Zeyu Zhou
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Hi! I am a PhD student at Purdue ECE where I work with David I. Inouye. I have a track record of publishing in top conferences like NeurIPS, ICLR, and AISTATS, and industry research experience at Amazon and Bloomberg.
My research focuses on the development and evaluation of Machine Learning (ML) models, including conventional deep learning models and foundation models, that are robust and trustworthy when faced with complex data shifts in test cases and undesirable bias in pretraining data, enabling safe and effective deployment in dynamic real-world environments.
To solve this problem, I have leverage tools including (1) causality (NeurIPS24, ICLR24) (2) Generative AI models (ICLR23, AISTATS22, Amazon Internship)(3) domain knowledge (Bloomberg Internship)
Feel free to drop me an email if you are interested in my research or just want to chat. I am always open to new ideas and collaborations.
🔍 I am expected to graduate in Spring 2025 (flexible). Please let me know if you have any openings for a Machine Learning Researcher/Engineer or a Quantitative Researcher
🔍 I am also looking for a research internship in Winter/Summer 2025. Please let me know if you have any openings.
News
Oct 19, 2024 | I will attend NeurIPS 2024 at Vancouver, Canada. I am looking forward to meeting you there! |
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Selected Publications
- NeurIPSCounterfactual Fairness by Combining Factual and Counterfactual PredictionsNeural Information Processing Systems, 2024
- ICLR DPFMImproving Practical Counterfactual Fairness with Limited Causal KnowledgeICLR Workshop on Navigating and Addressing Data Problems for Foundation Models, 2024
- ICLRTowards Characterizing Domain Counterfactuals For Invertible Latent Causal ModelsThe Twelfth International Conference on Learning Representations, 2024
- ICLREfficient Federated Domain TranslationIn The Eleventh International Conference on Learning Representations , 2023
- AISTATSIterative Alignment FlowsIn International Conference on Artificial Intelligence and Statistics , 2022