Researcher · TORIS
Conduct RF signal processing research for drone-detection radar systems and develop radar simulations for system design and performance evaluation.
Professional Resume
Resume
RF signal processing and radar research, supported by a foundation in artificial intelligence and cross-domain signal analysis.
Professional Summary
RF signal processing and radar researcher at TORIS, focused on drone-detection radar systems and simulation. I received an M.S. in Interdisciplinary Studies of Artificial Intelligence from DGIST in 2026. My background connects radar and RF engineering with machine learning, biomedical signal processing, computer vision, and autonomous-driving research.
Experience
Research Intern · Visual Intelligence Lab, University of Virginia
Participated in visual intelligence and computer-vision research in the United States.
Undergraduate Researcher · Communication and Signal Processing Lab, DGIST
Republic of Korea
Research Intern · Autonomous Driving R&D Team, Sonnet AI
Republic of Korea
Undergraduate Researcher · Medical Image & Signal Processing Lab, DGIST
Republic of Korea
Education
M.S. in Interdisciplinary Studies of Artificial Intelligence
Daegu Gyeongbuk Institute of Science and Technology (DGIST)
B.S. in Computer Science
Daegu Gyeongbuk Institute of Science and Technology (DGIST)
Selected Projects
Integrated Algorithm for an Autonomous Driving Platform
Computer Vision Developer and Vision Team Lead · DGIST
Dopamine Concentration Estimation from FSCV Signals
FSCV Data Processing and Deep Learning Developer · DGIST
Personalized Nutrition Salad Startup
Co-Founder · Ministry of SMEs and Startups
Selected Publications
- S. Kang, J. Park, Y. Jeong, Y.-S. Oh, and J.-W. Choi, “Second Derivative-Based Background Drift Removal for Tonic Dopamine Measurement in Fast-Scan Cyclic Voltammetry,” Analytical Chemistry, vol. 94, no. 33, pp. 11459–11463, Aug. 2022. DOI
- S. Kang, Y. Jeong, and J.-W. Choi, “Simultaneous estimation of tonic dopamine and serotonin with high temporal resolution in vitro using deep learning,” IEEE EMBC 2023, Sydney, Australia, Jul. 2023.
- Y. Jeong†, C. Moon†, and J.-W. Choi, “Efficient Biomedical Time-series Contrastive Learning: Revisiting Taylor Expansion in Loss Optimization,” ICTC 2025, Oct. 2025.
- E. Kim†, Y. Jeong†, S. Kim, J.-W. Choi, S. Kim, and H.-J. Kim, “Resilient FSCV decoding algorithm: Domain Adaptation for Neurotransmitter Concentration Estimation for a Preclinical Study.” Under review.
† Equal contribution.
Selected Patents
- J.-W. Choi, S. Kang, Y.-S. Oh, J. Park, and Y. Jeong, “Neurotransmitter Concentration Measuring Apparatus for Providing Second Derivative-Based Neurotransmitter Concentration Measurement Result of Fast-Scan Cyclic Voltammetry Data and Method Thereof,” U.S. Patent Application No. 18/120,771, filed Mar. 13, 2023.
- J.-W. Choi, S. Kang, Y. Jeong, and E. Kim, “Neurotransmitter Concentration Measuring Apparatus for Simultaneously Providing Long-Time Measuring Results of Concentration for Various Neurotransmitters Based on Fast-Scan Cyclic Voltammetry and Method Thereof,” U.S. Patent Application No. 18/594,719, filed Mar. 4, 2024.
Core Skills
Signal & RadarRF Signal Processing, Radar Signal Processing, Radar Simulation, Sequence Processing
ProgrammingPython, C, C++
Machine LearningPyTorch, Deep Learning, Computer Vision, Domain Adaptation
PlatformsLinux, ROS
For all publications, patents, awards, and complete research details, see the full CV.