Yisong Yue (he/him)
California Institute of Technology
1200 E. California Blvd.
CMS, 305-16
Pasadena, CA 91125

Office: 303 Annenberg

Contact Information >

• Neurosymbolic Programming Survey Paper: published in Foundations and Trends in Programming Languages. (Non-paywalled version will be widely available in June 2022 -- I may be able to accommodate individual requests in the meantime.)
• Best Paper Award: "End-to-End Sequential Sampling and Reconstruction for MR Imaging" won Best Paper at ML4Health 2021! [project]
  
• Invited Talk: I presented on Neurosymbolic Programming at the Caltech Explainable AI Virtual Workshop. [slides]
  
• Advances in Machine Learning-Assisted Directed Evolution for Protein Design: new paper showing that smart training set selection can significantly improve machine learning-guided directed evolution in highly epistatic protein fitness landscapes with large low-fitness regions. [online][bioRxiv][code]
  
• Personalized Preference Learning from Spinal Cord Stimulation to Exoskeletons: interactive learning approaches for personalizing medical assistive devices. [slides]
  
• Fine-Grained Identification of Biological Neural Networks: our KDD 2021 paper on "Fine-Grained System Identification of Nonlinear Neural Circuits" demonstrated identifying sparse nonlinear neural networks from real neural recording data. [arxiv][code]
  
• Multi-Agent Behavior Workshop: Video recordings from our Multi-Agent Behavior Workshop (co-located with CVPR 2021) are now available. [playlist]
  
• Bon Voyage! We have four departures in the 2020-2021 academic year:
  • Ellen Novoseller completed her PhD and has started as a postdoc in Ken Goldberg's group at UC Berkeley.
  • Angie Liu completed her postdoc and will start as an assistant professor at Johns Hopkins University.
  • Joe Marino completed his PhD and will start as a research scientist at DeepMind.
  • Jialin Song completed his PhD and has started as a research scientist at NVIDIA AI.
  
• Paper Award: Our work on Task Programming won Best Student Paper at CVPR 2021! [arxiv][code][project]
  
• AI for Science Challenge: We have released the Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions. [arxiv][dataset][code]
  
• Invited Talk: Video now available of my talk on "Learning to Optimize as Policy Learning" presented at the Princeton Optimization Seminar. [slides]
  
• Invited Talk: I presented on "Learning for Safety-Critical Control in Dynamical Systems" at the Control Meets Learning seminar series.
  
• Invited Talk: I gave the Earnest C. Watson Lecture on January 13th, 2021.
  
• Invited Talk: I gave a presentation on AI for Adaptive Experiment Design at the Directions in ML: AutoML and Automating Algorithms hosted by Microsoft Research. [slides]
  
• Neural-Swarm2: we have released the details of our heterogeneous neural swarm approach! [paper]
  
• Invited Talk: I am presenting on "Competitive Algorithms for Online Control" at the Simons Institute Workshop on Mathematics of Online Decision Making. [slides]
  
• Invited Talk: I am presenting at the Workshop on Imitation Learning: Single & Multi-Agent hosted by DAI 2020. [slides]
• Invited Talk: I am presenting on "Learning to Optimize as Policy Learning" at the Princeton Optimization Seminar. [slides]
• ML for Rover Path Planning: check out this video of our MLNav extension of ENav (the path planner currently on the Mars Perseverance Rover). [arxiv]
  
• NSF Expeditions on Program Learning: we are starting a new research initiative titled Understanding the World Through Code, funded through the NSF Expeditions in Computing Program.
• Controllable Generation of Behaviors: we designed a new method that can generate behaviors calibrated to many different styles. [paper][code][demo]
  
• AI for Swarm Automation: check out this new article titled Machine Learning Helps Robot Swarms Coordinate. [paper 1][paper 2] (videos below)
  
• Invited Talk: I gave a talk on "Learning for Safety-Critical Control in Dynamical Systems" in the Physics ∩ ML seminar. [slides] (video below)
  
• Best Paper Award: Our work on preference learning for exoskeleton gait optimization is appearing at ICRA 2020 with a Best Paper Award! [arxiv][project] (video below).
  
• Partnered with PyTorch to film a short clip on our robotics research at CAST.
  
• Invited Talk: I am giving a talk at University of Chicago on November 13th, 2019.
• Invited Talk: I am giving a talk at the UIUC Computer Science Colloquium on November 11th, 2019.
• Keynote talk at AI-for-Science: I am giving a keynote talk on Adaptive Experiment Design at the Caltech AI-for-Science workshop.
  
• Invited Talk: I am speaking at the PyTorch Developer Conference on October 10th, 2019.
  
• Invited Workshop: I am giving a talk at the Workshop on Automated Algorithm Design hosted by the TTI-Chicago 2019 Summer Workshop Program.
• Invited Workshop: I am giving a talk at the Workshop on Data Collection, Curation, and Labeling for Mining and Learning co-located with KDD 2019.
• Invited Workshop: I am giving a talk at the Adversarial Machine Learning in Real-World Computer Vision Systems co-located with CVPR 2019.
• Invited Workshop: I am giving a talk at the 2019 Workshop on Human In the Loop Learning (HILL) co-located with ICML 2019 [video].
• ICML 2019 Workshop: Please consider attending or submitting to the Real-World Sequential Decision Making Workshop co-located with ICML 2019!
• Simons Symposium: I am attending a Simons Symposium on New Directions in Theoretical Machine Learning on May 5-11, 2019.
• Invited Talk: I am speaking at the Machine Learning Seminar at CMU on April 23rd, 2019.
• Neural Lander: Our work on deep learning for provably stable drone landing control is appearing at ICRA 2019! [arxiv] (video below)
  
• Earthquake Early Detection: State-of-the-art results on earthquake early detection using deep learning! [arxiv]
• Earthquake Localization: State-of-the-art results on earthquake localization using deep learning! [arxiv]
• Invited Workshop: I am presenting at the NeurIPS 2018 workshop on Imitation Learning and its Challenges in Robotics.
• Invited Talk: I am presenting at UCLA on November 20th, 2018.
• Invited Talk: I am presenting at the University of Maryland College Park on October 24th, 2018.
• Invited Talk: I am presenting at Microsoft Research Redmond on October 3rd & 4th, 2018.
• Invited Talk: I am presenting at the University of Washington AI Seminar on October 2nd, 2018.
• Invited Talk: I am presenting at the Rice Computer Science Colloquium on September 27th, 2018.
• Okawa Award: I recently received the Okawa Foundation Research Grant.
• Invited Workshop: I am presenting on Inference+Imitation at the Tractable Probabilistic Models workshop at ICML 2018.
• Invited Workshop: I am presenting on Machine Teaching for Human Learners at the Humanizing AI workshop at IJCAI 2018.
• Tutorial: I am giving a tutorial on imitation learning with Hoang Le at ICML 2018. (video below)
  
• Invited Talk: I am presenting at the Intel AI DevCon. (video below)
  
• Invited Talk: Invited talk at UT Austin AI Seminar on March 30th, 2018.
• Invited Workshop: I am attending the Data-driven Algorithmics workshop on November 5-10, 2017.
• Invited Talk: Invited talk at Southern California Machine Learning Symposium on October 6th, 2017.
• Blog Article: Our paper on smooth imitation learning was covered in an invited blog article titled Beyond Deep Learning: a Case Study in Sports Analytics. [ICML paper]
• Invited Talk: Invited talk at Microsoft Research Colloquium at MSR New England on September 6th, 2017. [video]
• Dagstuhl Seminar: I am attending the Machine Learning and Formal Methods Dagstuhl Seminar on August 28th - September 1st, 2017.
• Press Release: Our work on data-driven speech animation is highlighted on Road to VR! [SIGGRAPH paper][demo video (shown below)]
  
• Press Release & Interview: Neural Networks Model Audience Reactions to Movies, also radio interview. [CVPR paper]
• Microsoft Faculty Summit: I am attending the Edge of AI Microsoft Research Faculty Summit on July 17-18, 2017.
• Invited Talk: Invited talk at Machine Learning Methods for Recommender Systems Workshop to be held at SDM 2017.
• Invited talk: Invited talk at Symposium on Machine Learning and Human Behavior to be held at UC Irvine on March 10th, 2017.
• Best Paper Runner Up: Our paper "Data-Driven Ghosting using Deep Imitation Learning" wins Runner Up to Best Research Paper at the MIT Sloan Sports Analytics Conferece! [pdf][project][press release][demo video (shown below)]
  
• Caltech Computes Alumni College: I gave a talk titled Automatically Improving Automation using Big Data at the Caltech Computes Alumni College.
  
• Southern California Machine Learning Symposium: I am co-organizing the next SoCal ML Symposium, to be held at Caltech on November 18th, 2016.
• Innovation in Artificial Intelligence: I will be moderating a discussion panel on Innovation in Artificial Intelligence on September 15th, 2016.
• Coverage on Sports Illustrated: My collaboration with Disney Research on imitation learning for camera control is featured on Sports Illustrated! [ICML paper][CVPR paper]
• Bloomberg Data Science Research Grant: I'm delighted to be awarded a Data Science Research Grant from Bloomberg Labs!
• Personalization Workshop: Please consider participating in our Computational Frameworks for Personalization Workshop being held at ICML 2016!
• Sports Analytics Workshop: Please consider participating in our Large-Scale Sports Analytics Workshop being held at KDD 2016!
• Blog Post: Thoughts on NeurIPS 2015 and OpenAI.
• Invited Workshop: Algorithms for Human Robot Interaction Workshop.
• Blog Post: Thoughts on KDD 2015.
• Fundraising Chair of AISTATS 2016.
• Invited Talk at Reflections | Projections 2015 organized by ACM@UIUC.
• Invited Workshop: Data-driven Algorithmics Workshop. [slides]
• A Decision Tree Framework for Spatiotemporal Sequence Prediction accepted for publication at KDD 2015. [pdf][demo]
• Sports Analytics Workshop: Please consider participating in our Large-Scale Sports Analytics Workshop being held at KDD 2015!
• Interview by Jessica Stoller-Conrad @Caltech. [link]
• Invited Talk at Human Propelled Machine Learning Workshop at NeurIPS 2014.
• Learning Fine-Grained Spatial Models for Dynamic Sports Play Prediction accepted for publication at ICDM 2014. [pdf][demo][press release]
• Personalization Workshop: Please consider participating in our Personalization Workshop being held at NeurIPS 2014!
• Sports Analytics Workshop: Please consider participating in our Large-Scale Sports Analytics Workshop being held at KDD 2014!
• Personalized Collaborative Clustering accepted for publication at WWW 2014. [pdf][slides][data]
• Invited Talk at DISCML Workshop at NeurIPS 2013.
• Press release of EMS ambulance allocation project with the iLab is now up! [link][research paper]
• Invited talk at WSCD Workshop at WSDM 2012.