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Anurag Ajay
Ph.D. student at Massachusetts Institute of Technology
Anurag Ajay is a prominent researcher currently pursuing his Ph.D. in Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), specifically within the Computer Science and Artificial Intelligence Laboratory (CSAIL). His academic journey began with a Bachelor's degree in EECS from the University of California, Berkeley (UC Berkeley), where he studied under renowned professors such as Pieter Abbeel and Sergey Levine from 2013 to 2017.234
Academic Background
- Undergraduate Education: B.S. in EECS from UC Berkeley (2013 - 2017).
- Graduate Education: S.M. in EECS from MIT (2017 - 2019) and currently a Ph.D. student at MIT (2019 - present), advised by Pulkit Agrawal.25
Research Focus
Anurag's research primarily revolves around Machine Learning, with significant contributions to areas such as:
- Reinforcement Learning (RL): He has worked on offline RL, generative modeling, and the development of foundation models for decision-making.
- Publications: His work includes influential papers on topics like adaptive meta-reinforcement learning and embodied question answering, with numerous citations reflecting his impact in the field.126
Professional Experience
In addition to his academic pursuits, Anurag has gained experience through internships at leading research institutions, including Meta AI (FAIR) and Google Brain.2 His contributions have been recognized through various awards, including support from the MIT Presidential Fellowship.
Online Presence
Anurag maintains a professional profile on platforms like LinkedIn and Google Scholar, where he shares his publications and ongoing research initiatives. His GitHub page also showcases his projects related to machine learning applications.25
In summary, Anurag Ajay is an emerging leader in the field of artificial intelligence and machine learning, with a strong foundation built during his time at UC Berkeley and ongoing innovative research at MIT.