Research

UC Berkeley (EECS 282)

Trained GPT-style Transformer models to study robustness of in-context learning under noisy demonstrations across synthetic regression and NLP benchmarks. Evaluated curriculum-based noise schedules on GPT-Neo 2.7B and Llama-2 7B.

UC Berkeley (CS 288)

Built neural n-gram and MLP-based language models from scratch, including tokenizer, dataloaders, and training pipelines. Achieved ~80–82% accuracy on 20 Newsgroups classification with optimized architectures.

UC Berkeley (EECS 294)

Studied Pareto frontier between user engagement and lifecycle carbon footprint in large-scale recommendation systems. Trained BPR and SASRec models (RecBole) and applied linear carbon-aware re-ranking policies.

UC Berkeley (INFO 288)

Modeling barriers to healthcare access using DHS survey data (16k+ responses) combined with geospatial travel-time, rainfall, and infrastructure data. Achieved Spearman ~0.53 and identified key drivers of access inequality in rural regions.

NTNU x NINA

Bachelor thesis project developing a scalable system to manage and visualize passive acoustic environmental data, improving automated biodiversity monitoring workflows.