• Fine-tune Large Language Models (LLMs) using Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), RewardModeling (RM)• Use SFT to improve model responses with labeled data.• Refine accuracy with feedback from RLHF.• Guide outputs using RM with defined success criteria.• Identify model weaknesses.• Analyze data to spot and correct anomalies.• Curate examples to enhance understanding of context and facts.• Monitor outputs for safety and… Show more • Fine-tune Large Language Models (LLMs) using Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), RewardModeling (RM)• Use SFT to improve model responses with labeled data.• Refine accuracy with feedback from RLHF.• Guide outputs using RM with defined success criteria.• Identify model weaknesses.• Analyze data to spot and correct anomalies.• Curate examples to enhance understanding of context and facts.• Monitor outputs for safety and precision.• Collaborate with teams to align AI with business goals. Show less

Teaching Assistant of Algorithms (CSC306) and Introduction to Computer Programming (CSC101) courses at IUB

As the Vice-Chair of IUB ACM Student Chapter I led a group of enthusiast people and together we planned and organized various seminar and events. I also conducted several working on C++ and Python myself. It was a wonderful journey.