Negar Rezaei | BSc in Computer Science
I'm a computer science student with a focus on Artificial Intelligence, Machine Learning, and Deep Learning. My work centers on building predictive models that address tangible problems—particularly in healthcare and system reliability domains.
- Core Focus: AI/ML with emphasis on data pipelines, preprocessing, and feature engineering
- Practical Experience: Hands-on work with healthcare datasets and system failure prediction, which shaped my understanding of data cleaning challenges and model behavior in real-world conditions
- Approach: I prioritize building solutions that solve actual problems over optimizing benchmark scores—whether that's predicting failures before they occur or interpreting why models make specific decisions
- Goal: Bridging algorithmic foundations with practical AI applications to create meaningful real-world impact
My research interests lie at the intersection of machine learning theory and practical application, with particular emphasis on healthcare and medical AI. Working extensively with healthcare and system-failure datasets has deepened my appreciation for the investigative aspects of ML: identifying patterns, analyzing model behavior, and diagnosing why systems fail under specific conditions.
Primary Areas of Interest:
- Reinforcement Learning & LLMs: Exploring adaptive systems capable of reasoning and decision-making in complex environments
- Computer Vision: Applying visual understanding to real-world problems
- ML & Robotics Intersection: Building systems that interact meaningfully with physical environments
- Theoretical Foundations: Algorithms, formal languages, and automata theory—especially as they relate to practical AI system design
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