About Me |
I previously obtained an M.S. in Computer Science
from the University of Maryland, College Park,
advised by Prof. David W. Jacobs.
My primary research interest is Multimodal Affective Computing, via minimal human expenses externally.
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.
6/23: Starts Research Internship at MIT Lincoln Lab in Lexington, MA
5/23: Graduates from the University of Maryland with an M.S. in Computer Science, advised by Prof. David W. Jacobs
5/22: Starts Research Internship with Prof. Ngan Le at the University of Arkansas over the summer
5/22: Serves as a part-time teaching assistant for Google Applied Machine Learning Intensive Summer Program
2/22: A paper [3] accepted at ACM SIGMOD 2022
12/21: Serves as a Student Committee Member for Graduate School Admissions for the Department of Computer Science at the University of Maryland
10/21: A paper [2] accepted at BMVC 2021 for an oral presentation
7/21: Selected as one of 12 receipients of $10,000 Google Scholarship in the year of 2021, funded by Google, for my postgraduate studies in Computer Science
6/21: Starts Research Internship with Prof. Leilani Battle at the University of Washington
through the NSF-funded Research Experiences for Undergraduates (REU)
5/21: Graduates from the University of Maryland with a B.S. in Computer Science (Machine Learning Track) and a Minor in Technology Entrepreneurship
6/20: Starts Software Engineering Internship at Amazon Devices (Remote)
6/19: Starts Software Engineering Internship at Amazon Web Services (AWS) in Herndon, VA
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.
Teaching Assistant
Summer 2022
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
Amazon Devices Denver, CO (Remote Internship) Summer 2020
Amazon Web Services (AWS) Herndon, VA Summer 2019
0xC0C4C0DA
(It's not a typical soda!)
v23.5.21
My Erdös number is 4
[ Erdös - P. O'Neil - M. Stonebraker - L. Battle - Me ]