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Achievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

Achievements

Achievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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@AAIR-lab

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pulkitverma25/README.md

Hi there 👋

I am a Postdoctoral Associate in the Interactive Robotics Group at CSAIL and AeroAstro, MIT, working with Prof. Julie Shah. I completed my Ph.D. from the School of Computing and Augmented Intelligence at Arizona State University, working with Prof. Siddharth Srivastava. During my Ph.D., I was also affiliated with UC Berkeley's Center for Human-Compatible Artificial Intelligence, and ASU's Center for Human, Artificial Intelligence, and Robot Teaming. I have completed M.Tech. from Department of Computer Science & Engineering at IIT Guwahati, advised by Prof. Pradip K. Das.

My primary interests lie in AI safety, AI planning, action-model learning, and analysis of abstractions. My research focuses on safe and reliable behavior of AI agents. I am currently investigating the minimal set of requirements in an AI system that would enable a user to assess and understand the limits of its safe operability.

🔭 My research focuses on safe and reliable behavior of AI agents. I am investigating the minimal set of requirements in an AI system that would enable a user to assess and understand the limits of its safe operability.

To know more, please visit pulkitverma.net.

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  1. AAIR-lab/AIA-AAAI21 AAIR-lab/AIA-AAAI21 Public

    Code for Asking the Right Questions: Learning Interpretable Action Models Through Query Answering. AAAI 2021.

    Python 2

  2. AAIR-lab/DAAISy AAIR-lab/DAAISy Public

    Code for Differential Assessment of Black-Box AI Agents. AAAI 2022.

    Python 2 1

  3. AAIR-lab/jedai AAIR-lab/jedai Public

    An educational tool to introduce AI planning concepts using mobile manipulator robots.

    C 15 3

  4. AAIR-lab/QACE AAIR-lab/QACE Public

    Code for "Autonomous Capability Assessment of Black-Box Sequential Decision-Making Systems". NeurIPS 2023.

    PDDL 2

  5. AAIR-lab/iCaML AAIR-lab/iCaML Public

    Code for the paper "Discovering User-Interpretable Capabilities of Black-Box Planning Agents". KR 2022.

    Python 2

  6. topic_modeling topic_modeling Public

    ASU CSE 569 Fall 2018 Project

    Python