Mansi Sood

I am a Schmidt Science Fellow at the MIT Laboratory for Information and Decision Systems (LIDS) working with Devavrat Shah since Fall 2024.

My research focuses on making networked systems that interface with our everyday lives more trustworthy and performant. Modeling the complexity, interdependency, and uncertainty in the continually evolving landscape of our networked socio-technical systems raises fundamental questions for stochastic modeling, network design and inference, which my research seeks to address.

My postdoctoral research is generously funded by a Schmidt Science Fellowship for 'world’s most outstanding emerging scientists' through the Rhodes Trust and Schmidt Sciences. My doctoral research has been recognized by the A.G. Jordan Award for outstanding Thesis ('25), Best Paper Award at International Conference on Communications '21, Graduation Day Award in Information Theory and Applications '24, and several competitive fellowships at CMU, including the College of Engineering's Dowd Fellowship '20 (awarded to top-3 applicants) and the Cylab Presidential Fellowship ('20, '23). I have been twice recognized as an EECS Rising Star (Georgia Tech '23 and MIT '21).

Keywords: stochastic modeling; complex networks; optimization; machine learning and inference

Background

I obtained my PhD in Electrical and Computer Engineering at Carnegie Mellon University where I was affiliated with the CyLab Security & Privacy Institute and advised by Osman Yağan. My doctoral research investigated how structural heterogeneity impacts performance of stochastic networked systems.

Prior to this, I completed my Bachelors and Masters in Electrical Engineering at the Indian Institute of Technology (IIT) Bombay, India, working with Sharayu Moharir and Ankur Kulkarni at the interface of optimization and game theory for resource allocation in online markets.

I moonlight as a watercolor artist and I am passionate about improving support structures in pursuing science and art. For my contributions, I have been awarded the Graduate Student Service Award ('24), the Unsung Hero Award ('22), and the Advanced Graduate Ambassadorship of the Institute for Advanced Study, Princeton ('22).

Updates

[May '25] Honored to be recognized with the A.G. Jordan Award for outstanding PhD thesis work [Thesis].
[Feb '25] Attended the Schmidt Science Fellows Science Leadership Program at Stanford and UC Berkeley.
[Jan '25] Invited talks at IIT Madras Wadhwani School of Data Science & AI and IIT Delhi Department of Electrical Engineering.
[Oct '24] Invited to speak at the session on Theoretical Advances in Networks, Dynamics and Inference at 2024 INFORMS Annual Meeting in Seattle.
[Oct '24] Attended the Schmidt Science Fellows Science Leadership Program at Rhodes House and Blavatnik School of Government, University of Oxford.
[Sep '24] Excited to be working with Devavrat Shah at MIT LIDS as a Schmidt Science Fellow.
[Apr '24] Honored to be part of the 2024 Cohort of Schmidt Science Fellows. [Forbes]
[Mar '24] Honored to receive the Graduate Student Service Award at the Annual Celebration of Education, CMU. [News Story by CMU ECE and College of Engineering]
[Feb '24] Honored to be recognized with a Graduation Day Award at the Information Theory and Applications Workshop.
[Dec '23] Invited to speak at the Stochastic Networks, Applied Probability, and Performance (SNAPP) Seminar [Slides]
[Dec '23] Completed multi-semester training in pedagogy as part of the Future Faculty Program.
[Nov '23] Honored to be recognized as an EECS Rising Star. Excited to visit Georgia Tech!
[Aug '23] Honored to be recognized as a CMU Security & Privacy Insitute (CyLab) Presidential Fellow. [News Story]
[Jun '23] Our paper Spreading Processes with Mutations over Multi-layer Networks features in the Proceedings of the National Academy of Sciences (PNAS). [News Story]
[Aug '22] Awarded the Advanced Graduate Ambassadorship of the Institute for Advanced Study (IAS).
[May '22] Started my Internship as a Machine Learning Researcher at the Bosch Center for Artificial Intelligence as part of the Robust and Safe Deep Learning team.
[May '22] Visited the IAS School of Mathematics for the WAM Mathematics of Machine Learning program.
[Apr '22] Awarded the Unsung Hero Award.
[Oct '21] Thrilled to be a part of the cohort of MIT EECS Rising Stars.
[Jun '21] Honored to receive the Best Paper Award at International Conference on Communications (ICC). [News Story by CMU ECE and College of Engineering].

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