Posts by Collection

research

Sketch-in-Context Nvidia Omniverse Extension

Independent Study, Cornell University, 2022

Designed an NVIDIA Omniverse extension for architectural visualization, integrating machine learning pipelines that translate blueprints and hand-drawn sketches into ML-generated 3D geometry within professional graphics workflows. Led by Professor Donald P. Greenberg.

Vision–Language Modeling for Large-Scale Geospatial Data

Undergraduate Research, Cornell University, CIS (BURE), 2024

Built large-scale geospatial vision–language datasets by generating detailed captions from internet imagery using LLaVA-1.5 and LLaMA-3, enabling distributed training of multimodal models with over one million aligned image pairs. Led by Professor Kavita Bala and Professor Bharath Hariharan

Online ADMM for Large-Scale Machine Learning and Optimization

Ph.D. Research, University of Southern California, ISE, 2025

Proposed an online adaptive ADMM framework that updates penalty parameters via exact hypergradients, enabling stable and fast convergence for large-scale constrained machine learning and optimization problems. Led by Professor Meisam Razavaiyayn

teaching

TA — ORIE 3300: Optimization I

Undergraduate Course, Cornell University, College of Engineering, 2024

Duties: Led lab sections, graded assignments and exams, monitored exams, and held office hours.

TA — CS 4782: Introduction to Deep Learning

Undergraduate Course, Cornell University, College of Engineering, 2025

Duties: Graded assignments and exams, monitored exams, held office hours, and created written and programming assignments.

TA — ORIE 3310: Optimization II

Undergraduate Course, Cornell University, College of Engineering, 2025

Duties: Led lab sections, graded assignments and exams, monitored exams, and held office hours.