Hao Chen

Email: haoc3 [at] andrew.cmu.edu

About Me

I’m a 4th-year PhD candidate at Carnegie Mellon University (CMU), where I am advised by Prof. Bhiksha Raj. I earned my Master’s degree in Electrical and Computer Engineering from CMU and my Bachelor’s degree from the University of Edinburgh, where I had the privilege of being supervised by Prof. Sotirios Tsaftaris and Tianjin University. I’ve also been fortunate to have the opportunity to collaborate with Prof. Jindong Wang along the way.

Research Interests

My research focuses on building more reliable and adaptable foundation models in realistic scenarios using data-centric methods:

• Exploring Pre-Training Data Imperfections: Investigate the effects of different types of data imperfections (e.g., corruption, bias, diversity) during pre-training and how they influence the physics of foundation models.
• Understanding and Mitigating Catastrophic Inheritance: Examine how imperfections in pre-training data impact downstream tasks, and develop fine-tuning methods to mitigate the detrimental effects, thereby improving reliability and generalization.
• Leveraging Imperfect Data and Labels for Transfer Learning: Develop robust learning methods to handle various types of imperfect data and labels for effective downstream task adaptation.
• Understanding Multi-Modality Generalization from Individual Components: Advancing multi-modality foundation models by understanding their individual components from training data.

I’m open to collaboration on relevant topics. I’m happy to mentor students in research and particularly encourage those from underrepresented groups to reach out.