Chamika Sudusinghe

Chamika is a PhD student in the Department of Computer Science at the University of Illinois Urbana-Champaign (UIUC), affiliated with the Accelerate Data Intensive Applications through Programming Languages Techniques (ADAPT) research group.

Previously I've worked at WSO2, Aegis Studio, and LiveRoom. I did my Bachelor's in Computer Science & Engineering at the University of Moratuwa, Sri Lanka, where I was advised by Sapumal Ahangama. I've received the Lance Stafford Larson Award, the Upsilon Pi Epsilon Honor Society Award, the Richard E. Merwin Scholarship, and the ICT Student of the Year Award 2022 (Undergraduate).

Email / Resume / Bio / Google Scholar / Twitter / Github

Research

I'm interested in I'll be delving into the captivating realm of developing data-driven approaches to accelerate systems (ML for Systems) and, conversely, designing high performance systems that accelerate complex machine learning workloads (Systems for ML). Representative papers are highlighted.

	Building Interpretable Predictive Models with Context-aware Evolutionary Learning Binh Tran, Chamika Sudusinghe, Su Nguyen, Damminda Alahakoon Applied Soft Computing, 2023 (Vol. 132) project page / video / arXiv Combining mip-NeRF 360 and grid-based models like Instant NGP lets us reduce error rates by 8%–77% and accelerate training by 24x.
	Eavesdropping Attack Detection using Machine Learning in Network-on-Chip Architectures Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan T. Barron, Yuanzhen Li, Varun Jampani ICCV, 2023 project page / arXiv Combining DreamBooth (personalized text-to-image) and DreamFusion (text-to-3D) yields high-quality, subject-specific 3D assets with text-driven modifications
	Denial-of-Service Attack Detection using Machine Learning in Network-on-Chip Architectures Lior Yariv, Peter Hedman, Christian Reiser, Dor Verbin, Pratul Srinivasan, Richard Szeliski, Jonathan T. Barron, Ben Mildenhall SIGGRAPH, 2023 project page / video / arXiv We use SDFs to bake a NeRF-like model into a high quality mesh and do real-time view synthesis.
	Hardware-Assisted Malware Detection using Machine Learning Christian Reiser, Richard Szeliski, Dor Verbin, Pratul Srinivasan, Ben Mildenhall, Andreas Geiger, Jonathan T. Barron, Peter Hedman SIGGRAPH, 2023 project page / video / arXiv We use volumetric rendering with a sparse 3D feature grid and 2D feature planes to do real-time view synthesis.
	Network-on-Chip Attack Detection using Machine Learning Dor Verbin, Ben Mildenhall, Peter Hedman, Jonathan T. Barron, Todd Zickler, Pratul Srinivasan arXiv, 2023 project page / video / arXiv Shadows cast by unobserved occluders provide a high-frequency cue for recovering illumination and materials.

Miscellanea

	Demo Chair, CVPR 2023 Area Chair, CVPR 2022 Area Chair & Longuet-Higgins Award Committee Member, CVPR 2021 Area Chair, CVPR 2019 Area Chair, CVPR 2018
	Graduate Student Instructor, CS188 Spring 2011 Graduate Student Instructor, CS188 Fall 2010 Figures, "Artificial Intelligence: A Modern Approach", 3rd Edition
Basically Blog Posts	Squareplus: A Softplus-Like Algebraic Rectifier A Convenient Generalization of Schlick's Bias and Gain Functions Continuously Differentiable Exponential Linear Units Scholars & Big Models: How Can Academics Adapt?

Design and source code from Jon Barron's website

Research

Miscellanea

Basically Blog Posts

Basically
Blog Posts