Bio
I am a Master’s student in Artificial Intelligence at Royal Holloway, University of London, specializing in prompt engineering, LLM optimization, and NLP. I created the open-source project prompt-eng-gsm8k-gpt3.5-dspy, where I used DSPy to automate prompt creation for the GSM8K benchmark and developed my Enhanced Prolog-style reasoning method, boosting GPT-3.5 accuracy from 55.0% (zero-shot) to 74.5%.
I have hands-on experience testing prompt strategies — zero-shot, few-shot, chain-of-thought, self-consistency, Prolog-style, and DSPy-optimized — across multiple models, including GPT-3.5, LLaMA-2-7B-Chat-HF, and Qwen. My work combines reproducible code, measurable results, and practical workflows that bridge research and real-world applications.
Outside AI, I enjoy doodling, playing badminton, and mentoring peers in AI projects. And while I don’t have a definitive favorite member of One Direction, I’ll say Harry Styles for his creativity — a trait I also bring to my AI experiments.