Professional Portfolio

PJirayu at ICCE-TW-22 conf

Jirayu (Jonathan) PETCHHAN

Lecturer

Status: He is currently a Lecturer with Computer Engineering at King Mongkut's Institute of Techology Ladkrabang after received his D.Phil. degree in Electrical Engineering (EE) with College of Electrical Engineering and Computer Science (EECS) at National Taiwan University of Science & Technology (Taiwan Tech; NTUST), Taipei city, Taiwan, R.O.C., 106

Interests: deep transfer/transductive learning, computer vision, edge intelligence, edge computing, computational intelligence, and man-machine systems

My social contacts & academic works

Facebook

Github repository

Academic publication lists

(Google scholar) | (Scopus) | (ORCID)

Linkedin

Experience

Participating Exemplary Projects

For practical work, Jirayu had served as a full-time system engineer with Contrologic Co., Ltd. for two years. He and his SE team, with Guangxi Construction Engineering Group Co., Ltd. (GXYA-China) and Braunschweigische Maschinenbauanstalt AG (BMA-Germany), successfully established the ABB 800xA process control systems at Guangxi Nanning East Asia Sugar, Chongzuo, Nanning, China, P.R.C. Moreover, he with his team formed up the centralized control systems at Ansell (Thailand) plant and he with Toyo Korea Thailand Ltd. established the gas detection system for new production plant in Bangkok Synthetics Co., Ltd.

For academic endeavors, Jirayu received his B.E. (Control Eng.-Hons. I) & M.E. (Instrumentation Eng.) at school of engineering, KMITL, Thailand, in 2017 and 2019, respectively. And recently, he completed pursuing his D.Phil. degree in Electrical Eng., CEECS, Taiwan Tech, from Sep '20 to Jan '24 (by 3.5 years). By his interests of the study related to deep learning/model compression utilizing GPU single/parallel computing as a computer-aided learning. His purpose to assess the current state of computational intelligence studies and propose innovative insights to be capable of valuable publications, and joined notable int'l conferences, like ICCE-TW/ICETA. Besides, while undertaking Blockchain coursework, he and his colleague presented the mini-project of monster games developed based on ERC-20 for in-game currency and ERC-721 for in-game non-fungible items. Example. He collaborated with graduate students in business management/engineering from Taipei Tech, assisting in thorough studies since conceptualization to computation pipeline modeling, e.g., 2D-to-3D regenerative and projects' success predictive frameworks.

Examples of Some Periodicals & New Upcoming Work

J. Petchhan* , and S.-F. Su. "High-Intensified Resemblance and Statistic-Restructured Alignment in Few-Shot Domain Adaptation for Industrial-Specialized Employment," IEEE Transactions on Consumer Electronics, vol. 69, no. 3, pp.353-365, 2023. doi:10.1109/TCE.2023.3245821 [2022-CiteScore: 9.9 (Q1), 2022-JIF: 4.3, 2022-5Y-JIF: 3.9 (Q2), SCIE]

S. Doungtap, J. Petchhan, V. Phanichraksaphong, and J.-H. Wang*. "Towards Digital Twins of 3D Reconstructed Apparel Models with an End-to-End Mobile Visualization," Applied Sciences, vol.13, no.15, 2023. doi:10.3390/app13158571 [CiteScore: 4.5 (Q2), 2022-JIF: 2.7, 2022-5Y-JIF: 2.9 (Q2), SCIE]

J. Petchhan*, and S.-F. Su. "Self-Supervised Domain-Adaptive Learning for Self-Labeling Unknown Rice Grains during Actual Rice Transportation Process," Computers and Electronics in Agriculture, vol. 216, p.108483, 2024. doi:10.1016/j.compag.2023.108483. [2022-CiteScore: 13.6 (Q1), 2022-JIF & 5Y-JIF: 8.3 (Q1), SCIE; Top-1 ranking in categories: "Agriculture Sci-Hoticulture" on Scopus & "Agriculture, Multidisciplinary" on WoS]

J. Petchhan*, and S.-F. Su. "Advances in Inter-Edge Transfer Learning with Self-Curriculum-Labeling Adaptive Learning and Lightweight Attention," Computers and Electrical Engineering, vol. 116, p. 109201, 2024. [2022-CiteScore: 7.1 (Q1), 2022-JIF: 4.3, 2022-5Y-JIF: 3.9 (Q2), SCIE]

Proficient Facilities & Abilities

Programming: IEC61131-3/C for automation/process control designs, Python, & Solidity.

Industrial automation & network: PLC/DCS/SCADA/HMI/OPC/CommBus.

Computerized theoritical knowledge: Computer vision, transfer learning, domain adaptation/generalization, fine-tuning, test-time adaptation, federated learning, knowledge transfer, and model compression.

Computerized Implementation/Generative Tools:: Python-based APIs (Deep learning⸻DL tools: pytorch 1.x/2.x, pytorch-lightning || ML tool: scikit-learn || model interpreter: ONNX/TensorRT), generative AI tools (SD/Automatic1111).

Data processing and visualization: Python-based APIs (e.g., Pandas, NumPy, & Seaborn) and SaaS (e.g., Power BI & Visio).

Virtualization: Virtual machines/DaaS (e.g., VMware/ESXi & Oracle/VirtualBox).

Blockchain: Fundamentals of smart contract, EVM, PoW-PoS-PoH, cryptography, & ERC standards (e.g., ERC-20/721/1155).

Miscellaneous (Soft skills): Data storytelling/feature engineering/business domain knowledge/fundamental of statistics in a data science pipeline (e.g., crowdfunding/startup project).

Etc

My brief resume and some supported documents are available at Google Drive, feel free to further investigate.

Language

Thai: native

English: competent (TOEIC:725 issued recently on Jan 21, 2020)

Mandarin Chinese: beginner

Japanese: beginner