Profile — Chakkrit Termritthikun (placeholder)

Chakkrit Termritthikun, PhD

Assistant Director for Digital Innovation & Assistant Professor
School of Renewable Energy and Smart Grid Technology (SGtech), Naresuan University
Phitsanulok, Thailand, 65000

EDUCATION

Naresuan University, Thailand · 2017 – 2021

PhD in Computer Engineering

  • Advisor: Professor Dr Paisarn Muneesawang (Mahidol University)
  • Co-Advisor: Associate Professor Dr Ivan Lee (University of South Australia)
  • Dissertation: Development of deep learning neural network for on-device mobile processing

Naresuan University, Thailand · 2014 – 2017

M.Eng. (Computer Engineering)

  • Advisor: Associate Professor Dr Surachet Kanprachar
  • Thesis: Large scale Thai food image recognition using deep neural network on smartphone

Naresuan University, Thailand · 2013

B.Eng. (Computer Engineering)

  • Advisor: Dr Settha Thangkawanit
  • Project: Tracking and time approximation system for EV via Smart phone on network 3G

SCHOLARSHIPS

EXPERIENCE & PROFESSIONAL SERVICE

Assistant Professor — SGtech, Naresuan University · 2023 – Present

Assistant Director for Digital Innovation — SGtech, Naresuan University · 2023 – Present

Guest Editor — Frontiers in Artificial Intelligence / Big Data · 2024

Special Topic: Exploring the Power of AI and ML in Smart Grids: Advancements, Applications, and Challenges

Reviewer — IEEE Access, TAI, TCE, TCDS, TCYB, TEVC, TII, TNNLS, TRPMS; ESWA, EAAI, Ecological Informatics, Neural Networks

Member — IEEE · 2022 – Present

Lecturer — SGtech, Naresuan University · 2021 – 2023

Visiting Student Research — STEM, University of South Australia, Australia · 2018 – 2020

A Fast-Neural Architecture Search using an Evolutionary Algorithm.

Senior Developer — Fiber One Public Co., Ltd, Bangkok, Thailand · 2016 – 2017

Developed on-device facial verification using deep learning for an automatic door (Autodoor) to replace fingerprint access.

Teaching Assistant — Naresuan University, Thailand · 2012 – 2013

Computer Programming; Advanced Computer Programming; Computer and Data Communications

TECHNICAL SKILLS

Most experienced with Python, C++, Java, PHP, SQL, Linux, and Git.

Linux server Machine learning Computer vision Convolutional Neural Network Deep learning (PyTorch, Caffe, Torch7, Keras, Tensorflow) Supercomputer & High-Performance Computing Docker & Container Neural Architecture Search Android Programming

TEACHING COURSES (Postgraduate)

RESEARCH PROJECTS

PUBLICATIONS — JOURNALS (Full List)

  1. Dorji, K., Jittanon, S., Prompook, T., Muna, Y. B., & Termritthikun, C. (2025). Short-Term Electricity Demand Forecasting Based on Cloudy and Clear Sky Solar Irradiance Data. Engineering, Technology & Applied Science Research, 15(4), 25889–25894.
  2. Prompook, T., Jittanon, S., Phumeesut, K., Termritthikun, C., Ketjoy, N., Chamsa-Ard, W., ... & Suriwong, T. (2025). Impact of distance measures in adaptive K-means clustering on load profiles and spatial patterns of distributed substations in Thailand. Scientific Reports, 15(1), 21123. [ISI]
  3. Kulkarni, V., Sahoo, S. K., Nemade, B., Kallam, S., & Termritthikun, C. (2025). Exploring the power of AI and ML in smart grids: advancements, applications, and challenges. Frontiers in Artificial Intelligence, 8, 1615547. [ISI]
  4. Termritthikun, C., Umer, A., Suwanwimolkul, S., & Lee, I. (2025). Semi-PKD: Semi-supervised Pseudoknowledge Distillation for saliency prediction. ICT Express, 11(2), 364–370. [ISI]
  5. Dorji, K., Jittanon, S., Thanarak, P., Mensin, P., & Termritthikun, C. (2024). Electricity Load Forecasting using Hybrid Datasets with Linear Interpolation and Synthetic Data. Engineering, Technology & Applied Science Research, 14(6), 17931–17938. [Scopus]
  6. Jittanon, S., Mensin, Y., Ketjoy, N., & Termritthikun, C. (2024). Net Metering Prediction in Prosumer Building with Temporal Fusion Transformer Models. IEEE Access. [ISI]
  7. Termritthikun, C., Umer, A., Suwanwimolkul, S., Xia, F., & Lee, I. (2024). SalNAS: Efficient Saliency-prediction Neural Architecture Search with self-knowledge distillation. Engineering Applications of Artificial Intelligence, 136, 109030. [ISI]
  8. Termritthikun, C., Umer, A., Suwanwimolkul, S., Xia, F., & Lee, I. (2023). Explainable Knowledge Distillation for On-Device Chest X-Ray Classification. IEEE/ACM Transactions on Computational Biology and Bioinformatics. [ISI]
  9. Termritthikun, C., Jamtsho, Y., Muneesawang, P., Zhao, J., & Lee, I. (2023). Evolutionary neural architecture search based on efficient CNN models population for image classification. Multimedia Tools and Applications, 82(16), 23917–23943. [ISI]
  10. Prasatsap, U., Nernchad, N., Termritthikun, C., Srita, S., Kaewchum, T., & Somkun, S. (2023). Comparison of Control Configurations and MPPT Algorithms for Single-Phase Grid-Connected Photovoltaic Inverter. Advances in Electrical & Computer Engineering, 23(2). [ISI]
  11. Umer, A., Termritthikun, C., Qiu, T., Leong, P. H., & Lee, I. (2022). On-Device saliency prediction based on Pseudoknowledge distillation. IEEE Transactions on Industrial Informatics, 18(9), 6317–6325. [ISI]
  12. Termritthikun C, Jamtsho Y, Ieamsaard J, Muneesawang P, Lee I. EEEA-Net: An Early Exit Evolutionary Neural Architecture Search. Engineering Applications of Artificial Intelligence. 2021. [ISI]
  13. Termritthikun C, Jamtsho Y, Muneesawang P. An improved residual network model for image recognition using a combination of snapshot ensembles and the cutout technique. Multimedia Tools and Applications. 2020;79(1–2):1475–95. [ISI]
  14. Termritthikun C, Muneesawang P. NU-LiteNet: Mobile Landmark Recognition using Convolutional Neural Networks. ECTI Transactions on Computer and Information Technology (ECTI-CIT). 2019;13(1):71–8. [Scopus]
  15. Termritthikun C, Jamtsho Y, Muneesawang P. On-device facial verification using NUF-Net model of deep learning. Engineering Applications of Artificial Intelligence. 2019;85:579–89. [ISI]
  16. Termritthikun C, Kanprachar S. NU-ResNet: Deep Residual Networks for Thai Food Image Recognition. Journal of Telecommunication, Electronic and Computer Engineering (JTEC). 2018;10(1–4):29–33. [Scopus]
  17. Termritthikun C, Muneesawang P, Kanprachar S. NU-InNet: Thai Food Image Recognition Using Convolutional Neural Networks on Smartphone. JTEC. 2017;9(2–6):63–7. [Scopus]
  18. Termritthikuna C, Tangkawanit S, Kanprachar S. DATA AND ENERGY USAGE REDUCTION FOR LIVE STREAMING ON SMART PHONE USING FUZZY LOGIC. JURNAL TEKNOLOGI. 2016;78(5–9):35–40. [Scopus]
  19. Settha Thangkawanit, Wanchaleam Chansong, Witsawa Namwong, Chakkrit Termritthikun, Kritsana Wataniyanon, Suwit Kiravittaya. Arrival time approximation and tracking of NU-EV via wireless network. Naresuan University Engineering Journal, Vol.8(21–29). [TCI]

PUBLICATIONS — CONFERENCES (Full List)

  1. Jittanon, S., Prompook, T., Phumeesut, K., Suriwong, T., Ketjoy, N., & Termritthikun, C. (2024, October). Photovoltaic Surface Environmental Contaminant Detection Based on Saliency Prediction. In 2024 IEEE International Smart Cities Conference (ISC2) (pp. 1–4). IEEE.
  2. Jittanon, S., Mensin, Y., & Termritthikun, C. (2023, March). Intelligent forecasting of energy consumption using temporal fusion transformer model. In 2023 IEEE International Conference on Cybernetics and Innovations (ICCI) (pp. 1–5). IEEE.
  3. Prasatsap, U., Nernchad, N., Srita, S., Kaewchum, T., Termritthikun, C., & Somkun, S. (2023, May). Parameters Influence on MPPT Efficiency for Single-Phase Grid-Connected Photovoltaic System. In 2023 20th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) (pp. 1–4). IEEE.
  4. Wannaphat, K., Museh, A., Jinasa, T., Prasatsap, U., Thanarak, P., & Termritthikun, C. (2022, December). PIRSE: Plant Identification and Repository for the Smart Environment. In 2022 26th International Computer Science and Engineering Conference (ICSEC) (pp. 78–83). IEEE.
  5. Termritthikun C, Xu L, Liu Y, Lee I. Neural Architecture Search and Multi-Objective Evolutionary Algorithms for Anomaly Detection. In 2021 International Conference on Data Mining Workshops (ICDMW) 2021 Dec 7 (pp. 1001–1008). IEEE.
  6. Termritthikun C, Jamtsho Y, Lee I, Morien R, Muneesawang P. Towards a New Ultra-High-Speed Search Algorithm for Convolutional Neural Networks. In KSII The 11th International Conference on Internet (ICONI), Hanoi, December 2019.
  7. Termritthikun C, Kanprachar S. Accuracy improvement of Thai food image recognition using deep convolutional neural networks. In Electrical Engineering Congress (iEECON), 2017 International 2017 Mar 8 (pp. 1–4). IEEE.
  8. Tangkawanit S, Termritthikun C, Kanprachar S. Electric vehicle tracking and notification application for smart phones. In Electrical Engineering Congress (iEECON), 2014 International 2014 Mar 19 (pp. 1–4). IEEE.

PUBLICATIONS — POSTERS (Full List)

COMPETITIONS (KAGGLE)

Top 8% Bronze (Placed 95th of 1314 Teams) — Google - American Sign Language Fingerspelling Recognition https://www.kaggle.com/competitions/asl-fingerspelling