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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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.
Large-Scale Exam Scheduling via Integer Programming
Applied Optimization Project, Cornell University, 2023
Leader of the Prelim Scheduling subteam for the Cornell Scheduling Team using integer programming, incorporating fairness constraints and ML-assisted enrollment predictions. Led by Professor David Shmoys.
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 — CS 1620: Visual Imaging in the Electronic Age
Undergraduate Course, Cornell University, CIS, 2023
Duties: Led lab sections, graded assignments and projects, and held office hours.
TA — CS 4620: Introduction to Computer Graphics
Undergraduate Course, Cornell University, College of Engineering, 2024
Duties: Graded assignments and exams, monitored exams, held office hours, and created programming assignments.
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 4780: Introduction to Machine Learning
Undergraduate Course, Cornell University, College of Engineering, 2024
Duties: Graded assignments and exams, monitored exams, held office hours, and created written and programming assignments.
TA — ORIE 3510: Intro to Engineering Stochastic Processes I
Undergraduate Course, Cornell University, College of Engineering, 2024
Duties: 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.