Tianwei (Victor) Ni

(Photoed in UC Berkeley 2017)



[Curriculum Vitae]

Short Bio

I’m Tianwei (Victor) Ni, a student researcher in AI.
I work closely with Benjamin Eysenbach and Prof. Ruslan Salakhutdinov at Carnegie Mellon University.
I will join Département d’informatique et de recherche opérationnelle, Université de Montréal & Mila - Quebec AI Institute as a PhD student advised by Prof. Pierre-Luc Bacon.

I obtained my master’s degree at Machine Learning Department, School of Computer Science, Carnegie Mellon University. My master research was advised by Prof. Katia Sycara at Robotics Institute. Prior to CMU, I obtained my Bachelor degree in Computer Science at Peking University. My undergraduate research was guided by Prof. Zhouchen Lin, Dr. Lingxi Xie, and Prof. Alan Yuille.

Research Topics

My research interest mainly lies in reinforcement learning, or in a broad sense, the intersection of machine learning and control. It is also known as robot learning when applied to robotics and actionable intelligence as part of AI. The key concept in this interdisciplinary area has several aliases in different fields: action/policy in reinforcement learning, control/law in control theory, motor/actuator in robotics, and decision-making in psychology/neuroscience. I hope to absorb ideas and bridge gaps among these areas for better understanding of and solutions to AI and other fields.

With the advances in deep learning in the last decade, we saw some superhuman (multi)agents in this area, but mainly in game AI. As a firm advocate of next-generation automation for everyday life in the long run, I love everything related to learning to control the dynamical systems in theory, algorithms, and applications.

More detailed and recent research topics will come soon. You can see my past publication here.


  • 2021-02-15: I will join Mila - Quebec AI Institute as a Ph.D. student starting from fall 2021 :)
  • 2021-02-01: I will join Allen Institute for AI (AI2) as a research intern during summer 2021 :)