I am a second-year Master's student (M.S. in CS '23) at the University of Maryland, College Park,
where I am advised by Prof. David W. Jacobs.
My primary research interest lies in Video Understanding & Spatiotemporal Analysis(e.g., Action Recognition, Video Anomaly Detection, Multispectral Satellite Imagery, Time-Series), and
my favorite areas of overlap with the topic include
Multimodality,
Zero-Shot Learning,
and Cognitive Neuroscience.
I received a B.S. from the University of Maryland, College Park, in May 2021, where I majored in Computer Science with specialization in Machine Learning and minored in Technology Entrepreneurship.
Outside of research, I like to draw a sketch, travel around, and appreciate artworks.
In addition, as a supporter of diversity, equity, and inclusion and as a believer in the power of peculiarity and unconventionalism, I like to take part in workshops or events promoting diversity as a hobby.
I am always open for invitation to be a guest speaker on diversity!
*I am currently looking for a Ph.D. position starting in Fall!*
Previously, I have been fortunate enough to have opportunities to conduct research on Action Recognition and Video Anomaly Detection with Prof. Ngan Le
from the AICV Lab at the University of Arkansas and on ML-based Scalable Optimization and Zero-Shot Learning with Prof. Leilani Battle
from the Interactive Data Lab at the University of Washington.
12/22: Receives an invitation to the CRA Grad Cohort Workshop '23 (Hawaii | Scholarship by CRA)
11/22: Receives a research internship offer from MIT Lincoln Lab for Summer 2023 to work on Video Understanding
9/22: Attends the Grace Hopper Conference '22 (Virtual | Scholarship by UMD)
9/22: Attends the ACM Richard Tapia Conference '22 (Washington, D.C. | Scholarship by UMD)
8/22: Receives the Graduate Assistantship from the University of Maryland as a Part-Time Teaching Assistant for CMSC131 (Object-Oriented Programming I) in Fall 2022
6/22: Attends CVPR 2022 (New Orleans, LA | Scholarship by CVPR & UMD) and selected to serve as one of the 11 graduate student mentors at the CVPR Academy Workshop
6/22: Attends the 41st ACM SIGMOD Conference (Remote)
5/22: Starts research internship 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
3/22: Attends the CRA Grad Cohort Workshop for IDEALS: Inclusion, Diversity, Equity, Accessibility, and Leadership Skills (San Diego, CA | Scholarship by UW)
3/22: Attends the 37th CSUN Assistive Technology Conference (Anaheim, CA | Scholarship by UW)
2/22: A paper [3] accepted at ACM SIGMOD 2022
1/22: Receives the Graduate Assistantship from the University of Maryland as a Full-Time Teaching Assistant for MSML641 (Natural Language Processing) and CMSC426 (Computer Vision) in Spring 2022
12/21: Serves as a Student Committee Member for Graduate School Admissions for the Department of Computer Science at the University of Maryland, reviewing over 20 applications (2022 Cycle)
12/21: Completes the Semester with a GPA of 4.0
10/21: A paper [2] accepted at BMVC 2021 for an oral presentation
8/21: Receives the Graduate Assistantship as a Full-Time Research Assistant for Fall 2021 from the University of Maryland
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 Dr. Leilani Battle at the University of Washington
through the Research Experiences for Undergraduates (REU) program funded by NSF
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 an REU project that I worked on with Dr. Battle and Dr. Moritz in Summer 2021. Keep an eye out for the extended version of the work, to be done and submitted in Fall 2022! ]
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: Dr. 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!)
v22.12.31
My Erdös number is 3
[ Erdös - Michael Stonebraker - Leilani Battle - Me ]