Nakorn Kumchaiseemak, Ph. D.
Radar ML/DL Researcher
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About ME(s) :
About ME(s) :
Hello, my name is Nakorn Kumchaiseemak (Ph.D., MIEEE) , and I am pleased to introduce myself. I received my B.Sc. degree from KMUTNB, Thailand, in 2014, followed by an M.Sc. degree in Physics from Kasetsart University, Bangkok, in 2017. In 2025, I completed my Ph.D. at the School of Information Science, Vidyasirimedhi Institute of Science and Technology (VISTEC), specializing in radar-based machine learning and deep learning. My doctoral research was conducted jointly at the Vision & Learning Lab and the Brain Lab, under the supervision of Asst. Prof Supasorn Suwajanakorn (Ph.D.) and Assoc. Prof. Theerawit Wilaiprasitporn (D.Eng., SMIEEE).
In 2023, I was a guest Ph.D. researcher with the Microwave, Signals and Systems (MS3) Group at Delft University of Technology (TU Delft), The Netherlands, under the supervision of Assoc. Prof. Francesco Fioranelli (Ph.D., SMIEEE). My work focused on radar-based head pose monitoring, supported by the Dutch Research Council (NWO) through the KLEIN RAD-ART project.
Throughout my M.Sc. and Ph.D. studies, I have authored and co-authored more than 15 publications in international journals and conferences, which led to my recognition as an Outstanding Ph.D. Student in 2023. In addition, I actively serve as a reviewer for leading IEEE journals, including IEEE Internet of Things Journal (IoTJ), IEEE Sensors Journal, IEEE Transactions on Radar Systems (TRS), and IEEE Robotics and Automation Letters (RA-L).
My research interests lie at the intersection of radar machine learning, deep learning, and federated learning, with a focus on radar–vision fusion, radar localization and mapping, and radar imaging, including SAR and ISAR. I am highly motivated to explore and contribute to cutting-edge advancements in these domains.
Academic Education(s) & Experience(s)
Academic Education(s) & Experience(s)
Ph.D. Information science and Technology (International program), VISTEC, Thailand
2018 - current (Vision and Brain lab.)
Supervisors: Dr. Supasorn Suwajanakorn, Assoc. Prof. Dr. Theerawit Wilaiprasitporn
Guest Ph.D. Researcher, MS3 group, Delft University of Technology, The Netherlands.
2023 - 2024
Supervisor: Assoc. Prof. Dr. Francesco Fioranelli
M.S. Physic, Kasetsart University, Thailand
2015-2017
Thesis: Electronic Monitoring Device for Agriculture.
Supervisor: Assoc. Prof. Dr. Chaiya Luengviriya
B.Sc Industrial Physics and Medical Instrumentation, KMUTNB, Thailand
2010-2014 (Second Class Honours)
Senior project: Uroflowmetry system
Advisor: Assoc. Prof. Dr. Surapun Yimman
Award(s) & Scholarship(s)
Award(s) & Scholarship(s)
IEEE SENSORS 2023 Student Travel Grant.
Ph.D. fully-funded scholarship issued by Siam Commercial Bank Public Company Limited (SCB) and PTT Public Company Limited.
Got offerred a Ph.D. scholarship in Physics from The Royal Golden Jubilee Ph.D. Programme (Class of 20).
Honorable mention award, KMUTNB Innovation Awards, awarded for a project of “low-cost uroflowmetry system design” by King Monkut’s University of Technology North Bangkok, Bangkok, Thailand.
Selected Project(s)
Selected Project(s)
Capturing Head Poses Using FMCW Radar and Deep Neural Networks (1).mp4Capturing Head Pose Using FMCW Radar and Deep Neural Networks (IEEE Transactions on Aerospace and Electronic Systems 2025)
This paper presents the first subject-specific head pose estimation approach using only one Frequency Modulated Continuous Wave (FMCW) radar data frame. Specifically, the proposed method incorporates a deep learning (DL) framework to estimate head pose rotation and orientation frame-by-frame by combining a Convolutional Neural Network operating on RangeAngle radar plots and a PeakConv network. The proposed method is validated with an in-house collected dataset, including annotated head movements that varied in roll, pitch, and yaw, and these were recorded in two different indoor environments. It is shown that the proposed model can estimate head poses with a relatively small error of approximately 6.7-14.4 degrees for all rotational axes and is capable of generalizing to unseen, new environments when trained in one scenario (e.g., lab) and tested in another (e.g., office), including in the cabin of a car.
Impulse-Radio UWB Self-Localization (IEEE Sensors Journal 2024)
This study introduces a simple and cost-effective localization system using a moving ultra-wideband (UWB) radar sensor and passive reflectors at fixed points. We propose a hybrid pipeline that first predicts the ranges from the sensor to the reflectors, and then predicts the radar’s position from these ranges. Two key components of the hybrid pipeline are a neural network for range prediction and an optimization-based “association” step. The neural network solves the challenge of predicting individual ranges from the mixed radar signal, while the association step matches each predicted range to its corresponding reflector using a novel regularized trilateration formulation.
DipSAR (IEEE Sensors Conference 2023)
We present a deep learning-based approach called DipSAR for reconstructing millimeter-wave synthetic aperture radar (SAR) images from sparse samples. The primary challenge lies in the requirement of a large training dataset for deep learning schemes. To overcome this issue, we employ the deep image prior (DIP) technique, which eliminates the need for a large dataset and instead utilizes only the sparse sample itself.
RA-CNN (IEEE Transactions on Geoscience and Remote Sensing, 2022)
We propose a deep learning-based approach to localizing a small moving object with a single millimeter-wave frequency-modulated continuous-wave (FMCW) radar. This pilot study establishes a new baseline for small-object tracking using FMCW and can enable tracking of small animals, such as ants inside the colony for behavior studies.
SleepPoseNet (IEEE Journal of Biomedical and Health Informatics, 2020)
This study investigates the performance of an off-the-shelf single antenna UWB in a novel application of sleep postural transition (SPT) recognition. The proposed Multi-View Learning, entitled SleepPoseNet.
Publication(s)
Publication(s)
N. Kumchaiseemak, F. Fioranelli, T. Wilaiprasitporn: Capturing Head Poses Using FMCW Radar and Deep Neural Networks , IEEE Transactions on Aerospace and Eletronic Systems 2024 .
P. Porjai, T. Panklai, N. Kumchaiseemak, W. Seelarat, S. Sangwanna, C. Chutimayanaphat, A. Bootchanont, C. Wattanawikkam, T. Rittidach, D. Boonyawan: Investigating effects of air-cold plasma jet on enzymatic activity and nutritional quality attributes of Mangosteen (Garcinia mangostana L.) juice , Innovative Food Science and Emerging Technologies 2024.
P. Kotchapansompote, N. Kumchaiseemak, K. Kaemarungsi, S. Suwajanakorn: Neural Network-based Impulse-Radio UWB radar Self-localization with Passive Reflectors, IEEE Sensors Journal 2024.
R. Assabumrungrat, N. Kumchaiseemak, J. Wang , D. Wang , P. Punpeng , F. Fioranelli, T. Wilaiprasitporn: DipSAR: Deep Image Prior for Sparse Sampled Near-Field SAR Millimeter-Wave Imaging, IEEE SENSORS Conf. 2023 (co-first authors).
N. Kumchaiseemak, I. Chatnuntawech, S. Teerapittayanon, P. Kotchapansompote, T. Kaewlee, M. Piriyajitakonkij, T. Wilaiprasitporn, S. Suwajanakorn: Towards Ant-sized Moving Object Localization using Deep Learning in FMCW Radar: A Pilot Study, IEEE Transactions on Geoscience and Remote Sensing, 2022.
M. Piriyajitakonkij, P. Warin, P. Lakhan, P. Leelaarporn, N. Kumchaiseemak, S. Suwajanakorn, T. Pianpanit, N. Niparnan, S. C. Mukhopadhyay, T. Wilaiprasitporn., SleepPoseNet: Multi-view learning for sleep postural transition recognition using UWB, IEEE Journal of Biomedical and Health Informatics, 2020.
B. Ponboonjaroenchai, J. Luengviriya, M. Sutthiopad, P. Wungmool, N. Kumchaiseemak, S. C. Müller, C. Luengviriya. Self-organization of multiarmed spiral waves in excitable media, Physical Review E, 2019.
P. Wungmool, N. Rangsi, N. Kumchaiseemak, M. Sutthiopad, C. Luengviriya. Electro-flotation harvesting of microalgae using a combination of electrode types, The Journal of Applied Science, 2019.
P. Porjai, M. Sutthiopad, K. Khaothong, M. Phantu, N. Kumchaiseemak, J. Luengviriya, K. Showalter, C. Luengviriya. Twisted scroll wave dynamics: partially pinned waves in excitable chemical media, Physical Chemistry Chemical Physics, 2019.
E. Chongsereecharoen, W. Kongsri, N. Kumchaiseemak and P. Porjai. Influence of excitability on scroll waves in a simulated excitable media, RMUTT journal, 2018.
P. Porjai, P. Wungmool, N. Kumchaiseemak, C. Luengviriya, E. Chongsereechareon and W. Kongsri. Classification of Thai Rice Seed Cultivars with Image Processing, RMUTT Journal, 2017.
N. Kumchaiseemak, T. Hormwantha, S. Suwanatus, P. Wungmool, S. Kanjai, T. Lertkitthaworn, K. Jutamanee and C. Luengviriya. Low-cost standalone multi-sensor thermometer for long time measurements, Journal of Physics: Conference Series, 2017.
B. Ponboonjaroenchai, P. Srithamma, N. Kumchaiseemak, M. Sutthiopas, S. C Müller, C. Luengviriya and J. Luengviriya. Unpinning of spiral waves from regtangular obstacles by stimulated wave trains, Journal of Physics: Conference Series, 2017.
M. Phantu, N. Kumchaiseemak, P. Porjai, M. Sutthiopas, S. C Müller, C. Luengviriya and J. Luengviriya. Generation of spiral waves pinned to obstacles in a simulated excitable system, Journal of Physics: Conference Series, 2017.
K. Khaothong, M. Sutthiopas, N. Kumchaiseemak, J. Luengviriya, J. Kanchanawarin, S. C Müller and C. Luengviriya. Effect of a modified sinusoidal forcing on spiral waves in a simulated reaction-diffusion system, Journal of Physics: Conference Series, 2017.
V. Chanchang, N. Kumchaiseemak, M. Sutthiopas and C. Luengviriya. Improvement of electrocardiogram by empirical wavelet transform, Journal of Physics: Conference Series, 2017.
B. Ponboonjaroenchai, P. Wungmool, N. Kumchaiseemak, J. Luengviriya and C. Luengviriya. Initiation of Multiarmed Spiral Waves in the Belousov-Zhabotinsky Reaction, Siam Physics Congress (SPC), 2016.
P. Srithamma, P. Wungmool, N. Kumchaiseemak, J. Luengviriya and C. Luengviriya. Control of Stimulated Wave Trains in the Belousov-Zhabotinsky, Siam Physics Congress (SPC), 2016.
P. Suwannakrua, N. Kumchaiseemak, J. Kanchanawarin, J. Luengviriya and C. Luengviriya. Elimination of Pinned Spiral Waves by On-Off Formed Electric Field in Excitable Media, Siam Physics Congress (SPC), 2016.
Research interest(s)
Research interest(s)
Radar Application
Synthetic Aperture Radar
Human-computer interaction
Optimization, ML/DL
Contact(s)
Contact(s)
Wangchan Valley 555 Moo 1 Payupnai, Wangchan, Rayong 21210 Thailand
Email : Nakorn.k_s18@vistec.ac.th,
Hobbie(s)
Hobbie(s)
I love >>>>>>>>>>>>
Kitesurfing
Badminton
Roller skate
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