📚 I’m a third-year student at the University of Sydney.

🔬 My passion is applied deep learning, especially fields with high impact. I also am deeply passionate about building and aligning harmless, honest and helpful AI systems.

🤝 I’m always eager to learn from others and help out fellow machine learning enthusiasts, especially in the fields of AI Safety. Please reach out if you’re working on something similar.

🔍 Currently Exploring

• Interpretability in large language models
• Reinforcement learning methods, e.g. PPO for game playing
• Applications of SOTA AI methods towards traditional science problems, e.g. enyzme design

💼 Selected Experience

• President, Sydney Uni Data Science Society (SUDATA)
  2023 – Present
  🎉 Led event planning and delivery for a 1000+ member club and 50+ member team, enhancing the student experience
  🧠 Developed peer-led study sessions and workshops, benefiting over 100 students
  🚀 Organized academic talks, networking nights, and the annual Datathon with 70+ attendees, mentors, guest speakers, and judges

• Data Science Intern, AI Labs – Commonwealth Bank of Australia
  Jan. 2025
  🧠 Designed and implemented internal AI tools, including an LLM-as-judge for NLP evaluation
  🔍 Built RAG models to enhance information retrieval and workflow automation

• Research Intern – Sydney Precision Data Science Centre
  2024
  📊 Developed a dataset and ML pipeline for predicting optimal clustering algorithms in spatial transcriptomics
  🧬 Presented research at the Australian Bioinformatics and Computational Biology Society Conference 2024

• Head Chemistry Tutor
  🧪 5 years of experience tutoring high school and competition-level chemistry
  🏅 International Chemistry Olympiad Bronze Medalist, mentoring the next generation of students
  👩‍🏫 Supported over 100+ students through personalized sessions and curriculum design

🛠️ Projects

• Clustering Recommender for Spatial Transcriptomics
  🧠 Built a machine learning framework to recommend clustering methods and parameters based on dataset characteristics
  📊 Presented at the Australian Bioinformatics and Computational Biology Society Conference 2024
  🧪 Stack: Python, scikit-learn, pandas, matplotlib

• LLM Interpretability Toolkit (in progress)
  🤖 Exploring transparency in large language models through attribution and probing. 🛠️ Stack: Python, Transformerlens, Wandb, LangChain

🌱 What I Value

• Building systems that are useful, honest, and kind (and also embodying those values yourself)
• Open-source collaboration and community learning, especially teaching others!
• Learning (and failing) every single day