Activities | Outside of research, I like to travel around, dine outside, and listen to music.
In addition, as a supporter of diversity, equity, and inclusion, I like to learn about the needs of the underrepresented minorities and explore the potential solutions to those problems with my skills.
*I am currently looking for a Ph.D. position starting in Fall 2024!*
Previously, I have been fortunate enough to have opportunities to conduct research on
Temporal Action Proposal Generation and Anomalous Activity Detection with Prof. Ngan Le
at the University of Arkansas
and on ML-based Scalable Optimization with Prof. Leilani Battle
from the Interactive Data Lab at the University of Washington.
In this paper, the magnitude-based video anomaly detection model is optimized in a weakly-supervised manner.
The proposed training pipeline notably leverages the ViT-encoded visual features from CLIP, in contrast with
the conventional C3D or I3D features in the domain, to extract discriminative representations efficiently
and nominates the snippets of interest with the proposed Temporal Self-Attention.
We propose a system that takes declarative specifications to automatically offload computation-intensive processing to a separate DBMS by optimizing visualization plans through machine learning techniques. In this project, I was primarily in charge of scalable optimization aspect of the project.
[ Note: This is the UW REU project that I worked on with Profs. Battle and Moritz in Summer 2021. Keep an eye out for the extended version of the work, to be done and submitted in Fall 2023! ]
The human perceives the establishment of an action in a video through the interaction between an actor and the surrounding environment.
We borrow the idea in producing the proposed Actor-Environment Interaction network.
After partnering with the National Action Council for Minorities in Engineering and Google, the College of Engineering at the University of Arkansas is hosting the Google Applied Machine Learning Intensive Bootcamp for 10 weeks over the summer to introduce undergraduate (URM-focused) college students to applied machine learning concepts.
Knowledge is meant to be shared! I enjoy interacting with people and sharing my knowledge with others! Oftentimes, I serve as a guest speaker, too, at academic clubs, dicussing my research, industry, and academic backgrounds with fellow students! :)
Here are seven other reasons I strongly prefer to be a Teaching TA for CMSC131:
1. Greatly improves my skills for oral presentation
2. Forms social connections with newcomers
3. Excellent memory refresher of Java
4. Enables self-evaluation of my communication skill
5. Student-evaluation of my skills at the end of sem
6. Builds up confidence as a speaker
7. Solid setting for practicing my leadership,
organization, and on-the-fly Q&A skills
Technology & Engineering Entrepreneurship TA @ UMD
Entrepreneurial Opportunity Analysis and Decision-Making in Technology Ventures (ENES210) Instructor: Prof. James Green Spring 2021 Marketing High-Technology Products and Innovations (ENES462) Instructor: Lecturer Michael Pratt Spring 2021 Leading and Financing the Technology Venture (ENES466) Instructor: Lecturer Michael Pratt Spring 2021
Undergraduate Internship Experience
Amazon Devices Denver, CO (Remote Internship) Summer 2020
Amazon Web Services (AWS) Herndon, VA Summer 2019
(It's not a typical soda!)
My Erdös number is 4
[ Erdös - P. O'Neil - M. Stonebraker - L. Battle - Me ]