Hamsa Balakrishnan
· Associate Dean, MIT School of Engineering; William E. Leonhard (1940) ProfessorMassachusetts Institute of Technology · Aeronautics & Astronautics
Active 1998–2026
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About
Hamsa Balakrishnan is the William E. Leonhard (1940) Professor of Aeronautics and Astronautics at MIT AeroAstro. She is the principal investigator associated with the research group, focusing on advanced air mobility, AI-assisted optimization of schedules, modeling and control of queuing networks, multi-agent navigation in dynamic environments, network models of air transportation, and trajectory-based operations. Her work involves developing innovative solutions and methodologies to improve air transportation systems and mobility through interdisciplinary research and technological advancements.
Research topics
- Computer Science
- Engineering
- Speech recognition
- Telecommunications
- Automotive engineering
Selected publications
Efficiency and Fairness in Unmanned Air Traffic Flow Management
IEEE Transactions on Intelligent Transportation Systems · 2021 · 58 citations
Senior authorCorrespondingAs the demand for Unmanned Aircraft Systems (UAS) operations increases, UAS Traffic Flow Management (UTFM) initiatives are needed to mitigate congestion, and to ensure safety and efficiency. Congestion mitigation can be achieved by assigning airborne delays (through speed changes or path stretches) or ground delays (holds relative to the desired takeoff times) to aircraft. While the assignment of such delays may increase system efficiency, individual aircraft operators may be unfairly impacted.…
Automatic Speech Recognition for Air Traffic Control Communications
Transportation Research Record Journal of the Transportation Research Board · 2021 · 44 citations
Senior authorCorrespondingA significant fraction of communications between air traffic controllers and pilots is through speech, via radio channels. Automatic transcription of air traffic control (ATC) communications has the potential to improve system safety, operational performance, and conformance monitoring, and to enhance air traffic controller training. We present an automatic speech recognition model tailored to the ATC domain that can transcribe ATC voice to text. The transcribed text is used to extract operation…
Cooperation and Fairness in Multi-Agent Reinforcement Learning
ACM Journal on Autonomous Transportation Systems · 2024-10-29 · 4 citations
articleOpen accessSenior authorMulti-agent systems are trained to maximize shared cost objectives, which typically reflect system-level efficiency. However, in the resource-constrained environments of mobility and transportation systems, efficiency may be achieved at the expense of fairness — certain agents may incur significantly greater costs or lower rewards compared to others. Tasks could be distributed inequitably, leading to some agents receiving an unfair advantage while others incur disproportionately high costs. It i…
Acta Astronautica · 2024-05-23 · 4 citations
articleSenior authorLong-Horizon Planning for Multi-Agent Robots in Partially Observable Environments
2024-01-01 · 4 citations
article1st authorCorresponding
Recent grants
CPS: Small: Recovery Algorithms for Dynamic Infrastructure Networks
NSF · $450k · 2017–2022
CAREER: Practical Algorithms for Next Generation Air Transportation Systems
NSF · $400k · 2008–2014
Frequent coauthors
- 73 shared
Karthik Gopalakrishnan
Amazon (United States)
- 36 shared
Max Z. Li
- 31 shared
Harshad Khadilkar
Tata Consultancy Services (India)
- 27 shared
Sandeep Badrinath
- 19 shared
Joseph M. Sussman
Rose–Hulman Institute of Technology
- 19 shared
Christopher Chin
Massachusetts Institute of Technology
- 19 shared
Tom Reynolds
Massachusetts Institute of Technology
- 18 shared
Ioannis Simaiakis
Massachusetts Institute of Technology
Labs
Awards & honors
- Vickie Kerrebrock Award, MIT AeroAstro, 2021
- Undergraduate Teaching Award, American Institute of Aeronaut…
- Donald P. Eckman Award | American Automatic Control Council,…
- AIAA Undergraduate Advising Award, MIT, 2014
- Associate Fellow, AIAA, 2013
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