Zhen Lin
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Zhen Lin

Jump Trading


I am a Quant Researcher at Jump Trading. I finished my Ph.D. at the University of Illinois at Urbana-Champaign, supervised by Professor Jimeng Sun. My latest research interest is in uncertainty quantification for language models and other generative models. I was fortunate to be recognized as a 2023 Meta PhD Fellowship Finalist.

Before grad school, I received my bachelor’s degrees in Computer Science, Mathematics, and Statistics from UChicago in 2018. I also spent two years at AQR Capital Management LLC.


Select Publications

Tutorial: Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey
Xiaoou Liu, Tiejin Chen, Longchao Da, Chacha Chen, Zhen Lin, Hua Wei
KDD 2025
[paper] [Tutorial]

Contextualized Sequence Likelihood: Enhanced Confidence Scores for Natural Language Generation
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Empirical Methods in Natural Language Processing (EMNLP) 2024
[arxiv] [code]

Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Transactions on Machine Learning Research (TMLR), May 2024
[arxiv] [code]

Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control
Zhen Lin, Shubhendu Trivedi, Cao Xiao, Jimeng Sun
International Conference on Machine Learning (ICML) 2023
[arxiv] [code]

Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
International Conference on Learning Representations (ICLR) 2023
[arxiv] [code]

Conformal Prediction with Temporal Quantile Adjustments
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Conference on Neural Information Processing Systems (NeurIPS) 2022
[arxiv] [code]

Conformal Prediction Intervals with Temporal Dependence
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Transactions on Machine Learning Research (TMLR), August 2022
[arxiv] [code]

SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models
Zhen Lin, Cao Xiao, Lucas Glass, M. Brandon Westover, Jimeng Sun
AAAI Conference on Artificial Intelligence (AAAI) 2022
[arxiv] [code]

Locally Valid and Discriminative Prediction Intervals for Deep Learning Models
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Conference on Neural Information Processing Systems (NeurIPS) 2021
[arxiv] [code]

Clebsch-Gordan Networks: A Fully Fourier Space Spherical Convolutional Neural Network
Risi Kondor†, Zhen Lin†, Shubhendu Trivedi†
Neural Information Processing Systems (NuerIPS) 2018
[arxiv] [code]

† denotes alphabetical author ordering