Assistant Professor
Department of Electrical and Compute Engineer (ECE)
University of Texas at Dallas (UTD)
minah.lee @ utdallas.edu
[CV] | [Google Scholar] | [LinkedIn]
Assistant Professor (August 2025 - Present)
Postdoctoral Research (February 2023 - July 2025)
# Vision-based Multi-Agent System Prediction for Accurate and Energy-Efficient Computation
# Analog-to-Feature Extraction Embedded Sensor
# Cross-Layer Uncertainty-based Adaptive Sensor
Ph.D Research (August 2017 - December 2022)
# Lightweight Uncertainty Estimation for Deep Neural Object Detection at Intelligent Sensor
# Adaptive Camera Platform using Deep Learning-based Early Warning of Task Failures
# Cross-Layer Noise Analysis in Smart Digital Pixel Sensors with Integrated Deep Neural Network
# Fully Spatiotemporal Pre-processing Network for Action Detection under Rain
M.S. Research (August 2017 - December 2019)
# Automated Generation of Interface Circuit Library for Interposer based System-in-Package (SiP) Integration
B.S. Creative IT Engineering (March 2012 - February 2017)
# True Random Number Generator in 65nm CMOS Design
Ph.D. Electrical and Computer Engineering (August 2017 - December 2022)
Georgia Institute of Technology, Atlanta, GA
Advisor: Dr. Saibal Mukhopadhyay
Thesis: Reliable Sensor Intelligence in Resource Constrained and Unreliable Environment
M.S. Electrical and Computer Engineering (August 2017 - December 2019)
Georgia Institute of Technology, Atlanta, GA
Advisor: Dr. Saibal Mukhopadhyay
Thesis: Automated I/O Library Generation for Interposer based System-in-Package Integration of Multiple Heterogeneous Dies
B.S. Creative IT Engineering (March 2012 - February 2017)
Double Major in Electrical Engineering
Pohang University of Science and Technology (POSTECH), Pohang, South Korea
My research rethinks sensors as active devices that use a cross-layer approach to intelligently collect and process information.
I have developed 1) Dynamic Sensor Adaptation using real-time uncertainty-based early-warning, and proposed 2) Hardware Aware Edge Computing, an analog-to- feature extraction embedded sensor and event vision-based multi-agent system prediction. Additionally, I have designed 3) Energy-Efficient Computing Hardware through interposer-based SiP integration.
Best Poster Award (March 2025)
IEEE International Reliability Physics Symposium (IRPS 2024)
Best Demo Award (October 2023)
Jump 2.0 CogniSense 2023 Annual Review
Travel Grant for DAC PhD Forum Finalists (August 2023)
Association for Computing Machinery (ACM)
Best Paper Award (July 2022)
IEEE International Joint Conference on Neural Networks (IJCNN 2022)
Third Place for the Best Student Paper (October 2020)
IEEE Sensors 2020
Best Student Paper Nominated (October 2018)
IEEE SOI-3D-Subthreshold Microelectronics Technology Unified Conference (S3S 2018)
Best Student Paper Nominated (October 2018)
IEEE Electrical Performance of Electronic Packaging and Systems (EPEPS 2018)
Best Design Project Award (December 2015)
Department of Electrical Engineering, POSTECH
i-Lab Scholarships (March 2012 - December 2015)
Department of Creative IT Engineering, POSTECH
Technical Program Committee
IEEE/ACM Design Automation Conference (DAC’24-25)
Association for the Advancement of Artificial Intelligence (AAAI’24)
Session Chair
IEEE/ACM Design Automation Conference (DAC’24-25)
Journal / Conference Review
IEEE Transactions on Design Automation of Electronic Systems (TODAES)
Nature Communications Engineering
IEEE Computer Architecture Letters (CAL)
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS)