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

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]

Theses

Lifelong Machine Learning of Functionally Compositional Structures

Jorge Mendez-Mendez. University of Pennsylvania, 2022 [PDF]

Teaching

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

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

Testing Institute of America 2014 Annual Conference

Conference Proceeding talk 3 on Relevant Topic in Your Field, 2014

London School of Testing

Talk 2 on Relevant Topic in Your Field, 2014

UC-Berkeley Institute for Testing Science

Tutorial 1 on Relevant Topic in Your Field, 2013

UC San Francisco, Department of Testing

Talk 1 on Relevant Topic in Your Field, 2012

Service

Journal Article Reviewing

IJRR, International Journal of Robotics Research (2023)

Conference Paper Reviewing

NeurIPS Datasets and Benchmarks Track (2023)
ICLR, International Conference on Learning Representations (2021^*, 2022^*)
ICML, International Conference on Machine Learning (2021^*)
NeurIPS, Conference on Neural Information Processing Systems (2020, 2021^*, 2022)
ICRA / RA-L, International Conference on Robotics and Automation (2020, 2021, 2023)
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)

Jorge Mendez-Mendez

CV