Email: allen29@ucla.edu / ykei@ucsc.edu
Google Scholar

I am a Visiting Assistant Professor in the Department of Statistics at University of California, Santa Cruz (UCSC). I obtained a Ph.D. in Statistics at University of California, Los Angeles (UCLA) in June 2024, under the supervision of Prof. Oscar Hernan Madrid Padilla.

My research aims to develop realistic models and the associated inference and learning algorithms for multi-modal data to allow useful abstraction, generation, and detection. Extracting meaningful representations from data (abstraction) can help devise powerful models that produce valid knowledge in a real-world setting (generation), while identifying anomalies when certain criteria are violated (detection).

My research has also been advised by Prof. Mark S. Handcock and Prof. Ying Nian Wu at UCLA, Prof. Robert Lund, Prof. Rebecca Killick, Prof. James D. Wilson during my current position at UCSC, and many other amazing collaborators.

My research interests are

Previously, I have interned at Amazon and Cisco. I received a B.S. in Statistics and a B.A. in Economics at UCLA.

Publications

Published papers

Change Point Detection on A Separable Model for Dynamic Networks
Yik Lun Kei*, Hangjian Li*, Yanzhen Chen, Oscar Hernan Madrid Padilla
Transactions on Machine Learning Research (TMLR) 2025
PDF, Video, library(CPDstergm)
Funded by NSF DMS-2015489

Change Point Detection in Dynamic Graphs with Decoder-only Latent Space Model
Yik Lun Kei, Jialiang Li, Hangjian Li, Yanzhen Chen, Oscar Hernan Madrid Padilla
Transactions on Machine Learning Research (TMLR) 2025
PDF, Video

A Partially Separable Model for Dynamic Valued Networks
Yik Lun Kei, Yanzhen Chen, Oscar Hernan Madrid Padilla
Computational Statistics & Data Analysis 2023
PDF

YouRefIt: Embodied Reference Understanding with Language and Gesture
Yixin Chen, Qing Li, Deqian Kong, Yik Lun Kei, Song-Chun Zhu, Tao Gao, Yixin Zhu, Siyuan Huang
The IEEE International Conference on Computer Vision (ICCV) 2021 (Oral)
PDF

Preprints

Clustering in Networks with Time-varying Nodal Attributes
Yik Lun Kei, Oscar Hernan Madrid Padilla, Rebecca Killick, James D. Wilson, Xi Chen, Robert Lund
Under Review
PDF

Change Point Localization and Inference in Dynamic Multilayer Networks
Fan Wang, Kyle Ritscher, Yik Lun Kei, Xin Ma, Oscar Hernan Madrid Padilla
Under Review
PDF

Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks
Carlos Misael Madrid Padilla*, Oscar Hernan Madrid Padilla*, Yik Lun Kei, Zhi Zhang, Yanzhen Chen
Under Review
PDF

In Progress

Change Point Detection for Cell Population Measured by Flow Cytometry
Yik Lun Kei, Qi Wang, Paul Parker, Sangwon Hyun

Others

Online Multi-robot Deadlock Prediction with Conditional Variational Auto-Encoder for Sequences
Yik Lun Kei, Mo Zhang, Claire Stolz, Anoop Aroor, Yulin Zhang, Yuchen Gao
Amazon Robotics Science Summit

* denotes equal contribution

Teaching

STAT 132: Classical and Bayesian Inference
Lecture videos (Spring 2025)
Lecture videos (Fall 2024)

STAT 80A: Gambling and Gaming

STAT 266A: Data Visualization and Statistical Programming in R

STAT 280B: Seminars in Statistics

Industry Research Experience

Cisco
Software Engineer Intern (2024)

Amazon Robotics
Data Scientist Intern (2023)

UCLA
Graduate Student Researcher (2019-2024)

UCLA Health
Senior Data Analyst (2017-2019)

Software

library(CPDstergm)
Github

Talks

Department of Statistics, University of California, Santa Cruz (April 2024)

Awards

UCLA Graduate Fellowship (2021-2023)
UCLA Summer Mentored Research Fellowship (2022)

Services

Journal Reviewer
NSF Grant Reviewer
Master Thesis Committee
Graudate Student Mentor