Visiting Master’s Researcher
University of Cambridge, October 2025 – Present
Analysing the effects of fine-tuning methodologies on AI bias guardrails in LLMs; in collaboration with Noah Broestl, under the supervision of Dr. Umang Bhatt
Research Engineer in AI Policy and Governance
Responsible AI Institute, January 2026 – Present
Building the theoretical and technical foundations for AI governance mechanisms, such as a risk classification and policy generation framework for agentic AI systems
Analysing the Effects of Fine-Tuning Methodologies on AI Bias Guardrails in LLMs
Master’s Dissertation, May 2026 – Present
Testing the effectiveness of LoRA and OFT on eroding pre-programmed AI bias guardrails in LLMs. Aiming to develop a practical recommendation and theorem that industry and academic stakeholders can use to determine how much fine-tuning data they need to eliminate bias guardrails in their specific use case. In collaboration with the TRACE Lab at the University of Cambridge.
Developing Bias Identification and Mitigation Techniques for Clinical Prediction Models (CPMs)
Imperial College London ELEC70122: ML for Safety Critical Decision-Making, January 2026 - March 2026
Devised bias identification methods that showed CPMs can learn to use missing data as a predictive signal and contribute to undesirable feedback loops in clinical settings. Introduced an uncertainty-triggered measurement intervention and a causal RLHF pipeline as bias mitigation methods for this use case.
Investigating the Presence of Bias and Potential Copyright Concerns in LLM Image Generation Capabilities
Penn HCI Lab, August 2024 - February 2026
Used quantitative and qualitative sociotechnical evaluation methods to investigate racial bias, gender bias, and potential copyright concerns in LLM-generated movie posters.
Comparing Predictive Machine Learning Models’ Capacity to Objectively Predict Dyspnea
Penn Medicine, May 2022 - May 2023
Developed predictive ML models that automatically and accurately estimated a patient’s breathing exertion levels; allowed doctors to monitor patient with respiratory illness without using physically invasive methods.
Utilising Correlational Analysis to Identify Traits of Successful Forecasters
Penn Psychology Department, May 2023 - September 2023
Applied correlational analysis to identify the traits and behaviours most associated with successful forecasters in a forecasting tournament.
🎓 Rhodes Scholarship Nominee
University of Pennsylvania, August 2024 & August 2025
Endorsed by UPenn to move forward in the Rhodes Scholarship process
🎓 Phi Beta Kappa Inductee
Phi Beta Kappa, May 2025
Top 8% of UPenn’s graduating class of 2025