Dr. Sarun Gulyanon is an Assistant Professor at CMKL University, joining in 2025. He earned his Ph.D. in Computer Science from Purdue University, specializing in neuron morphology analysis using various microscopy imaging modalities. His research interests include Computer Vision, Machine Learning, Biomedical Imaging, and Data Science. His recent work focuses on AI-driven multimodal medical imaging and computational spectroscopy for environmental microplastic analysis. Previously, he served as the Director of the Data Science and Innovation Program at Thammasat University, where he taught courses in Data Science and Machine Learning and facilitated industry-academic collaboration through work-integrated education. In addition, he collaborates with the Institute for the Promotion of Teaching Science and Technology (IPST) to develop AI courses for high school students.
[1] L. He, S. Gulyanon, M. M. Skanata, D. Karagyozov, E. S. Heckscher, M. Krieg, G. Tsechpenakis, M. Gershow, and W. D. Tracey, Jr., "Direction selectivity in Drosophila proprioceptors requires the mechanosensory channel Tmc," Current Biology, vol. 29, no. 6, pp. 945–956.e3, Mar. 2019. doi: 10.1016/j.cub.2019.02.025.
[2] N. Chotisarn, S. Gulyanon, T. Zhang, and W. Chen, "VISHIEN-MAAT: Scrollytelling visualization design for explaining Siamese Neural Network concept to non-technical users," Visual Informatics, vol. 7, no. 1, pp. 18–29, 2023. doi: 10.1016/j.visinf.2023.01.004.
[3] Thar, Aeint Shune, Seksan Laitrakun, Pattara Somnuake, Somrudee Deepaisarn, Pakorn Opaprakasit, Krit Athikulwongse, Masahiro Yamaguchi, and Sarun Gulyanon. "Enhancing microplastic classification through filter-interfered FTIR spectra using dimensionality reduction and deep learning in low-dimensional spaces." Marine Pollution Bulletin 221 (2025): 118548. DOI: 10.1016/j.marpolbul.2025.118548
[4] S. Gulyanon et al., "Denoising Raman Spectra Using Autoencoder for Improved Analysis of Contamination in HDD," in IEEE Access, 2024, doi: 10.1109/ACCESS.2024.3441824.
