Wei-Chiu Ma 馬惟九

Young Investigator/Postdoc @ AI2/UW
Incoming Assistant Professor @ Cornell CS (starting Fall 24')

Email / Google scholar / Twitter / Misc. / Pro Bono

About Me

I am a Young Investigator/Postdoc at AI2/University of Washington, as well as an incoming Assistant Professor of Computer Science at Cornell University.

My research lies at the intersection of 3D computer vision and robotics. Specifically, I am interested in developing robust computational tools that allow us to model, reconstruct, and simulate the dynamic world from sparse, noisy, and unconstrained sensory data.

I received my Ph.D. from MIT, where I worked with Antonio Torralba (aka the Great Torralba) and Raquel Urtasun. Previously, I was a Senior Research Scientist at Uber ATG R&D and Waabi working on self-driving vehicles. I completed my M.S. in Robotics at Carnegie Mellon University (CMU), where I was advised by Kris M. Kitani.

Prospective students: I am always looking for motivated and talented students! If you are interested in collaborating or joining my group as a PhD/MS/Undergrad student or intern, please read this.


 

Recent News

  • NEW Pro bono: I will be hosting pro bono office hours starting 2021. Please check out here for more details.
  • NEW Career update: I will be joining the Computer Science Department at Cornell University as an Assistant Professor in Fall 2024! In the meantime, I will visit AI2 and the University of Washington!

  • NEW Sep. 2023: Two papers on in-the-wild/extreme 3D inverse graphics accepted to NeurIPS 2023!
  • NEW Sep. 2023: I am now Dr. Ma! Thank you, Antonio and Raquel, for your guidance and tremendous support!
  • Apr. 2023: Our work on extreme-view geometry is featured on Vox! Check it out!
  • Apr. 2023: Selected as a Cyber-Physical Systems (CPS) rising star!
  • Mar. 2023: Check out our latest effort on closed-loop sensor simulation, LiDAR generation, and thermal imaging!
  • Oct. 2022: Gave a talk at CMU, Columbia, and UIUC on in-the-wild 3D modeling, generation, and simulation!
  • Sep. 2022: Check out our latest effort on 3D scene generation, sensor simulation, and neural fields for manipulation!
  • Aug. 2022: Selected as a Siebel Scholar!
  • Apr. 2022: Gave a talk at Harvard on exploiting high-level vision for level-vision!
  • Mar. 2022: Our work on extreme-view 3D reconsturction and planar neural field are accepted to CVPR 2022!
  • Jul. 2021: BARF! Train your own NeRF from a collection of images without knowing camera poses!
  • Mar. 2021: Check out our latest effort on simulating pedestrians in the wild at CoRL and CVPR!
  • Jul. 2020: Four papers (two spotlight) accepted to ECCV 2020! Stay tuned!
  • Mar. 2020: Our work on LiDAR simulation and instance segmentation are accepted to CVPR 2020!
  • Oct. 2019: The source code of our real-time stereo algorithm is available now! Make sure to check out the amzaing differentiable PatchMatch module!
  • Jul. 2019: Three papers accepted to ICCV 2019! Details coming soon!
  • Jun. 2019: Our paper on light-weight localization is accepted to IROS 2019!
  • Mar. 2019: Two papers (scene flow and road boundary extraction) accepted to CVPR 2019!
  • Jul. 2018: Our paper on Unsupervised Intrinsic Decomposition is accepted to ECCV 2018!
  • Mar. 2018: 3 papers accepted to CVPR 2018!
  • Apr. 2017: Our book chapter on Activity Forecasting is published! Check it out!
  • Mar. 2017: Our work (a game-theoretic approach to multi-agent activity forecasting) is accepted to CVPR 2017!
  • Jan. 2017: Our work (self-localization for autonomous vehicles) is accepted to ICRA 2017!
  • May. 2016: I graduated from CMU --- thanks Kris for all your support in the past two years!

 

Research Projects

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Pro bono office hour

Inspired by Prof. Kyunghyun Cho and Krishna Murthy, starting January 2021, I have decided to commit 1~2 hours every week to provide guidance, suggestions, and/or mentorships for students from underrepresented groups or whoever is in need. Please fill in this form if you are interested.

Need more (diverse) opinions? Consider talking to people with different expertise or from different background: Tongzhou Wang (ML/RL), Alexander Haojan Liu (Speech/NLP), Zhijian Liu (ML), Vlas Zyrianov (CV), Yuan Shen (CV), Jun Gao (CV/Graphics).

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