Kevin Hyekang Joo

I am a graduate student at the University of Maryland, College Park, where I work as a research assistant on projects primarily concerning computer vision and machine learning with my advisor Prof. David W. Jacobs. I am particularly interested in the areas of Video & Motion Understanding, Image Synthesis & Manipulation, Time-Series Analysis, Generative Models, Human Cognition Modeling, Few-/One-Shot Learning, and Remote Sensing.

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 view and appreciate art online (still learning!); as I try to understand it, sometimes it gives me an inspiration or an idea.
Also, as a supporter of diversity and inclusion and a believer in the power of peculiarity, I like to participate in events promoting diversity as a hobby.

Previously, I conducted research on Object Detection and Object Tracking with Dr. Mohammad Nayeem Teli from the University of Maryland, and on Data Science and Data Visualization with Dr. Leilani Battle from UWashington Interactive Data Lab (IDL), focusing on the ML-based scalable optimization aspect of projects. In addition, I have conducted research on Temporal Action Proposal Generation and Video Anomaly Detection as an affiliate research assistant with Dr. Ngan Le from the AICV Lab based in the University of Arkansas.

  • 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) and selected to serve as one of 11 student mentors for the HBCU/MI (Historically Black Colleges and Universities/Minority Institutions) Program
  • 6/22: Attends the 41st ACM SIGMOD Conference (Remote)
  • 5/22: Serves as a teaching assistant for Google Applied Machine Learning Intensive Summer Program over the summer
  • 3/22: Attends the CRA Grad Cohort Workshop for IDEALS: Inclusion, Diversity, Equity, Accessibility, and Leadership Skills (San Diego, CA)
  • 3/22: Attends the 37th CSUN Assistive Technology Conference (Anaheim, CA)
  • 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 CRA
  • 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
  • 6/19: Starts Software Engineering Internship at Amazon Web Services (AWS) in Herndon, VA
[3] Demonstration of VegaPlus: Optimizing Declarative Visualization Languages new
Junran Yang, Hyekang Kevin Joo, Sai S. Yerramreddy, Siyao Li, Dominik Moritz, Leilani Battle
ACM Special Interest Group on Management of Data (SIGMOD) Conference - Demo Track, 2022
machine learning hci
ACM SIGMOD Demo '22 statistics [h5-index: 68]: 33.8% accept
tags: scalable optimization, data visualization, dataflow, machine learning
conference / video / github / pdf / bibtex

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! ]
[2] AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation
Khoa Vo, Hyekang Joo, Kashu Yamazaki, Sang Truong, Kris Kitani, Minh-Triet Tran, Ngan Le
The British Machine Vision Conference (BMVC), 2021 (Oral Presentation)
computer vision
BMVC '21 statistics [h5-index: 75]: 40 (3.33%) oral / 437 (36.23%) accept / 1206 submissions
tags: temporal action proposal generation, activitynet
conference / github / pdf / bibtex

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.
[1] Guided Hyperparameter Tuning Through Visualization and Inference
Hyekang Joo, Calvin Bao, Ishan Sen, Furong Huang, Leilani Battle
arXiv, 2021
machine learning hci
tags: hyperparameter tuning, AutoML
pdf / bibtex

We create an AutoML tool and run evaluations on machine translation and image classification through user studies.

*PI & Co-PI are marked green on mouse-hover

**My legal name is  Kevin Hyekang Joo, but I occasionally put my name as  Hyekang Kevin Joo  on papers.


Graduate School Admissions

Department of Computer Science
University of Maryland, College Park

Student Committee Member for CS Graduate School Admissions
Spring 2022

Student Groups

Association for Computing Machinery
University of Maryland, College Park

2020-2021 2019-2020

Vice President

ALD Alpha Lambda Delta Honor Society
University of Maryland, College Park

2022-2023 2021-2022 2020-2021 2019-2020
cybersecurity Cybersecurity Club
University of Maryland, College Park



Google Applied Machine Learning Intensive Summer Program
University of Arkansas, Fayetteville

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.

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i4c Diversity & Inclusion in Computing Education (DICE)
University of Maryland, College Park

2022-2023 2021-2022
bitcamp IEEE/CVF CVPR 2022
CVPR Academy: HBCU/MI (Historically Black Colleges and Universities/Minority Institutions) Workshop

Mentor & Poster Presenter
Summer 2022

Teaching Assistant Experience

Computer Science TA @ UMD

Computer Vision (CMSC426)
Instructor: Dr. Mohammad Nayeem Teli
Spring 2022
Natural Language Processing (MSML641)
Instructor: Dr. Shabnam Tafreshi
Spring 2022
Object-Oriented Programming I (CMSC131)
Instructor: Senior Lecturer Nelson Padua-Perez
Fall 2022 Spring 2020 Fall 2019

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 Devices
Denver, CO (Remote Internship)
Summer 2020

Amazon Web Services (AWS)
Herndon, VA
Summer 2019

(It's not a typical soda!)



More About Me :) Special Thanks