Alexander Wan
Undergraduate Researcher
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolAlexander Wan is an undergraduate computer science researcher at UC Berkeley specializing in NLP and machine learning, with eight years of hands-on experience in model benchmarking, robustness, and AI policy. He has led and published work on vulnerabilities in instruction-tuned LLMs and LLM detectors (ICML 2023, ACL 2024), demonstrating novel data-poisoning and adversarial attack techniques on large models and training pipelines. Currently at Stanford HAI/CRFM, he focuses on model evaluation and public policy, bridging technical rigor with real-world governance implications. Alexander also builds educational content for ML courses and has scaled experiments on TPUs and multi-GPU systems, reflecting both practical systems expertise and strong research depth. He often explores less obvious angles—such as differences between human and model evidence-resolution behavior in retrieval-augmented systems—highlighting a curiosity for the intersections of ML, security, and societal impact.
8 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at University of California, Berkeley
Github Skills (10)
gaussian8
optimization7
python6
gaussian-processes6
experimental-design4
hyperparameter-tuning4
javascript3
react3
luke2
deep-learning1
Programming languages (2)
Github contributions (5)
AlexWan0/DomiKnowS
Jan 2022 - Apr 2023
Contributions:23 pushes, 5 branches in 1 year 3 months
AlexWan0/PromotionalLSTM
May 2019 - Sep 2021
Contributions:6 pushes, 1 branch in 2 years 4 months
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