PhD candidate in Machine Learning at Georgia Tech and AI4OPT, advised by Pascal Van Hentenryck. I work at the intersection of machine learning and mathematical optimization, developing methods for reliable, effective, and computationally efficient decision-making under uncertainty: learned solution maps and policies, the local response of optimization models, value functions, and decisions under estimated uncertainty and model mismatch.
Website · CV · Google Scholar · LinkedIn
- NeurIPS 2026: Masked Sobolev Training for Feasibility-Reliable Optimization Proxies
- DiffOpt.jl: sensitivities of nonconvex programs with respect to JuMP parameters
- LearningToOptimize: learned proxies and policies for constrained decision problems, including DecisionRules.jl
- HydroPowerModels.jl, PortfolioOpt.jl, OptimalBids.jl
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About this repository (source of the website)
The website is a hand-built static site with no runtime dependencies.
src/ pages (HTML with a metadata comment) and assets
src/_partials/ shared head, header and footer
data/ publications.json, projects.json, news.json
build.py renders src/ + data/ into _site/ (Python 3, standard library only)
tools/ make_figures.py regenerates the site-styled charts;
make_diagrams.js regenerates the decision-process diagrams
- Preview:
python3 build.py --serve, then open http://localhost:8000/ - Deploy: pushing to
mainruns.github/workflows/Deploy.yml, which builds_site/and publishes it to thegh-pagesbranch. - Add a paper: append an entry to
data/publications.json(set"selected": trueto feature it on the home page). - Add a project: add an entry to
data/projects.json. An internal page lives atsrc/research/<slug>/index.html; copy an existing project page as a template. A project with its own website just setshrefto that URL, and its card links straight to it. - Diagrams: pages include
{{diagram:stage focus=state,duals}}or{{diagram:through}}; the SVG lives insrc/_partials/diagrams/and is regenerated withnpm install --no-save mathjax-full@3.2.2 && node tools/make_diagrams.js. - Regenerate charts:
python3 -m venv .venv && .venv/bin/pip install matplotlib numpy && .venv/bin/python tools/make_figures.py