Jacob K Christopher
Scholar

Jacob K Christopher

Google Scholar ID: Jz_PoUQAAAAJ
Ph.D. Candidate, University of Virginia
Generative AI for ScienceResponsible AIDifferentiable Optimization
Citations & Impact
All-time
Citations
82
 
H-index
5
 
i10-index
4
 
Publications
9
 
Co-authors
0
 
Resume (English only)
Academic Achievements
  • September 2025: Two papers accepted at NeurIPS 2025: 'Training-Free Constrained Generation With Stable Diffusion Models' (spotlight) and 'Constrained Discrete Diffusion'.
  • May 2025: Paper accepted to ICML 2025: 'Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models'.
  • May 2025: Submission 'Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation' received the DARPA Disruptive Idea Award at NeuS 2025.
  • April 2025: Upcoming oral presentation at NAACL 2025 for work on speculative decoding: 'Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion'.
  • February 2024: Looking forward to two upcoming oral presentations of work 'Multi-Agent Path Finding in Continuous Spaces with Projected Diffusion Models' at AAAI 2025 workshops.
  • December 2024: Presenting paper on constrained diffusion models at NeurIPS 2024: 'Constrained Synthesis with Projected Diffusion Models'.
Research Experience
  • Focused on developing innovative approaches in generative AI, responsible AI, and differentiable optimization.
Education
  • PhD student in Computer Science at the University of Virginia, working under the guidance of Dr. Ferdinando Fioretto.
Background
  • PhD Candidate in Computer Science, with research interests in Generative AI for Science, Responsible AI, and Differentiable Optimization.
Co-authors
0 total
Co-authors: 0 (list not available)