CV

Education

PhD Candidate, Princeton University (Aug 2025 - present)

Our paper got accepted to NeurIPS!
Research on Gaussian Splatting and unsupervised structure recognition - reach out for details.

Associate, Boston Consulting Group GmbH (Nov 2023 - Jul 2025)

ML research intern, Active Vision Lab, University of Oxford (2023)

Conducted research on using non-rigid neural radiance fields for virtual reality video conferencing with the Engineering department at the University of Oxford; supervised by Ismail Ceylan, Victor Prisacariu and Philip Torr
Developed an efficient novel-pose and view synthesis model that can be used in downstream tasks such as virtual reality video conferencing systems. The system uses input from a standard webcam, and then generates different perspectives of the person in front of the camera
To achieve the required real-time performance, proposed a simple preprocessing stage during training and inference which relies on existing priors to optimize ray sampling

Applied science intern, Zalando Switzerland AG (2022)

Designed and implemented generative adversarial neural networks
Initiated and conducted experiments on unsupervised image inpainting
Contributed to the architectural design of 3D generative models to be trained without 3D data by leveraging suggestive contours
Made significant performance improvements to existing image tooling
Added additional tools to a common library for simple general-purpose preprocessing (such as semantic segmentation and dense UV unwrapping of humans)
Developed a new application for automatically generating datasets of model images with desired attributes.

Consulting intern, d-fine GmbH (2021)

Six-month full-time internship with two projects, one on sustainable and climate friendly urban transport and another focusing on decentralized cloud using distributed ledger technologies.

Cryptography research intern, Telecom Paris (2020)

Thesis on privacy-preserving face recognition in large-scale video surveillance systems using Secure Multi- Party Computation. Proposed a new framework for face recognition that makes mass-surveillance cryptographically impossible (however, with performance limitations).

Cryptography research intern, Deutsche Bank AG (2020)

Two-month full-time internship, responsible for researching on machine learning on encrypted data using homomorphic encryption and implementing a Proof of Concept.

William Koch*, Cheng Zheng*, Baiang Li, Felix Heide. 2025. "HEIR: Learning Graph-Based Motion Hierarchies". NeurIPS.

William Koch. 2023. "Efficient Non-Rigid Neural Radiance Fields for Virtual Reality Video Conferencing". Self-published.

William Koch. 2020. "Privacy-Preserving Face Recognition in Large Scale Video Surveillance Systems". Self-published.

École Polytechnique

“DESTINY - Detection of Earthquakes through a STratospheric INfrasound studY” (REXUS/BEXUS Program) - Software developer in a student research project (voluntary, no credits)
IEEE Student Branch of Ecole Polytechnique - Co-Founder and Secretary (March - June 2021)
Robotics Club - Communication (December 2020 - June 2021)
Privacy Club - Founder and President (January 2019 - June 2021)
Binet Reseau (IT Club) - contributions to projects such as a self-hosted XMPP server and Nextcloud instance for students

Studienstiftung des deutschen Volkes

Selected scholar
Scholarship spokesperson of the Paris region (2019 - 2020)
(Co-)organizer/moderator of events on educational equality and digital independence/empowerment • Organizer of a one-week academy on state surveillance, filter bubbles and big data April 2022 with a confirmed budget of nearly $40,000, 80 expected participants, 6 researchers and various speakers