Email: allen29@ucla.edu
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Lectures
I am a Ph.D. candidate in the Department of Statistics and Data Science at University of California, Los Angeles (UCLA). My advisor is Prof. Oscar Hernan Madrid Padilla. Previously, I received a B.S. in Statistics and a B.A. in Economics at UCLA in 2017. My research interests are
- Generative Learning, Representation Learning, Unsupervised Learning
- Computer Vision
- Bayesian Inference and Empirical Bayes Methodology
- Generative, Temporal, and Latent Space Models for Complex Networks/Graphs
- Change Point Detection, Anomaly Detection
Publications
Change Point Detection on a Separable Model for Dynamic Networks
Yik Lun Kei *, Hangjian Li *, Yanzhen Chen, Oscar Hernan Madrid Padilla
Under Review
PDF
R package: library(CPDstergm)
A Partially Separable Temporal Model for Dynamic Valued Networks
Yik Lun Kei, Yanzhen Chen, Oscar Hernan Madrid Padilla
Under Review
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
* denotes equal contribution
Teaching
Guest Lecturer
- Linear Models (100C)
- Mathematical Statistics (100B)
Teaching Fellow
- Statistical Modeling and Learning (201B)
- Computation and Optimization for Statistics (102B)
- Introduction to Data Analysis and Regression (101A)
- Linear Models (100C)
- Mathematical Statistics (100B)
- Introduction to Probability Theory (100A)
- Introduction to Statistical Methods for Life and Health Sciences (13)
- Introduction to Statistical Reasoning (10)
Work Experience
Data Scientist Intern at Amazon (2023)
Senior Data Analyst at UCLA Health (2017-2019)
R package
library(CPDstergm) # install in R via install_github(“allenkei/CPDstergm”)
Awards
UCLA Graduate Fellowship (2021-2023)
UCLA Summer Mentored Research Fellowship (2022)
Services
Journal Reviewer