Computer Science & Physics double major at UC Irvine with junior standing. Researching GPU systems performance and acceleration compiled in C++/CUDA at MIT CSAIL, and synthetic perception models at CMU Human Sensing Lab.
A brief introduction
Hi, I'm Ishaani, a freshman at UC Irvine with junior standing, studying Computer Science and Physics. I care deeply about building high-performance technologies that make a real difference and love working on hard problems at the low-level systems and ML compilation layers.
Currently doing GPU compilation and systems research at MIT CSAIL, synthetic data pipelines at CMU Human Sensing Lab, and full-stack software development at C2S Technologies.
I enjoy bridging the gap between hardware-level execution speed and high-level artificial intelligence to create robust, barefoot-performance, and deeply impactful solutions that compile in milliseconds and scale to global workloads.
Where I've worked and researched
Recent work and experiments
Matrix multiply from scratch across 4 optimization levels: naive, shared-memory tiling, register blocking, and warp primitives. Reaches 86% of cuBLAS at large sizes. Profiled with Nsight Compute.
ResNet-18 on CIFAR-10 (60K images, 10 classes) with data augmentation, cosine LR scheduling, and early stopping. 90% test accuracy. Deployed with ONNX for hardware-agnostic inference.
A hands-on toolkit for profiling and optimizing PyTorch data loading pipelines. Demonstrates how to cut data loading overhead from ~40% to ~10% of total training time using smart batching, parallel augmentation, and CUDA prefetching.
Turns plain English into Google Calendar events. "Study for 2 hours" → optimal slot with no conflicts, auto-synced. Reads real calendar context so there's never a double-booking.
ML extraction pipeline for aviation compliance docs with 94%+ compliance accuracy, Lambda cold-start cut 65% (8 s to 2.8 s). Serving 2 international clients processing 500+ documents/month.
Matchmaking platform for startups and investors with AI semantic search. Led 3-engineer team to win 1st place out of 11 teams at C2S Technologies' internal pitch competition ($10,000 funding).