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

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
Instructor

Deep Learning Algorithms and Software

Fall '24
Instructor

University of Pennsylvania

Python Programming

Fall '19, Spring '20
Instructor

Introduction 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 Assistant

Electric Circuit Analysis II

Spring '12
Teaching Assistant

Calculus II

Winter '12
Teaching Assistant

Calculus 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)