A Systematic Study of Large Language Models for Task and Motion Planning With PDDLStream
Jorge Mendez-Mendez. Preprint, 2025 [PDF]
CV
See the PDF version here.
Academic Appointments
- 2024-Present: Assistant Professor
- Electrical and Computer Engineering, Stony Brook University
- 2022-Present: Postdoctoral Fellow
- CSAIL, Massachusetts Institute of Technology
- Topics: compositionality, planning and learning, robotics, lifelong learning
- Supervisors: Tomas Lozano-Perez and Leslie Pack Kaelbling
- Summer 2022: Postdoctoral Researcher
- GRASP Lab, University of Pennsylvania
- Topics: lifelong learning, reinforcement learning, compositionality
- Supervisor: Eric Eaton
- 2016-2022: Research Assistant
- GRASP Lab, University of Pennsylvania
- Topics: lifelong learning, reinforcement learning, compositionality
- Supervisor: Eric Eaton
Education
- Ph.D. in Computer and Information Science, University of Pennsylvania, 2022
- M.S.E. in Robotics, University of Pennsylvania, 2018
- B.S. in Eletronics Engineering, Universidad Simon Bolivar (Venezuela), 2016
Honors and Awards
- Invited to Dagstuhl Seminar on Deep Continual Learning in the Foundation Model Era, 2025
- Early-Career Spotlight at the Conference on Lifelong Learning Agents, 2025
- MIT-IBM Distinguished Postdoctoral Fellowship, 2022-2024
- 3rd place award of the Two Sigma Diversity PhD Fellowship ($5,000), 2021
- Best paper award at the 4th Lifelong Learning Workshop at ICML for “Lifelong learning of factored policies via policy gradients”, 2020
- Outstanding reviewer or equivalent at ICLR, ICML, and NeurIPS, 2021-2022
- Exceptionally Good Thesis award at Universidad Simon Bolivar for “Implementation of algorithms and debugging for STMicroelectronics wearable platform”, 2016
- Top 30 GPAs at Universidad Simon Bolivar among students in the final two years, 2015-2016
- Top 10 GPAs at Universidad Simon Bolivar (3 / 750) among first-year students, 2011
- Top 50 entrance placement exams at Universidad Simon Bolivar (25 / 7409)
Other Research Appointments
- Summer 2021: Research Intern
- Facebook AI Research, NYC
- Topics: mixture of experts models
- Supervisor: Arthur Szlam and Ludovic Denoyer
- Summer 2020: Research Intern
- Microsoft Research, Montreal
- Topics: lifelong learning, reinforcement learning, compositionality
- Supervisor: Harm van Seijen
- Summer 2019: Research Intern
- Facebook AI
- Topics: conversational AI, reinforcement learning, multidomain learning
- Supervisor: Alborz Geramifard and Mohammad Ghavamzadeh
Publications
Preprints
Journal Articles
Improving Black-box Robustness with In-Context Rewriting
Kyle O'Brien and Nathan Hoyen Ng and Isha Puri and Jorge Mendez-Mendez and Hamid Palangi and Yoon Kim and Marzyeh Ghassemi and Thomas Hartvigsen. Transactions on Machine Learning Research (TMLR), 2024 [PDF]
How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition
Jorge Mendez-Mendez, Eric Eaton. Transactions on Machine Learning Research (TMLR), 2023 [PDF]
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Ese Ben-Iwhiwhu,,rew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik Learned-Miller, Seungwon Lee, Michael L. Littman, Sandeep Madireddy, Jorge Mendez-Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff,,rea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha. Neural Networks, 2023 [PDF]
Gap Minimization for Knowledge Sharing and Transfer
Boyu Wang, Jorge Mendez-Mendez, Changjian Shui, Fan Zhou, Di Wu, Xu, Gezheng, Christian Gagne, Eric Eaton. Journal on Machine Learning Research (JMLR), 2023 [PDF]
Conference Papers
Learning Long-Horizon Action Dependencies in Sampling-Based Bilevel Planning
Bartlomiej Cieslar, Leslie Kaelbling, Tomas Lozano-Perez, and Jorge Mendez-Mendez. Conference on Robot Learning (CoRL), 2024 [PDF]
Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning
Marcel Hussing*, Jorge Mendez-Mendez*, Anisha Singrodia, Cassandra Kent, Eric Eaton. Reinforcement Learning Conference (RLC), 2024 [PDF]
Embodied Lifelong Learning for Task and Motion Planning
Jorge Mendez-Mendez, Leslie Pack Kaelbling, Tomas Lozano-Perez. Conference on Robot Learning (CoRL), 2023 [PDF]
SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries
Meghna Gummadi, Cassandra Kent, Jorge Mendez-Mendez, Eric Eaton. Conference on Lifelong Learning Agents (CoLLAs), 2022 [PDF]
CompoSuite: A Compositional Reinforcement Learning Benchmark
Jorge Mendez-Mendez*, Marcel Hussing*, Meghna Gummadi, Eric Eaton. Conference on Lifelong Learning Agents (CoLLAs), 2022 [PDF]
Modular Lifelong Reinforcement Learning via Neural Composition
Jorge Mendez-Mendez, Harm van Seijen, Eric Eaton. International Conference on Learning Representations (ICLR), 2022 [PDF]
Lifelong Learning of Compositional Structures
Jorge Mendez-Mendez, Eric Eaton. International Conference on Learning Representations (ICLR), 2021 [PDF]
Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting
Jorge Mendez-Mendez, Boyu Wang, Eric Eaton. Advances in Neural Information Processing Systems (NeurIPS), 2020 [PDF]
Transfer Learning via Minimizing the Performance Gap Between Domains
Boyu Wang, Jorge Mendez-Mendez, Mingbo Cai, Eric Eaton. Advances in Neural Information Processing Systems (NeurIPS), 2019 [PDF]
Lifelong Inverse Reinforcement Learning
Jorge Mendez-Mendez, Shashank Shivkumar, Eric Eaton. Advances in Neural Information Processing Systems (NeurIPS), 2018 [PDF]
Workshop Papers
Continual Improvement of Threshold-Based Novelty Detection
Abe Ejilemele, Jorge Mendez-Mendez. CoLLAs Workshop Track, 2023 [PDF]
Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning
Marcel Hussing*, Jorge Mendez-Mendez*, Cassandra Kent, Eric Eaton. CoRL Workshop on Pre-training Robot Learning, 2022 [PDF]
Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings
Jorge Mendez-Mendez, Alborz Geramifard, Mohammad Ghavamzadeh, Bing Liu. 3rd Conversational AI Workshop at NeurIPS, 2019 [PDF]
Theses
Lifelong Machine Learning of Functionally Compositional Structures
Jorge Mendez-Mendez. University of Pennsylvania, 2022 [PDF]
Teaching
Stony Brook University
Artificial Intelligence for Robotics
Spring '25
InstructorDeep Learning Algorithms and Software
Fall '24
Instructor
University of Pennsylvania
Python Programming
Fall '19, Spring '20
InstructorIntroduction to Machine Learning
Fall '17
Head Teaching Assistant
Universidad Simon Bolivar
Programming I
Winter '16, Spring '14, Winter '14, Fall '14, Spring '13, Winter '13, Fall '13
Teaching AssistantElectric Circuit Analysis II
Spring '12
Teaching AssistantCalculus II
Winter '12
Teaching AssistantCalculus I
Fall '11
Teaching Assistant
Invited Talks
Conference on Lifelong Learning Agents
Unlocking Lifelong Robot Learning With Modularity (early-career spotlight), 2025
Workshop on Scalable Continual Learning for Lifelong Foundation Models at NeurIPS
Unlocking Lifelong Robot Learning With Modularity, 2024
Continual Causality Bridge at AAAI
Causal Models for Lifelong Robot Learning and Where to Find Them (position talk), 2024
Computer Science Seminar at Rutgers University
Unlocking Lifelong Robot Learning With Modularity, 2023
Forum for Artificial Intelligence at UT Austin
Unlocking Lifelong Robot Learning With Modularity, 2023
Machine Learning and Friends Lunch at UMass Amherst
Unlocking Lifelong Robot Learning With Modularity, 2023
Lifelong Robotics Workshop at IROS
Lifelong Robot Learning via Functional Compositionality, 2022
University of Western Ontario
Creating Versatile Learning Agents Via Lifelong Compositionality, 2022
Toyota Research Institute
Creating Versatile Learning Agents Via Lifelong Compositionality, 2022
Continual AI
Lifelong Learning of Compositional Structures, 2020
Service
Organization
- Tutorials Chair for Conference on Lifelong Learning Agents (2025)
- Finance and Sponsorship Co-Chair for LatinX in AI Workshop at NeurIPS (2022)
Journal Article Reviewing
- IJRR, International Journal of Robotics Research (2023)
Conference Paper Reviewing
- NeurIPS, Conference on Neural Information Processing Systems (2020, 2021*, 2022, 2024)
- ICRA / RA-L, International Conference on Robotics and Automation (2020, 2021, 2023)
- ICLR, International Conference on Learning Representations (2021*, 2022*, 2023, 2024, 2025)
- ICML, International Conference on Machine Learning (2021*, 2025)
- NeurIPS Datasets and Benchmarks Track (2023, 2024)
- CoRL, Conference on Robot Learning (2024, 2025)
- RLC, Reinforcement Learning Conference (2024)
- RSS, Robotics Science and Systems (2025)
- Conference paper co-reviewer:
- IJCAI, International Joint Conference on Artificial Intelligence (2017, 2018, 2019)
- ICML, International Conference on Machine Learning (2018)
- NeurIPS, Neural Information Processing Systems (2018)
- AAAI, Conference on Artificial Intelligence (2019)
*Outstanding reviewer
Workshop Proposal Reviewing
- AAAI, Conference on Artificial Intelligence (2021)
Workshop Paper Reviewing
- InterNLP Workshop at NeurIPS (2022)