Daniel Kang

Daniel Kang is an assistant professor of computer science at the University of Illinois Urbana-Champaign and one of the foundational researchers in zero-knowledge machine learning (ZKML). His 2022 paper "Scaling up Trustless DNN Inference with Zero-Knowledge Proofs," co-authored with Tatsunori Hashimoto, Ion Stoica, and Yi Sun, is among the most cited works in the field, and his group's open-source zkml and ZKTorch systems brought practical proving of ML model inference to models as large as GPT-scale networks. He also serves as a founding technical advisor to the VAIL project and has collaborated with the Zero Knowledge Podcast on experiments in attested audio provenance.

7 talks by Daniel Kang

• Episode 370 - ZKTorch & the Evolution of ZKML with Daniel Kang
• ZK13: ZKTorch: Efficiently Compiling ML Models to Zero-Knowledge Proof Protocols - Daniel Kang
• Bonus: zkpod.ai & Attested Audio Experiment with Daniel Kang
• CryptoXai.wtf - Daniel Kang
• What ZK can do for us: Privately Authenticating Real People (without third parties) and Auditing ML
• ZK9: Scaling Trustless DNN Inference with ZK-SNARKs to GPT, ResNet, and more – Daniel Kang (UIUC)
• Episode 265: Where ZK and ML intersect with Yi Sun and Daniel Kang