Jacob Christopher
PhD Student in Computer Science
Focus: Generative AI for Science, Responsible AI, Differentiable Optimization
About Me
I am a Ph.D. student in Computer Science at the University of Virginia, working under the guidance of Dr. Ferdinando Fioretto. My research focuses on developing innovative approaches in generative AI, responsible AI, and differentiable optimization. I'm particularly interested in creating compliant AI systems for scientific and engineering applications.
Research Interests
- Generative AI for Science: Developing novel approaches for constrained generation and diffusion models, enabling applications in real-world, safety-critical domains.
- Responsible AI: Ensuring AI systems are ethical, transparent, and aligned with human values by providing formal guarantees as to compliance with these values.
- Differentiable Optimization: Bridging the gap between machine learning and mathematical optimization with fundamental approaches.
Latest Updates
May 2025
Happy to share that our paper was accepted to ICML 2025: "Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models"
May 2025
Exicted to announce that our submission "Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation" is a recipient of the DARPA Disruptive Idea Award at NeuS 2025
April 2025
Upcoming oral presentation at NAACL 2025 for our work on speculative decoding: "Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion"
February 2024
Looking forward to two upcoming oral presentations of our work "Multi-Agent Path Finding in Continuous Spaces with Projected Diffusion Models" at AAAI 2025 workshops
December 2024
Presenting our paper on constrained diffusion models at NeurIPS 2024: "Constrained Synthesis with Projected Diffusion Models"