Chen, Y. and Vinayak, R. K. “Query Design for Crowdsourced Clustering: Effect of Cognitive Overload and Contextual Bias.”
Published by
Workshop on Models of Human Feedback for AI Alignment (ICML 2024)
About
I am a fourth year PhD student in the ECE department at the University of Wisconsin-Madison, advised by Professor Ramya Korlakai Vinayak. I am interested in crowdsourcing, preference learning, and the application of machine learning algorithms. I received my B.A. in Computer Sciences and Mathematics with Honors from the University of Wisconsin-Madison as well.
Publications
Tatli, G., Chen, Y., and Vinayak, R. K. “Learning Populations of Preferences via Pairwise Comparison Queries”
Published by
MFPL Workshop at the 40th International Conference on Machine Learning (ICML 2023)
Tatli, G., Chen, Y., Mason, B., Nowak, R. D., Vinayak, R. K. “Metric Learning in an RKHS.”
Published by
The 41st Conference on Uncertainty in Artificial Intelligence (UAI 2025)
Vishwakarma, H.*, Chen, Y.*, Namburi, S.S.S., Tay, S.J., Vinayak, R. K., Sala, F. “Rethinking Confidence and Thresholds in Pseudolabeling-based SSL.”
Published by
Forty-second International Conference on Machine Learning (ICML 2025)
Chen, Y. and Vinayak, R. K. “Query Design for Crowdsourced Clustering: Effect of Cognitive Overload and Contextual Bias.”
Published by
The Web Conference 2025 (TheWebConf 2025) [Oral]
Chen, D., Chen, Y., Rege, A. and Vinayak, R. K. “PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferences.”
Published by
The Thirteenth International Conference on Learning Representations (ICLR 2025)
Vishwakarma, H., Chen, Y., Tay, S. J., Namburi, S. S. S., Sala, F., and Vinayak, R. K. “Pearls from Pebbles: Improved Confidence Functions for Auto-labeling.”
Published by
The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
Tatli, G., Chen, Y., and Vinayak, R. K. “Learning Populations of Preferences via Pairwise Comparison Queries.”
Published by
Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2024)
Chen, Y., Vinayak, R. K., and Hassibi, B. “Crowdsourced Clustering via Active Querying: Practical Algorithm with Theoretical Guarantees.”
Published by
The Eleventh AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2023)
Chen, Y., Yin, C. H., Chikodikar, S. M., and Vinayak, R. K. “On the Scoring Functions for RAG-based Conformal Factuality.”
Published by
ICML 2025 Workshop on Reliable and Responsible Foundation Models (ICML 2025)
Chen, Y., Vinayak, R. K., and Hassibi, B. “Crowdsourced Clustering via Active Querying: Practical Algorithm with Theoretical Guarantees.”
Published by
AI & HCI Workshop at the 40th International Conference on Machine Learning (ICML 2023)
Tatli, G., Chen, Y., and Vinayak, R. K. “Learning Preference Distributions From Pairwise Comparisons."
Published by
9th International Workshop on Computational Social Choice (COMSOC 2023)
Education
Awards
HCOMP/CI 2023 Travel Award
Awarded By
HCOMP/CI
UW-Madison Conference Presentation Award
Awarded By
University of Wisconsin-Madison
Skills
Programming Languages
Python, C/C++, Java, JavaScript, Rust, CUDA, SQL.
ML/AI Frameworks
PyTorch, TensorFlow, JAX, Hugging Face Transformers, scikit-learn.
Tools & Platforms
AWS (Lambda, S3, EC2), Docker, Git, MongoDB, React, Node.js.
Specializations
Machine Learning, Deep Learning, Reinforcement Learning (RLHF), Crowdsourcing, Foundation Model Alignment, Trustworthy AI, Human-in-the-Loop ML, Distributed Systems, Production ML Pipelines.