic, O., Utsumi, Y., Lee, J., Hernandez, J., Castello Ferrer, E., Schuller, B., Picard, R. "CultureNet: A Deep Learning Approach for Engagement Intensity Estimation from Face Images of Children with Autism." IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018).
Feffer, M., Rudovic, O., Picard, R. "A Mixture of Personalized Experts for Human Affect Estimation." The 14th International Conference on Machine Learning and Data Mining (MLDM). July 2018.
Rudovic, O., Lee, J., Dai, M., Schuller, B. , Picard, R. W., " Personalized machine learning for robot perception of affect and engagement in autism therapy," Science Robotics, June 2018.
Jaques, N., Engel, J., Ha, D., Bertsch, F., Picard, R., and Eck, D. "Learning via social awareness: improving sketch representations with facial feedback." International Conference on Learning Representations (ICLR) Workshop, Vancouver, Canada, April 2018.
Eduardo Castello Ferrer, Ognjen Rudovic, Thomas Hardjono, Alex Pentland, “RoboChain: A Secure Data-Sharing Framework for Human-Robot Interaction” eTELEMED 2018.
Taylor, S.*, Jaques, N.*, Nosakhare, E., Sano, A. and Picard, R., "Personalized Multitask Learning for Predicting Tomorrow's Mood, Stress, and Health," in IEEE Transactions on Affective Computing, vol. PP, no. 99, pp. 1-1. doi: 10.1109/TAFFC.2017.2784832 *Both authors contributed equally. WINNER: BEST OF COLLECTION
A. Rana, G. Yauney, L. C. Wong, O. Gupta, A. Muftu, P. Shah. IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT). IEEE (2017). DOI: 10.1109/HIC.2017.8227605
Jaques, N., Taylor, S., Sano, A., and Picard, R. International Conference on Affective Computing and Intelligent Interaction (ACII), San Antonio, Texas, October 2017
G. Yauney, K. Angelino, D. A. Edlund, P. Shah. IEEE 17th International Conference on Bioinformatics and Bioengineering (2017). DOI: 10.1109/BIBE.2017.00-37
Ritesh Noothigattu, Snehalkumar 'Neil' S. Gaikwad, Edmond Awad, Sohan Dsouza, Iyad Rahwan, Pradeep Ravikumar, Ariel D. Procaccia AAAI 2018: Association for the Advancement of Artificial Intelligence (Acceptance rate of 24.6%)
Zhang, Yan. “CityMatrix – An Urban Decision Support System Augmented by Artificial Intelligence.” Massachusetts Institute of Technology, 2017.
Jaques, N., Rudovic, O., Taylor, S., Sano, A., and Picard, R. Proceedings of Machine Learning Research, 48, 17-33. August 2017.
Guy Satat, Matthew Tancik, Otkrist Gupta, Barmak Heshmat, and Ramesh Raskar, "Object classification through scattering media with deep learning on time resolved measurement," Opt. Express 25, 17466-17479 (2017)
Taylor, S., Jaques, N., Nosakhare, E., Sano, A., Klerman, E., and Picard, R. "Importance of Sleep Data in Predicting Next-Day Stress, Happiness, and Health in College Students," Sleep2017, June 2017.
Jin Joo Lee. A Bayesian Theory of Mind Approach to Nonverbal Communication for Human-Robot Interactions. PhD Thesis, Massachusetts Institute of Technology, 2017.
Jaquesn, N., Gu, S., Turner, R., and Eck, D. International Conference on Learning Representations (ICLR) workshop, Toulon, France, April 2017
Tan, Flora. Algorithmically Supported Moderation in Children’s Online Communities. Thesis. Massachusetts Institute of Technology, 2017.
Jaques, N., Taylor, S., Nosakhare, E., Sano, A., Picard, R. In Proc. NIPS Workshop on ML in Health, Barcelona, Spain, December 2016. **BEST PAPER AWARD**
JJ Lee, WB Knox, JB Wormwood, C Breazeal, D DeSteno (2013). Computationally Modeling Interpersonal Trust. Frontiers in Psychology.
Jin Joo Lee. Modeling the Dynamics of Nonverbal Behavior on Interpersonal Trust for Human-Robot Interactions. Masters Thesis, Massachusetts Institute of Technology, 2011.