I build simulators and learned surrogates for large scientific computing facilities, and I design photonic hardware for AI. Both lines of work ask the same question, which is how to predict the behavior of a system that is too large, too expensive, or too new to measure directly.
Before joining Brookhaven I completed a Ph.D. in Electrical Engineering at the University of Kentucky in 2024, advised by Ishan Thakkar, where I worked on photonic integrated circuit based AI accelerators.
News
TRASSE submitted to IAAI-27 Latest
Learned simulator surrogates for scheduling-policy search, submitted to the Emerging Applications track.
COSMOS selected for an LDRD award
Brookhaven will fund the multidimensional photonic computing framework from October 2026 through September 2028. I lead benchmarking and evaluation.
Talk at PASC 2026 in Bern
Presented the simulator-to-surrogate methodology for performance modeling of distributed computing.
Plenary at ATLAS Software and Computing Week
Grid simulation with CGSim and surrogate modeling with TRASSE.
Poster and talk at ModSim 2026
AI-enabled modeling and simulation for distributed computing, with coauthors across Brookhaven, Pittsburgh, CMU, UMass Amherst, ORNL, and SLAC.
Best Short Paper at PMBS, SC 2025
Awarded for CGSim, the discrete-event simulator behind the grid modeling work.
Publications
Predicting job turnaround time in large-scale distributed computing environments with graph neural networks
CGSim, a SimGrid-based discrete-event simulator for distributed scientific computing Best short paper
HEANA, a hybrid time-amplitude analog optical accelerator with flexible dataflows for energy-efficient CNN inference
SCONNA, a stochastic computing based optical accelerator for ultra-fast, energy-efficient inference of integer-quantized CNNs
Photonic reconfigurable accelerators for efficient inference of CNNs with mixed-sized tensors
PROTEUS, rule-based self-adaptation in photonic NoCs for loss-aware co-management of laser power and performance
Under review and in preparation
TRASSE, learned simulator surrogates for scheduling-policy search at distributed scientific computing facilities
HOLOS, gradient-based design space exploration for LLM parallelism and hardware co-design
Analytical modeling of superconducting digital systems for large language model inference and training
An agentic extension of LightshowAI with standardized tool interfaces for XANES analysis
Research
Modeling and surrogates for distributed computing
Discrete-event simulators reproduce the behavior of production grids, and learned surrogates stand in for them once a search needs thousands of rollouts. The goal is scheduling-policy search at facilities where a single real experiment costs weeks of grid time.
Photonic and beyond-CMOS accelerators
Microring and interferometric meshes can carry many computations at once across wavelength, time, spatial mode, and polarization. My work spans the device models, the mapping from workload to degrees of freedom, and the benchmarking that decides whether any of it beats a GPU.
Projects
REDWOOD
A DOE ASCR project on modeling and optimizing scientific cyberinfrastructure. I build the simulation and surrogate stack, CGSim and TRASSE, and the training pipelines that cover 74 WLCG sites.
COSMOS
A Brookhaven LDRD on simulation-driven co-design of multidimensional photonic computing systems. I am a co-investigator leading benchmarking and evaluation against GPU, TPU, and single-degree-of-freedom photonic baselines.
LightshowAI
An X-ray absorption spectroscopy platform for NSLS-II. I work on federated authentication, streaming beamline data, and the agentic layer that exposes surrogate models and materials databases as tools.
HOLOS
A gradient-descent design space exploration framework that searches parallelism strategy and accelerator geometry together, across CMOS and superconducting digital technologies.
Service and talks
Reviewing
- IEEE Transactions on Computers
- IEEE Transactions on Computer-Aided Design
- SC 2025
- VLSI Design
- Great Lakes Symposium on VLSI
Recent talks
- Simulator-to-surrogate performance modeling for distributed computing PASC 2026, Bern
- Grid simulation and surrogates for ATLAS ATLAS Software and Computing Week, plenary
- AI-enabled ModSim for distributed computing ModSim 2026