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Aditya Ganeshan

CS PhD Student
Brown University
Graphics / Vision / Mathematics / Machine Learning / Music
Most recent update: March 31st 2023.

What I am doing now:

I am contributing towards four research directions: a) Semi-supervised program synthesis with approximate gradients, b) neural program rewriting, c) 3D Shape Editing with LLMs and d) 3D Scene generation with LLMs. Apart from that, I spend some time trying to make music and understanding different graphics/vision/pl problems/ideas.

Short Bio: Aditya Ganeshan is a third-year Ph.D. student at the Brown Visual Computing group, advised by Professor Daniel Ritchie. He is interested in developing techniques for inferring and using structured representations for 3D data (Shapes and Scenes). Previously, he worked on vision for autonomous driving at Preferred Networks Inc., Japan, and adversarial robustness at IISc, India. He completed his Bachelor’s in Applied Mathematics from IIT Roorkee, India.

Recent Research:

Improving Unsupervised Visual Program Inference with Code Rewriting Families

A. Ganeshan, R. Kenny Jones and Daniel Ritchie

Oral (1.8%) IEEE / CVF International Conference on Computer Vision (ICCV), 2023

Skill Generalization with Verbs

R. Ma, L. Lam, B. A. Spiegel, A. Ganeshan, B. Abbatematteo, R. Patel, D. Paulius, S. Tellex, G. Konidaris.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023

Warp-Refine Propagation Semi-Supervised Auto-labeling via Cycle-consistency

A. Ganeshan , Alexis Vallet, Yasunori Kudo, Shin-ichi Maeda, Tommi Kerola, Rares Ambrus, Dennis Park, Adrien Gaidon

IEEE / CVF International Conference on Computer Vision (ICCV), 2021

Phonetroller - Visual Representations of Fingers for Precise Touch Input with Mobile Phones in VR

Fabrice Matulic, A. Ganeshan, Hiroshi Fujiwara, Daniel Vogel

Conference on Human Factors in Computing Systems, CHI 21

Meta-Learning Extractors for Music Source Separation

David Samuel, A. Ganeshan, Jason Naradowsky

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-2020)

Recent highlights and news:

  • 9 February 2024 : I am helping organize a Visual Program Inference challenge at C3DV: 2nd Workshop On Compositional 3D Vision at CVPR 2024. Its the first of its kind so hope to get more folks interested in mixing programs and visual processing! A big Thanks to Habib Slim for thinking of including visual program inference as a challenge at C3DV!
  • 19 December 2023 : Finished my fifth semester with no courses. Most of the time spent in research - coding clean versions of old packages, and pushing forth with new ideas!
  • 9 December 2023 : I will be attending the NYC Computer Vision Day 2024 with many of my lab members. We will also do a short poster presentation of multiple works at 2:40 PM.
  • 9 December 2023 : I released the code for GeoLIPI: A DSL for Implicit Geometric Modelling. Its my attempt at putting together different code pieces I deal with constantly into one place. The code is still in its infancy, and I will be adding more features to it as I go along.
  • 12 November 2023 : I have accepted the awesome opportunity to work with Matt Fisher and Michael Gharbi at Adobe for the summer 2024. Hope to cook something exciting with stochastic patterns in the near future!
  • See all news ...