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. (*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.
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
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
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.
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
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
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.
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
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.
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.