Shubham Goelshubham-goel@berkeley.edu

Education
University of California, Berkeley

2018 - 2023

Pursuing Ph.D. in Computer Science
Advisors: Prof. Jitendra Malik and Prof. Angjoo Kanazawa

Indian Institute of Technology, Bombay

2014 - 2018

Bachelor of Technology (with Honors) in Computer Science and Engineering

Research Interests
3D Computer Vision. I’m interested in using images and videos for building a better 3D understanding of the world.
In the past, I’ve worked on Formal Methods and Program Verification also!

Scholastic Achievements· Secured All India Rank 6 in JEE Advanced 2014 among 150 thousand candidates· Secured All India Rank 50 in JEE Mains 2014 among over 1.3 million candidates· Received the Institute Academic Award, IIT Bombay for exceptional academic performance in 2014-15

Olympiads & Scholarships· Silver Medalist at the 46th International Chemistry Olympiad, Hanoi, Vietnam held in 2014
· Recipient of the KVPY (Kishore Vaigyanik Protsahan Yojana Fellowship) in 2013 by Govt. of India· Awarded the NTSE (National Talent Search Examination) Scholarship in 2010 by N.C.E.R.T. New DelhiPublications[7] Humans in 4D: Reconstructing and Tracking Humans with Transformers
Shubham Goel, Georgios Pavlakos, Jathushan Rajasegaran, Angjoo Kanazawa∗ , Jitendra Malik∗
ICCV 2023[6] Differentiable Stereopsis: Meshes from Multiple Views using Differentiable Rendering
Shubham Goel, Georgia Gkioxari, Jitendra MalikCVPR 2022[5] ABO: Dataset and Benchmarks for Real-World 3D Object Understanding
Jasmine Collins, Shubham Goel, Achleshwar Luthra, Leon Xu, Kenan Deng, Xi Zhang, Tomas F. Yago Vicente,
Himanshu Arora, Thomas Dideriksen, Matthieu Guillaumin, Jitendra MalikCVPR 2022[4] Shape and Viewpoint without Keypoints
Shubham Goel, Angjoo Kanazawa, Jitendra Malik
ECCV 2020[3] Boolean Functional Synthesis: Hardness and Practical Algorithms†
S. Akshay, Supratik Chakraborty, Shubham Goel, Sumith Kulal, Shetal ShahFMSD 2020[2] What’s hard about Boolean Functional Synthesis?†
S. Akshay, Supratik Chakraborty, Shubham Goel, Sumith Kulal, Shetal ShahCAV 2018[1] Computing Scores of Forwarding Schemes in Switched Networks with Probabilistic Faults†
Guy Avni, Shubham Goel, Thomas A. Henzinger, Guillermo Rodriguez-NavasTACAS 2017
∗Equal Contribution.

†Names of authors sorted alphabetically by last name.

Teaching & Mentoring
Graduate Student Instructor, UC Berkeley· CS 184 : Computer Graphics under Prof. Ren Ng and Prof. James F. O’BrienSpring 2023

· CS 280 : Graduate Computer Vision under Prof. Jitendra Malik and Prof. Stella Yu

Spring 2020

Teaching Assistant, IIT Bombay· MA 105 : Advanced Calculus under Prof. I.K.RanaFall 2015

· CS 226 : Digital Logic Design under Prof. Supratik Chakraborty (awarded TA of the Month) Spring 2017, 2018

Mentoring, IIT Bombay· Institute Student Mentorship Programme (mentored 12 freshmen)

2017-18· Department Academic Mentorship Programme (mentored 6 sophomores)

2017-18

Other Research Experience
Abstract Interpretation for Graphics Renderers
Guide: Prof. Sanjit Seshia, UC Berkeley

Spring 2019

· Designed an abstract domain for (over- and under-) approximating the graphics rendering pipeline for a tri-mesh.
· It enables pushing properties over the semantic space (in the 3D world) through a graphics renderer to pixel space.
· Could potentially be used for proving robustness of a downstream ML-based vision component to -ball perturbations in the (semantic) space of vertex positions

Estimating Dense Correspondences on Wide Baseline Images
Guide: Prof. Arjun Jain, IIT Bombay

2017 - 18· Worked on finding coarse-to-fine dense correspondences between wide-baseline images in a fully supervised setting.
· We used a correlation volume that encoded descriptor similarity between points and coarse regions in the first andsecond image respectively· Achieved promising results on relatively planar surfaces but didn’t perform very well in the typical case with highocclusions and disocclusions.

Restoration of Manifold-Valued Images
Guide: Prof. Stefan Roth, TU DarmstadtSummer 2017

· Worked on restoration (denoising and inpainting) of images that take values in Riemannian manifolds· Explored the use of higher order differences and arbitrary filters in modeling the loss objective.
· Came up with a family of frameworks for applying arbitrary zero-sum filters to manifold valued patches; Provided
flexibility and generalized previously defined first and second order differences over manifolds

Extracurriculars· Attended the Second Indian SAT+SMT School held at Infosys, Mysore in 2017
· Secured 2nd place in the Computer Vision track for IIT Bombay in the Inter-IIT Tech meet 2018 in Madras, India.
· Ranked 14th in ACM ICPC Chennai onsite contest and 20th in the online regionals in 2016
· Qualified for the onsite finals of Microsoft’s Build The Shield, a network security competition

Last updated: March 18, 2023