Design and develop the Wave Dashboard:

• Develop a full-stack ticket sales management dashboard generating $120,000+ monthly revenue using Next.js and Node.js.
• Leverage Firebase to for scalable data storage and Google/Firebase authentication for secure data retrieval.
• More details coming up soon.

Supervised by Prof. Yu Huang and Prof. Kevin Leach:

• Reinforcement Learning for LLMs for Code: Generating negative code samples using RL with compiler-in-the-loop. More details coming up soon.
• Few-shot Malware Classification: Designed a semi-supervised malware classifier, pioneering efficient & semantics-aware malware data augmentation through information retrieval, invariance learning, and alignment techniques. The classifier achieved SOTA results with 5.60% improvement in few-shot settings and 11.44% improvement under concept-drift.
• Merging Human & Transformer Attention: Implemented a Transformer-based NLP model whose self-attention weights are refined using human attention data captured through eye-tracking. The model is applied to neural code summarization tasks with a 29.91% performance improvement, showcasing the potential of integrating human attention into neural models.
• LLM Feature Attribution Analysis: Comprehensively evaluated feature attribution in six LLMs (GPT, Llama 2, StarCoder, etc.) in code summarization through Shapley-value analysis; compared against human eye-tracking attention patterns.

Supervised by Prof. Lingming Zhang:

• Designed a universal LLM-based fuzzer targeting compilers of any programming language, with LLM-mutated code inputs integrated in the fuzzing loop; tested on 7 languages with significantly improved coverage and uncovered 76 new bugs.
• Specialized in JIT vulnerabilities within the V8 JavaScript engine; refined fuzz testing algorithms for targeted exploitation; offered expertise in instrumentation, auto-prompting, and compiler and systems programming for vulnerability pinpointing.

Post-Investment Management Team:

• Worked on the post-investment team to eliminate future manual processing of three portfolio companies’ operational data.
• Implemented a full-stack web service in React JS, Flask, and MySQL for robust client data catalog collection and storage.
• Automated the conversion of raw operational data into financial statements using OpenPyXL, Pandas, NumPy, and Seaborn.
• Built an interactive sales performance visualization interface using D3 for real-time strategic insights.