Professor Alejandro Ribeiro
Welcome to the Artificial Intelligence (AI) Lab! My name is Alejandro Ribeiro (aribeiro@seas.upenn.edu) and I am very much looking forward to working with you in this course. I am grateful to my colleagues at Penn for allowing me the opportunity to teach it. I believe that we are reaching the point at which AI technologies can have a big impact in our society and it fills me with joy that I have the chance to contribute. You should ask me why I believe in the transformational power of AI in person. My belief rests in somewhat unexpected places that have little to do with what we hear in media.
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
Shervin Khalafi (shervink@seas.upenn.edu) got his BSc in Electrical Engineering from Sharif University of Technology in Tehran, Iran. Currently he is a third-year PhD student at the University of Pennsylvania where he is advised by Prof. Alejandro Ribeiro. His research interests include Generative Models, Optimization Theory, and graph-based Machine Learning. He is developing constrained optimization frameworks for training generative models (diffusion models in particular) under requirements. He is also studying generative diffusion models for Graphs.
Romina Garcia Camargo (rominag@seas.upenn.edu) is a graduate student advised by Dr. Alejandro Ribeiro at the University of Pennsylvania. Her interests are the areas of wireless systems and signal processing. She has also participated in various projects involving robot swarms.
She completed her undergraduate studies at Universidad de la República, in Montevideo, Uruguay. During the last three years of her degree, she was fortunate to work at her school’s Institute for Electrical Engineering. She worked as an assistant teacher for several courses within the topics of data networks and wireless communications. She also participated in various research projects as part of Grupo ARTES.
Antonio Pariente (pariente@seas.upenn.edu) Antonio Pariente is a second-year student at the University of Pennsylvania, advised by Prof. Alejandro Ribeiro. He earned a B.Sc. in Mathematics from the University of Valencia (not exempt from some suffering) and an M.Sc. in Data Science from the Polytechnic University of Catalonia (UPC). His research interests include optimization, machine learning, vector search, and metric geometry. Recently, he has focused on speeding up vector search through metric spaces. When he is not wrestling with distances and proofs, he enjoys actual wrestling.
Ignacio Boero (iboero@seas.upenn.edu) Ignacio received his B.Sc. in Electrical Engineering from the Universidad de la República in Montevideo, Uruguay. He is currently a second-year Ph.D. student at the University of Pennsylvania, advised by Prof. Alejandro Ribeiro. His research interests span optimization theory, generative models, and functional analysis. His current work focuses on extending theoretical guarantees for constrained learning problems and exploring their applications to generative models, particularly large language models (LLMs).
Teresa Shang (tshang@seas.upenn.edu) is a third year undergrad. Her research interests include transformers, language modeling, and image generation. She is from Shenyang, China, and she enjoys dancing, ice skating, and playing the flute.
Pedro Sánchez-Gil Galindo (pedrosan@seas.upenn.edu) Pedro is from Guadalajara, Mexico. He is majoring in Artificial Intelligence at Penn Engineering. His main involvements include Hack4Impact as external relations chair, Cursor campus lead, and working at edtech startup CultivatED. In his free time he enjoys lifting, biking and running.