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Talks, seminars, and posters.
2026
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Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
Department of Mathematics and Statistics, Binghamton University, Binghamton, New York
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Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania
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Understanding Cross-Population PRS Prediction: Transfer Learning with Sparse and Correlated Structures
DahShu Data Science Symposium 2026, Harvard Medical School, Boston, Massachusetts
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Contaminated Multi-task Learning with Heterogeneity: Negatives and Positives
2026 ICSA Applied Statistics Symposium, George Mason University
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Contaminated Multi-task Learning with Heterogeneity: Negatives and Positives
Workshop on Robust Statistics, Department of Statistics, Columbia University
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Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
School of Statistics, University of Minnesota Twin Cities
2025
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Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
2025 Joint Statistical Meetings
SLDS Student Paper Award
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Federated Transfer Learning with Differential Privacy
2025 ENAR Spring Meeting
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics, University of Illinois Urbana-Champaign
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics, Pennsylvania State University
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics and Data Science, National Singapore University
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics, University of British Columbia
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics, University of Michigan
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics, University of Virginia
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics, Ohio State University
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics, University of California, Riverside
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics, University of California, Irvine
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics and Data Science, University of California, Los Angeles
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Mathematics and Statistics, Boston University
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Biostatistics, University of North Carolina - Chapel Hill
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics and Operations Research, University of North Carolina - Chapel Hill
2024
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Applied and Computational Mathematics and Statistics, University of Notre Dame
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Division of Biostatistics and Health Data Sciences, University of Minnesota - Twin Cities
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Transfer and Multi-task Learning: Statistical Insights for Modern Data Challenges
Department of Statistics, Florida State University
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Regularized Fine-tuning in Representation Multi-task Learning: Adaptivity and Robustness
Department of Statistics, Iowa State University
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Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
SIAM Conference on Mathematics of Data Science (MDS24)
SIAM Student Travel Award
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Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
2024 Joint Statistical Meetings
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Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
2024 IMS-China International Conference on Statistics and Probability, Ningxia University, China
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Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
The 37th New England Statistics Symposium (NESS 2024), University of Connecticut
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Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
Foundations of Data Science Center Workshop, Data Science Institute, Columbia University
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Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
2024 Minghui Yu Memorial Conference, Department of Statistics, Columbia University
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Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
Student seminar, Department of Statistics, Columbia University
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Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
Department of Statistics and Finance, School of Management, University of Science and Technology of China
2023
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Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
Young Statistician Workshop, School of Mathematical Sciences, Shenzhen University, China
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Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
IMS Young Mathematical Scientists Forum - Statistics and Data Science, Department of Statistics and Data Science, National University of Singapore
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Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
2023 Joint Statistical Meetings
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Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
The 36th New England Statistics Symposium (NESS 2023), Boston
Student Research Award
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Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
Statistical Foundations of Data Science and their Applications: A conference in celebration of Jianqing Fan’s 60th Birthday
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Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
2023 Minghui Yu Memorial Conference, Department of Statistics, Columbia University
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Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
Berkeley-Columbia Meeting in Engineering and Statistics
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Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
Columbia Statistical Machine Learning Symposium
2022
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Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
2022 IMS International Conference on Statistics and Data Science (ICSDS), Florence, Italy
Student paper award
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Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
International Conference on Advances in Interdisciplinary Statistics and Combinatorics (AISC 2022), The University of North Carolina at Greensboro
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Prediction of Dementia Subtypes by Machine Learning: Feasibility of Error Control
The Alzheimer’s Association International Conference (AAIC 2022), San Diego
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2nd Annual Graduate Student Research Conference (online), National Institute of Statistical Sciences (NISS)
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Transfer Learning under High-dimensional Generalized Linear Models
2022 Minghui Yu Memorial Conference, Department of Statistics, Columbia University
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Transfer Learning under High-dimensional Generalized Linear Models
Conference on Advances in Bayesian and Frequentist Statistics with a Celebration of the 80th Birthday of Professor William E. Strawderman, Department of Statistics, Rutgers University
2021
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RaSE: Random Subspace Ensemble Classification
2021 Minghui Yu Memorial Conference, Department of Statistics, Columbia University
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RaSE: Random Subspace Ensemble Classification
2021 Women in Science at Columbia Graduate Research Symposium, Columbia University