Professor Alejandro Ribeiro
Welcome to the Graph Neural Networks (GNNs) course at Penn. My name is Alejandro Ribeiro (aribeiro@seas.upenn.edu) and I am very much looking forward to working with you. This course grew out of my research on GNNs and it is therefore very close to my personal interests. I believe that GNNs are a transformational technology that can have a high impact on the management of physical systems such as wireless communication networks, collaborative multiagent robotics and power distribution networks. GNNs will also impact a number of virtual world technologies such as recommendation systems. However, I am not a big fan of the virtual world and I don’t really care much about improving a recommendation system. I’d much rather we have better multiagent systems and power networks.
My research group is well known for its contributions to the fundamental understanding of AI information processing architectures. We try to determine what are the operations that we should perform on data to generate intelligent behavior and why do these operations should be expected to work or not. We are also active in developing theory and algorithms for learning with requirements. This has to do with developing AI systems that are good according to several metrics. They make, say, decisions that are within a specified range of optimal but are also fair and safe. Our application domains are multiagent autonomous systems, wireless communication networks, and network neuroscience.
I strive to be a good teacher and sometimes succeed. I am very proud to be the recipient of the 2012 S. Reid Warren, Jr. Award presented by the students of the School of Engineering and Applied Science for distinguished teaching and the 2017 Lindback award presented by my Penn colleagues for the same reason.
I also strive to be a good scientist and in this endeavor I am very much helped by the remarkable work of my doctoral students and postdocs. Their papers have received a number of awards which I am happy to claim as my own. These awards are the 2024 and 2022 IEEE Signal Processing Society Best Paper Award, the 2022 IEEE Brain Initiative Student Paper Award, the 2021 Cambridge Ring Publication of the Year Award, the 2020 Signal Processing Society young author pest paper award, the 2014 O. Hugo Schuck best paper award and paper awards at the 2023 Workshop on Computational Advances in Multi-Sensor Adaptive Processing, the 2021 European Signal Processing Conference, the 2020 International Conference on Acoustics, Speech and Signal Processing, the 2019 European Signal Processing Conference, the 2017 Conference on Decision and Control, the 2016 Workshop on Statistical Signal Processing, the 2016 Sensor Array, and Multichannel Signal Processing Workshop, the 2015 Asilomar Conference on Signals Systems and computers, the 2013 American Control Conference, and the 2005 and 2006 International Conferences on Acoustics, Speech, and Signal Processing. I have also been selected as a Fulbright Scholar class of 2003, a Penn Fellow class of 2015, and an Outstanding Researcher by Intel in 2019.
I am husband to Gabriela and father to Miranda (Penn Class of 2020), Guillermo(Penn Class of 2023), and Ariel (Penn Class of 2031, I hope).
If you think that I can ever be of assistance to you in the future, connect with my LinkedIn account.
Teaching Assistants
Javier Porras-Valenzuela (jporras@seas.upenn.edu) is a third year PhD. student advised by Prof. Alejandro Ribeiro. His research interests include graph neural networks, transformers, reinforcement learning and stochastic optimization. Originally from Heredia, Costa Rica, he holds a BSc. in Software Engineering from Universidad Nacional de Costa Rica (2015) and an MSc. in Computer Science from Tecnológico de Costa Rica (2022). He enjoys chess, hikes, and taking pictures in front of brick walls.
Frederic Vatnsdal (vatnsdal@seas.upenn.edu) is a third-year PhD student advised by Prof. Alejandro Ribeiro. His aim is to create swarm systems. He splits his time between learning control policies for swarm navigation and establishing the tooling necessary to deploy these policies in the real world. Before joining Alelab, he was a vehicle engineer at Nvidia. He obtained his BASc in Electrical Engineering from the University of Waterloo. Hobbies include climbing and woodworking.
Shreyas Muthusamy (muthurak@seas.upenn.edu) is a third-year undergraduate student majoring in electrical engineering and researching under Prof. Alejandro Ribeiro. He is interested in multi-agent robotics, reinforcement learning, and graph neural networks. He was born and raised in Richmond, Virginia, and in his free time, he likes to venture into Center City and dive into Wikipedia rabbit holes.
Indrani Paul Roy(ipaulroy@seas.upenn.edu) is a second-year Electrical Engineering master’s student researching under the guidance of Prof. Alejandro Ribeiro. Her research interests include neural signal processing, graph neural networks, and brain-computer interfaces. Born in Calcutta, India, she graduated from North-Eastern Hill University,Shillong(2023) with a B.Tech in Electronics and Communications Engineering. She moved to Philadelphia a year ago and enjoys going on hikes,solving puzzles,visiting museums and playing the piano in her free time.
Beiming Li (beimingl@seas.upenn.edu) is a second-year PhD student advised by Prof. Alejandro Ribeiro and Prof. Vijay Kumar. His research interests lie in developing reinforcement learning techniques that solve multi-agent cooperation and competition at scale. He obtained his B.S. in Computer Engineering from the University of Michigan. He enjoys cooking, sports, and taking pictures on top of cars.
Jiashu He (jiashuhe@seas.upenn.edu) is a fourth-year PhD in CIS advised by Professor Alejandro Ribeiro. He is interested in boosting reasoning ability of GenAI systems using human cognitive inspired approaches, such as combining retrieval and reasoning, reinforcement-learning advanced agentic frameworks, testing time scaling methods, etc. Before joining UPenn, he earned his B.S. in Mathematics and Computer Science from University of Illinois, Urbana-Champaign in 2022.