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AI for Robotics: Toward Embodied and General Intelligence in the Physical World

AI for Robotics: Toward Embodied and General Intelligence in the Physical World - Alishba Imran

AI for Robotics: Toward Embodied and General Intelligence in the Physical World

Alishba Imran is a machine learning and robotics developer focusing on robot learning for manipulation and perception. She is currently conducting research in reinforcement learning and unsupervised learning with Pieter Abbeel at the Berkeley AI Research Lab. Alishba has worked on perception at Cruise, developed simulation object manipulation methods at NVIDIA, and led efforts to reduce prosthetics costs at SJSU. At Hanson Robotics, she improved manipulation in Sophia the Robot, and at Kindred.AI, she contributed to robots that have picked up over 140 million units in production.


Keerthana Gopalakrishnan is a senior research scientist at Google Deepmind, working on robot manipulation and the Gemini project. She was educated at Carnegie Mellon University and Indian Institute of Technology. Her research concerns large language models for robotic planning, scaling visual language models for low level control, and cross-embodiment robot learning.

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Alishba Imran is a machine learning and robotics developer focusing on robot learning for manipulation and perception. She is currently conducting research in reinforcement learning and unsupervised learning with Pieter Abbeel at the Berkeley AI Research Lab. Alishba has worked on perception at Cruise, developed simulation object manipulation methods at NVIDIA, and led efforts to reduce prosthetics costs at SJSU. At Hanson Robotics, she improved manipulation in Sophia the Robot, and at Kindred.AI, she contributed to robots that have picked up over 140 million units in production.


Keerthana Gopalakrishnan is a senior research scientist at Google Deepmind, working on robot manipulation and the Gemini project. She was educated at Carnegie Mellon University and Indian Institute of Technology. Her research concerns large language models for robotic planning, scaling visual language models for low level control, and cross-embodiment robot learning.

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