A journey through academia, bridging cutting-edge research with real-world applications.

Highlights

  • Published ORBIT dataset curation methodology (ACL Findings 2024) and contributed to SIGIR LiveRAG workshop work.
  • Improved domain performance on MMLU (astronomy) from 69% → 76% via targeted data selection.
  • Built cost-efficient, reproducible dataset curation pipelines and released artifacts to the community.
  • Hands-on with GPU acceleration, distributed training, and IR/NLP evaluation at scale.

Academic Experience

Graduate Research Assistant — University of Illinois Urbana-Champaign (2022–2024)

Department: Computer Science
Advisor: Prof. Chengxiang Zhai
Focus: NLP, Information Retrieval, Domain Adaptation

Selected contributions

  • Designed ORBIT, a principled framework for domain-specific dataset curation and filtering.
  • Demonstrated cross-domain generalization across astronomy, law, and medicine with transparent ablations.
  • Delivered measurable gains on evaluation suites (e.g., MMLU astronomy 69% → 76%) with small, targeted data.
  • Open-sourced methods, code, and datasets for reproducibility and community adoption.
  • Collaborated with interdisciplinary teams; mentored junior researchers on methodology and writing.

Research Collaborator — NCSA (National Center for Supercomputing Applications) (2021–2023)

Mentor: Prof. Volodymyr Kindratenko
Focus: High-Performance Computing & AI Acceleration

Impact

  • Explored HPC architectures for AI workloads; profiled end-to-end bottlenecks in data and training loops.
  • Implemented GPU-centric optimizations (CUDA kernels, memory access patterns, mixed precision).
  • Scaled ML jobs with distributed systems; improved throughput and cost efficiency.
  • Built large-scale data processing flows (Spark) with robust storage and I/O strategies.

Education

Master of Computer Science (MCS) — University of Illinois Urbana-Champaign (2022–2024)

Focus: AI & Machine Learning

Relevant coursework

  • Advanced Machine Learning; Natural Language Processing; Information Retrieval
  • High-Performance Computing; Distributed Systems
  • Statistics & Data Science; Algorithms & Complexity

Bachelor of Science (BS), Computer Science — University of Illinois Urbana-Champaign (2018–2022)

Highlights

  • Strong foundation in algorithms, data structures, systems, and applied ML.
  • Leadership and service through CS organizations and peer mentorship.

Technical Skills

Programming
Python · C++ · Java · JavaScript · SQL

AI/ML
PyTorch · TensorFlow · JAX · Hugging Face · scikit-learn

Cloud & DevOps
AWS · Google Cloud · Docker · Kubernetes · Git

Data & Systems
Spark · Parallel/Distributed computing · Performance profiling/optimization

Leadership & Mentoring

  • Research mentoring: Guided undergraduates at UIUC on AI efficiency and domain adaptation (methodology, implementation, writing).
  • Community engagement: Contributed open-source code, datasets, and technical posts; active in AI/ML communities.

Awards & Recognition

  • Dean’s List (multiple semesters)
  • James Scholar (UIUC Honors Program)
  • ISUR Scholar (Research Scholar Distinction)
  • NCSA Letter of Recognition

Get in touch

I’m passionate about roles that combine cutting-edge research with practical impact—across industry and academia.