Milind Tambe

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Milind Tambe

Short bio for external seminars: Milind Tambe is Gordon McKay Professor of Computer Science and Director of Center for Research on Computation and Society at Harvard University; concurrently, he is also Principal Scientist and Director for “AI for Social Good” at Google Deepmind. Prof. Tambe and his team have developed pioneering AI systems that deliver real-world impact in public health (e.g., maternal and child health), public safety, and wildlife conservation. He is recipient of the AAAI Award for Artificial Intelligence for the Benefit of Humanity, AAAI Feigenbaum Prize, IJCAI John McCarthy Award, AAAI Robert S. Engelmore Memorial Lecture Award, AAMAS ACM Autonomous Agents Research Award, INFORMS Wagner prize for excellence in Operations Research practice, Military Operations Research Society Rist Prize, Columbus Fellowship Foundation Homeland security award and commendations and certificates of appreciation from the US Coast Guard, the Federal Air Marshals Service and airport police at the city of Los Angeles. He is a fellow of AAAI and ACM.

milind_tambe@harvard.edu

Prof. Tambe’s CV

Teamcore Group Home

Bio, Research and Awards

Longer bio:

Milind Tambe is Gordon McKay Professor of Computer Science and Director of Center for Research on Computation and Society at Harvard University. Concurrently, he is also Principal Scientist and Director for “AI for Social Good” at Google Deepmind. Prof. Tambe and his team have developed pioneering AI systems that deliver real-world impact in public health (e.g., maternal and child health), public safety, and wildlife conservation.

Prof. Tambe is recipient of the AAAI (Association for Advancement of AI) Award for Artificial Intelligence for the Benefit of Humanity, AAAI Feigenbaum Prize, IJCAI (International Joint Conference on AI) John McCarthy Award, AAAI Robert S. Engelmore Memorial Lecture Award, AAMAS ACM (Association for Computing Machinery) Autonomous Agents Research Award, INFORMS ( Institute for Operations Research and the Management Sciences) Wagner prize for excellence in Operations Research practice and MORS (Military Operations Research Society) Rist Prize for best implemented national security operations research study . He is a fellow of AAAI and ACM. For his work on AI and public safety, he has received Columbus Fellowship Foundation Homeland security award and commendations and certificates of appreciation from the US Coast Guard, the Federal Air Marshals Service and airport police at the city of Los Angeles.

Prof. Tambe and coauthors have received 17 best paper awards at conferences such as AAAI, AAMAS, IJCAI, and others; this includes his 1997 paper “Towards flexible teamwork” in the Journal of AI Research that won the AAMAS influential paper award (an award given out 10 years after publication of a paper). His other prior awards include the Okawa foundation award, RoboCup Scientific challenge award and the IBM faculty award.

Prior to Harvard, Prof. Tambe was the Helen N and Emmett H Jones Professor in Engineering at the University of Southern California (USC), where he was awarded the USC associates award for creativity in research, “the highest honors the university faculty can bestow on its members for distinguished intellectual and artistic achievements”, the inaugural USC Viterbi School of Engineering Use-inspired research award, and the Steven B. Sample teaching and mentoring award “only faculty recognition award that is initiated by USC parents and family members”.

Prof. Tambe completed his PhD from the School of Computer Science at Carnegie Mellon University. Prior to that, he completed his undergraduate education at BITS, Pilani, India, where he was awarded Distinguished Alumnus Award.

Prof. Tambe Research

Prof. Tambe and his team’s work focuses on advancing AI and multiagent systems for public health, conservation & public safety, with a track record of building pioneering AI systems for social impact. In so doing, this research has often provided the first very uses of key multiagent systems models and algorithms in the real world and and is now exploring new paradigms with large language models (LLMs) to accelerate the AI for social impact process. Some major example projects include the following:

AI for Public Health (2013 – now)

AI for maternal and child care: Prof. Tambe and team were the first to deploy restless bandit algorithms for public health, specifically for maternal and child care. Prof. Tambe and team have been collaborating with the NGO ARMMAN in India since 2019; ARMMAN focuses on maternal and child care in India, working with 40 Million beneficiaries. Prof. Tambe’s work with ARMMAN is focused on the world’s two largest mobile health programs for maternal and child care: a region program based in Mumbai (mMitra) and a pan India program (Kilkari). A key challenge is that beneficiaries/mothers drop out of these healthcare information programs.

For the regional mMitra program, Prof. Tambe and team used restless bandits in this large scale public health settings to show a more than 30% reduction in drop out rate. The system has been deployed in the field with ARMMAN since April 2022. Over 350,000 mothers have been assisted by this system in deployment, and it has boosted the engagement, more than doubling the engagement of the bottom 25% of listners with the health information. It has also brought on several health benefits for the mothers. This work was conducted in part at Google Deepmind, India.

At Google Deepmind India, Prof. Tambe and team are now collaborating with ARMMAN to assist them with their work on Kilkari, a pan-India program of India’s Ministry of Health and Family Welfare, focused on maternal and child care. Kilkari is one of the largest mobile health programs in the world with 10 Million beneficiaries registered at a time. Initial field trials with Kilkari, using collaborative bandits, have also shown improved engagement with the program.

AI for HIV prevention: Prior to this work with ARMMAN, Prof. Tambe and his team also provided the first large scale applications of social network algorithms for public health. Conducted In collaboration with social work researchers, their pioneering large-scale field study focused on spreading HIV prevention information among youth experiencing homelessness (YEH). This project started in 2013 and provided the first empirical results (with 750 YEH in in Los Angeles) demonstrating the use of AI-guided interventions that led to significant reductions in HIV risk behaviors compared to traditional methods.

AI for Conservation (2013 – now)

AI for protecting endangered wildlife: Prof. Tambe and team were the first to apply AI models, specifically machine learning and game theory, for global scale anti-poaching efforts, as part of the PAWS project for wildlife conservation. The PAWS project was initiated in 2013 and has been extremely effective in predicting poaching activities and recommending patrols against them. Prof. Tambe and team’s decade-long collaboration on PAWS with NGOs has resulted in removing tens of thousands of snares set to trap endangered animals, in Uganda and Cambodia. For example, this work led to a 5-fold increase in snare removals in Cambodia.

The SMART partnership – a collaboration of major conservation agencies — has begun deploying PAWS in 800 wildlife parks internationally, bringing AI to the fight to save the lives of endangered animals all around the globe.PAWS was listed as “Top Tech” of 2018 by IEEE spectrum.

AI for public Safety (2006-2018)

AI for optimizing security operations for counter-terrorism: Prof. Tambe and team provided the first ever applications of computational game theory for operational security. The first of these deployments was the ARMOR system of game theoretic algorithms for security (e.g., counter terrorism) which started operating at the Los Angeles LAX airport in 2007. This is one of the largest and busiest airports in the United States that serves 80 Million passengers, where ARMOR’s security games provided day-to-day randomized schedules for checkpoints and canine patrols for over 10 years. This research was followed by pioneering deployments of security games used by major security agencies, including the US Coast Guard to generate patrols in ports such as New York and Boston since 2011, the US Federal Air Marshals for scheduling air marshals on US air carriers international flights since 2009 and others. This research is credited with more than $100M in savings to US agencies.

The LAX airport police, the Federal Air Marshals Service, and the US Coast Guard, have testified in United States Congress committee hearings on three separate occasions, about the utility of security games-based software for improving public safety & security (2008, 2012, 2013). See also Teamcore group home page. Since 2017, the focus of Teamcore group’s security games research has shifted to AI for conservation.

Prof. Tambe’s research has also focused on fueling and energizing the “AI for social good” ecosystem around the globe. To that end, he and his team at Google Research have started dozens of “AI for social good” projects by matchmaking AI researchers with non-profits; this includes recent kick-off of 30 new projects across 17 countries. These new projects build on earlier successes at Google Research discussed in this blog post.

Future Directions: A key focus of current research is on accelerating the AI for social impact pipeline through the use of large language models (LLMs). This work aims to leverage LLMs to automate key development stages, from problem formulation to solution deployment, ultimately enabling faster and more scalable creation of AI tools for addressing societal challenges.

Previous Research on Multiagent Systems (before 2007)

Prior to this focused work on “AI for social good”, Prof Tambe’s early research provided foundational models of multiagent teamwork. In addition to his JAIR 1997 paper “Towards flexible teamwork” that won the AAMAS influential paper award, Tambe and collaborators also contributed foundational papers on Distributed Constraint Optimization (DCOP) that started that subfield by providing the first comprehensive algorithm with quality guarantees (“ADOPT: Asynchronous distributed constraint optimization with quality guarantees” Artificial Intelligence Journal. 2005). Finally, their earlier paper introducing a novel Distributed POMDP model for teamwork won the AAMAS’02 Best paper. During this period, Prof. Tambe and team also built pioneering systems such as “Electric Elves” team of office assistants, reported in CNN, USA Today and others; built in early 2000s the office agents brought forth a number of challenges of privacy and agent autonomy, while assisting in day to day office activities.

Prof. Tambe’s Recent Awards

AAAI 2024 Award for Artificial Intelligence for the Benefit of Humanity

Teaching and Service

Prof. Tambe’s Teamcore group recently celebrated 25 years of research. So far, 38 PhD students have completed their theses under his supervision; he has also mentored 16 Postdoctoral researchers. Currently Prof. Tambe supervises a team of 12 PhD students and postdocs. Prof. Tambe’s former students have repeatedly been best thesis award winners or runners-up at top conferences such as AAMAS. Alumni from Teamcore group are faculty members at CMU MLD, CMU ISR, Georgia Tech, U Chicago, U Michigan and many other key departments, as well as at key positions in industry.

Prof Tambe also manages a group on “AI for social good” at Google Research.

Prof. Tambe’s service includes National Academy of Sciences panels, blue ribbon panel to review security at LAX airport and DARPA ISAT Panels. He has also served as general co-chair for AAMAS (2004), and as a member of the board of directors of IFAAMAS, the IJCAI executive committee, the board of trustees of RoboCup Robot Soccer World Cup Federation and the steering board of the Conference on Decision and Game Theory for Security (GameSec); he also served as associate editor, advisory board member and editorial board member of journals including the Journal of AI Research (JAIR), IEEE Intelligent Systems and the Journal of Autonomous Agents and Multiagent Systems (JAAMAS), and as co-editor for JAIR special track on AI and Society.

In 2013, based on their research, Prof. Tambe co-founded Avata Intelligence, which was acquired by Procore Technologies.