Alex Wong

Department of Computer Science
University of California, Los Angeles

Google Scholar
alexw [at] cs [dot] ucla [dot] edu

I am a post-doctoral researcher at the UCLA Vision Lab under the supervision of Professor Stefano Soatto. My research is primarily focused on 3D vision, which lies at the intersection of machine learning and computer vision. I was co-advised by Professor Stefano Soatto (UCLA) and Professor Alan Yuille (JHU) and successfully defended my thesis ''Exploiting Regularities to Recover 3D Scene Geometry'' on November 21, 2019.

News:

05/15/2021: I will be co-chairing the Adaptive System session (1:00 PM PST, June 1, 2021) at ICRA 2021! I will also be presenting our paper An Adaptive Framework for Learning Unsupervised Depth Completion during the session.

05/3/2021: We will be presenting our paper Learning Topology from Synthetic Data for Unsupervised Depth Completion at the Machine Learning II session (11:00 AM PST, June 1, 2021) at ICRA 2021!

02/28/2021: Two of our papers, Learning Topology from Synthetic Data for Unsupervised Depth Completion and An Adaptive Framework for Learning Unsupervised Depth Completion, have been accepted to ICRA 2021!

02/08/2021: Our paper An Adaptive Framework for Learning Unsupervised Depth Completion has been accepted to RA-L 2021!

02/06/2021: A huge thanks to everyone who came by to visit our poster Stereopagnosia: Fooling Stereo Networks with Adversarial Perturbations at AAAI 2021. The code is opensourced on github and can be accessed here (and below under Publications)!

01/21/2021: Our paper Learning Topology from Synthetic Data for Unsupervised Depth Completion has been accepted to RA-L 2021!

12/08/2020: We are excited to present Targeted Adversarial Perturbations for Monocular Depth Prediction at NeurIPS 2020, Poster session 3 (9 PM PST)!

12/02/2020: Our paper Stereopagnosia: Fooling Stereo Networks with Adversarial Perturbations has been accepted to AAAI 2021!

09/25/2020: Our paper Targeted Adversarial Perturbations for Monocular Depth Prediction has been accepted to NeurIPS 2020!

06/06/2020: We will be presenting Unsupervised Depth Completion from Visual Inertial Odometry at ICRA 2020!

Dataset:

Publication:

Preprint:

Technical Report:

Teaching:

Loyola Marymount University (LMU)
Academic Semester Course Number Course Title
Fall 2020 CMSI 535 Machine Learning
Spring 2020 CMSI 371 Computer Graphics
Fall 2019 CMSI 533 Data Science and Machine Learning
Spring 2019 CMSI 371 Computer Graphics
Fall 2018 CMSI 281 Data Structures
Spring 2018 CMSI 371 Computer Graphics

University of California, Los Angeles (UCLA)
Academic Quarter Course Number Course Title
Spring 2017 ENGR 110 Introduction to Technology Management and Economics
Winter 2017 ENGR 111 Introduction to Finance and Marketing for Engineers
Fall 2016 ENGR 111 Introduction to Finance and Marketing for Engineers
Spring 2016 ENGR 110 Introduction to Technology Management and Economics
Winter 2016 ENGR 111 Introduction to Finance and Marketing for Engineers
Fall 2015 ENGR 111 Introduction to Finance and Marketing for Engineers
Spring 2015 ENGR 110 Introduction to Technology Management and Economics
Winter 2015 ENGR 111 Introduction to Finance and Marketing for Engineers
Fall 2014 ENGR 110 Introduction to Technology Management and Economics
Spring 2014 MGMT 237G Computational Methods in Finance
Spring 2014 PIC 10B Data Structures
Fall 2013 PIC 10A Introduction to Programming
Spring 2013 PIC 10A Introduction to Programming
Winter 2013 PIC 10A Introduction to Programming