Yang Ba

Yang Ba profile photo
PhD Student @ ASU SCAI
yangba [at] asu [dot] edu

I am a final-year Ph.D. student in Data Science, Analytics and Engineering at Arizona State University, School of Computing and Augmented Intelligence (ASU SCAI), where I am co-supervised by Dr. Rong Pan and Dr. Michelle V. Mancenido, and worked with the DHS Center for Accelerating Operational Efficiency (DHS-CAOE). I previously earned my M.S. in Business Analytics from the University of Connecticut.

My research interests span machine learning and generative AI, with a particular focus on large language models (LLMs) and multimodal learning. I investigate synthetic data generation and evaluation, aiming to understand and improve how generative and foundation models learn, represent, and generalize across modalities. My current work explores the benefits and risks of synthetic data, advances model uncertainty quantification, and improves multimodal performance through latent space alignment. Broadly, I seek to advance responsible AI systems through the effective use of synthetic data and model interpretability. Additionally, I have a strong background in statistical data analysis.

Selected Publications

ICLR Workshop
Measuring Dataset Diversity from a Geometric Perspective
Yang Ba, Mohammad Sadeq Abolhasani, Michelle V Mancenido, Rong Pan
ICLR 2026 (DATA-FM Workshop)
NeurIPS Workshop
Predict Training Data Quality via Its Geometry in Metric Space
Yang Ba, Mohammad Sadeq Abolhasani, Rong Pan
NeurIPS 2025 (NPGML Workshop)
EMNLP
Fill In The Gaps: Model Calibration and Generalization with Synthetic Data
Yang Ba, Michelle V. Mancenido, Rong Pan
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP) 2024
Journal
Data Quality in Crowdsourcing and Spamming Behavior Detection
Yang Ba, Michelle V. Mancenido, Erin K. Chiou, Rong Pan
Behavior Research Methods
Preprint
Data Diversity as Implicit Regularization: How Does Diversity Shape the Weight Space of Deep Neural Networks?
Yang Ba, Michelle V. Mancenido, Rong Pan
Preprint

Awards

Student Travel Award for Joint Research Conference on Statistics in Quality, Technology, and Industry, 2024
ASU Travel Award, 2024, 2025
ASU SCAI Doctoral Fellowship, 2023
the 6th place at the 2nd Annual Big Data Health Science Case Competition, 2021
1st place for the final projects in the Data Mining class at UConn, 2020

Teaching Experience

Teaching Assistant, Arizona State University, CSE 110: Principles of Programming, Fall 2021
Graduate Teaching Assistant, University of Connecticut, OPIM 5671: Data Mining and Business Intelligence, Spring 2021

Professional Service

Conference Reviewer: ICLR 2025, 2026, NeurIPS 2025, AAAI 2026, ICML 2026
Journal Reviewer: Journal of Quality Technology