ดร.ภัทร คุ้มพร้อม

ประวัติการศึกษา

  • Bachelor of Electrical Engineering (Electrical Power Engineering)          2012
    Prince of Songkla University (PSU), Hat Yai, Thailand
  • Master of Science in Engineering Management                                         2014
    Robert Morris University (RMU), Pittsburgh, Pennsylvania
  • Industrial Engineering Attended Ph.D. program for one semester then **transferred** to NDSU in August, 2017
    Wichita State University (WSU), Wichita, Kansas                                                                           
  • Doctor of Philosophy (Ph.D.) in Industrial Engineering                             2022
    North Dakota State University (NDSU), Fargo, North Dakota                                                          

ประกาศนียบัตรและการอบรม

Practical Data Mining with RapidMiner Studio 7 training (June, 2016)

Trained by: Eakasit Pacharawongsakda (PhD), a Certified RapidMiner Analyst

Training Details:

  • The introduction of the software RapidMiner Studio 7.
  • Data conversion techniques discretization
  • Association Rules and FP Growth Technique
  • Segmentation data (clustering), K-Means, DBScan, and Application area
  • Classification and Modelling technique (Regression, Naïve Bayes, Decision Tree, KNN, Neural Networks, SVM)
  • T-Test
  • Introduction to Text Mining and Image Processing

Advanced Predictive Modeling with R and RapidMiner Studio 7 (Aug, 2016)

Trained by: Eakasit Pacharawongsakda (PhD), a Certified RapidMiner Analyst

Training Details:

  • The model for classifying data infrastructure. And performance measurement models
  • Introduction to the R programming language for creating graphs and models.
  • Data management is characterized by sampling different Imbalance.
  • Management attributes are not unnecessarily duplicated and Attribute Selection different ways.
  • The optimization model used by many. Technical collaboration with Ensemble ways.
  • Search parameters (parameter) of appropriate techniques by means of optimization.

Practical 3D Simulation for Industrial Design with Flexsim (December 2021)

Trained by: Nara Samattapapong (PhD), IE Thai Software Co., Ltd.

Training Details:

  • 3D and 2D Objects in Flexsim
  • Basic Process Flow
  • 3D Model and 2D Logic

Advanced 3D Simulation for Industrial Design with Flexsim (January 2022)

Trained by: Nara Samattapapong (PhD), IE Thai Software Co., Ltd.

Training Details:

  • Advanced 3D Model Building
  • Advncae Process Flow
  • Statistical Analysis from Simulated Model
  • Advanced Flexsim 3D Model Libraries
  • Realtime 3D Model and Data Analysis

ประวัติการทำงาน

King Mongkut’s University of Technology Thonburi,

Bangkok, Thailand (March, 2023 – Present)

Position: Lecturer

Full-Time – Graduate School of Management and Innovation

  • Under Logistics and Supply Chain Management program
  • Focus on Inventory and Demand Management, Supply Chain Simulation Modeling, and Big Data for Supply Chain Management topics

Prince of Songkla University,

Hat Yai, Thailand (June, 2022 – March, 2023)

Position: Lecturer

Full-Time – Department of Industrial and Manufacturing Engineering (June – November, 2022)

  • Ongoing 3 research projects – 1 project with National Research Council of Thailand (NRCT) and 2 projects under Fundamental Fund (FF)
  • Take part in ABET program development team
  • Act as department’s Information Technology (IT) committee to help on suggesting and allocating funds for IT improvement plan
  • Establish relationship with international universities such as Robert Morris University, USA and North Dakota State University for student exchange programs, academic research, and 4+1 integrated accelerated Bachelor + Master programs.
  • Lecture courses: 225-443 Industrial Project Management, and 225-231 Engineering Statistic

Part-Time – Innovation Engineering and Management (International) Program (November, 2022 – March, 2023)

  • Lecture course: 234-551 Introduction to Artificial Intelligence

CMKL University,

Bangkok, Thailand (July – September, 2021).

Position: Research Coordinator

  • Assist with the daily activities of the supervisor and related members including project management and execution of strategic planning.
  • Assist with the planning and organization of meetings.
  • Responsible for the preparation of documents, reports, and other management information as required.
  • Copy and distribute the meeting minutes to all relevant people as detailed in the participants’ section.
  • Plan, manage and deliver our projects in accordance with a planned schedule and best-practice project management.
  • Analyze requirements and ensure that proposals meet requirements
  • Write and edit proposals, including creating templates and boilerplate text and draft proposals and communicate across teams to get input and meet deadlines
  • Ensure the smooth and efficient day-to-day operation of research and data collection activities; act as the primary administrative point of contact for internal research staff and as the operational liaison for other research organizations, funding agencies, and regulating bodies.
  • Monitor and report the progress of research activities as required by investigators, administrators, funding agencies, and/or regulatory bodies.

North Dakota State University,

Fargo, North Dakota, USA (January – May, 2017)

Position: Research and Teaching Assistant

  • Reinforce lessons presented by university’s instructors/professors for Production and Inventory Control class at Industrial and Manufacturing Department, North Dakota State University
  • Enforce university and class rules to help teach students proper behavior
  • Help university’s instructors/professors with record keeping, such as tracking attendance and calculating grades
  • Help university’s instructors/professors prepare for lessons by getting materials ready or setting up equipment, such as computers
  • Help supervise students in and between class
  • Research focus on Data Mining, Data Analytics, Predictive Analysis Modeling, and Data Visualizing, for Reliability Engineering and Prognostic and Health Management (PHM) applications

Wichita State University,

Wichita, Kansas, USA (August, 2017 – June, 2021)

Position: Research Assistant

  • Conducting research in the area includes multifidelity modeling, analysis, and design optimization of complex engineered systems, with applications on electrical power and energy systems
  • Being a member of the RELIABILITY ENGINEERING AUTOMATION LABORATORY (REAL) team of Industrial, Systems, and Manufacturing Engineering department, reviewing and conducting researches in various area of engineering perspectives
  • Also focusing on some areas of Data Mining, Data Analytics, Predictive Analysis Modeling, and Data Visualizing, within reliability research areas

Hoei Electronics (Thailand) Company Limited (Fuji Electric Affiliate),

Bangkok, Thailand (February – June, 2016).

Position: Technical Sales Engineer

  • Focusing on electronics manufacturing components markets, searching for new clients who might benefit from company products or services and maximizing client potential in designated regions
  • Developing long-term relationships with clients, through managing and interpreting their requirements
  • Negotiating tender and contract terms and conditions to meet both client and company needs

Esso (Thailand) Public Company Limited (ExxonMobil Affiliate),

Bangkok, Thailand (February – December, 2015).

Position: Territory Manager

  • Execute industrial & commercial business plan for the territory/segment to achieve stewardship commitments
  • Manage portfolio of accounts to achieve sustainable profitability and expand fuels sales to prospecting customers
  • Develop sales strategies and relationships for strategic accounts and key market segments
  • Coordinate sales activities to ensure alignment with the company’s Safety, Health & Environment and Control policies and guidelines
  • Manage and resolve on-site operational issues
  • Achieve high customer/dealer satisfaction through value-added services and customer relationship management
  • Timely manage and settle enquiries, disputes, claims and complaints associated with the business
  • Calculating client quotations and administering client accounts
  • Providing pre-sales technical assistance and product education
  • Working on after-sales support services and providing technical back up as required
  • Analyzing costs and sales
  • Preparing reports for head office and keeping customer records
  • Meeting regular sales targets and coordinating sales projects
  • Supporting marketing activities by attending trade shows, conferences and other marketing events
  • Making technical presentations and demonstrating how a product meets client needs

Rasika Property Company Limited,

Bangkok, Thailand (April, 2013 – June, 2016). *work Full-time from April to July 2013 —- work Part-time from December 2015 to June 2016

Position: Business Research and Development Specialist

  • Worked with the business researcher team of Rasika Property Co., Ltd.
  • Conducted a research project analyzing the data of the overall house selling in Thailand and make a prediction of the future house selling trend base on the past data.
  • Updated the overall house selling data and house selling situation in Thailand for each quarter.

ผลงานที่ตีพิมพ์/การประชุมวิชาการ

PUBLICATIONS

  • Khumprom, P.*, & Yodo, N. (2019). A data-driven predictive prognostic model for lithium-ion batteries based on a deep learning algorithm. Energies12(4), 660. DOI: 3390/en12040660
  • Khumprom, P.*, & Yodo, N. (2019, January). Data-driven Prognostic Model of Li-ion Battery with Deep Learning Algorithm. In 2019 Annual Reliability and Maintainability Symposium (RAMS)(pp. 1-6). IEEE. DOI: 1109/RAMS.2019.8769016
  • Khumprom, P.*, Grewell, D., & Yodo, N. (2020, January). Neural Networks Based Feature Selection Approaches for Prognostics of Aircraft Engines. In 2020 Annual Reliability and Maintainability Symposium (RAMS)(pp. 1-7). IEEE. DOI: 1109/RAMS48030.2020.9153598
  • Khumprom, P.*, Grewell, D., & Yodo, N. (2020). Deep Neural Network Feature Selection Approaches for Data-Driven Prognostic Model of Aircraft Engines. Aerospace7(9), 132. DOI: 3390/aerospace7090132
  • Khumprom, P. *, Davila-Frias, A., Grewell, D., & Buakum, D. (2023, January). A Hybrid Evolutionary CNN-LSTM Model for Prognostics of C-MAPSS Aircraft Dataset. In 2023 Annual Reliability and Maintainability Symposium (RAMS)(pp. 1-8). IEEE. DOI: 1109/RAMS51473.2023.10088251
  • Davila-Frias, A., Khumprom, P. *, & Yadav, O. P. (2023, January). Reliability Estimation Using Long Short-Term Memory Networks. In 2023 Annual Reliability and Maintainability Symposium (RAMS)(pp. 1-6). IEEE. DOI: 1109/RAMS51473.2023.10088225
  • Khumprom, P. *, Davila-Frias, A., Sirivongpaisal, N., Buakum, D., Jindakul, J., Suwatcharachaitiwong, S., & Treeranurat, L. (2023, October). The Stock-flow Classification Model Using Ensemble Machine Learning Approach for Particle Board Inventory. In 23rd Asia Pacific Industrial Engineering & Management System Conference (APIEMS)(pp. 98-100). UKM-Graduate School of Business (UKM-GSB) Universiti Kebangsaan Malaysia. e ISBN: 978-967-17856-1-4
  • Davila-Frias, A., Yodo, N., Yadav, O. P., & Khumprom, P.* (2024). Probabilistic modeling of hardware and software interactions for system reliability assessment. Quality Engineering, 36(1), 131. DOI: 1080/08982112.2023.2274563
  • Muanchang, S., Wepulanon, P., Khumprom, P., & Davila-Frias, A. (2024, June). Diesel Price Prediction Models with Traditional Time-Series Algorithms and Neural Networks. In 2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE)(pp. 246-252). IEEE. DOI: 1109/JCSSE61278.2024.10613626

ACADEMIC ACTIVITIES

Academic Conference Attendances

  • IEEE Symposium Series on Computational Intelligence Conference – SSCI 2014, Orlando, Florida, USA
  • The Florida Artificial Intelligence Research Society Conference – FLAIRS 2017, Marco Island, Florida, USA
  • International Conference on Digital Information Management – ICDIM 2018, Berlin Germany
  • Annual Reliability & Maintainability Symposium – RAMS 2019, Orlando, Florida, USA
  • Institute of Industrial and Systems Engineers – IISE 2019, Orlando, Florida, USA
  • Annual Reliability & Maintainability Symposium – RAMS 2020, Palm Springs, California, USA
  • Annual Reliability & Maintainability Symposium – RAMS 2021, Orlando, Florida, USA
  • Asia Pacific Industrial Engineering & Management System Conference – APIEMS 2023, Kuala Lumpur, Malaysia
  • Annual Meeting of the Association for Computational Linguistics – ACL 2024, Bangkok, Thailand

Invited as Journal Reviewer

ElsevierSince 2019

  • Reliability Engineering & System Safety (JRESS & RESS) 13 articles:
    • Direct remaining useful life assessment for electric equipments using short-time Fourier transform and deep convolution neural network (2019)
    • Remaining Useful Lifetime Prediction via Deep Domain Adaptation (2019)
    • Life prediction of lithium-ion batteries based on stacked-de-noising autoencoder (2020)
    • Prognostics and Health Management (PHM) where are we and where do we (need to) go in theory and practice (2021)
    • A Systematic Guide for Predicting Remaining Useful Life with Machine Learning (2022)
    • A Prescriptive Dirichlet Power Allocation Policy with Deep Reinforcement Learning (2022)
    • Impedance based data driven prognostics for early state estimations and cross battery predictions of lithium-ion batteries (2022)
    • Explainability-driven model improvement for SOH estimation of Lithium-ion battery (2022)
  • Advanced Engineering Informatics (ADVEI) 8 articles
    • A Novel Long-term Degradation Trends Predicting Method for Multi-Formulation Li-ion Batteries Based on Deep Reinforcement Learning (2021-2022)
    • Intelligent machinery health prognostics under variable operation conditions with limited and variable-length data (2022)
    • Joint state-of-health and remaining-useful-life prediction based on multi-level long short-term memory model prognostic framework considering battery cell voltage inconsistency reflected health indicators (2022)
    • Multi-feature spaces cross adaption transfer learning-based bearings piece-wise remaining useful life prediction under unseen degradation data (2023)
  • Energy Reports (EGYR) 7 articles
    • A new predictive energy management system: Deep Learned Type-2 Fuzzy system based on Singular Value decommission (2021)
    • Theoretical investigation and implementation of PEM fuel cell into UAV (2022)
    • A Review on Recycling of Spent Lithium-Ion Batteries (2023)
    • Integrating Ensemble Learning and Meta Bagging Techniques for Temperature-Specific State of Health Prediction in Lithium-Ion Batteries (2024)
  • Mechanical Systems and Signal Processing (YMPSS & MSSP) 1 article
    • A Novel Hierarchical Attention Model Fusing Statistical and Deep Features for RUL Estimation (2021)
  • Advances in Electrical Engineering, Electronics and Energy (e-Prime) 5 articles
    • Application of Machine Learning Algorithms in Prognostics and Health Monitoring of Electronic Systems: A Review (2022)
    • Natural Esters as Sustainable Alternating Dielectric Liquids for Transformer Insulation System: A Brief Review (2023)
    • Optimal design of a BLDC Motor Using African Vulture Optimization Algorithm (2023)
    • Using Machine Learning Algorithms for Predicting the Production of Utility Scale PV Power Plant (2023)
    • Optimal design of a BLDC Motor Using African Vulture Optimization Algorithm (2024)
  • Energy (EGY) 4 articles
    • Lithium-ion battery remaining usable life prediction and health status diagnosis based on deep extreme learning machine algorithm and enhanced grey wolf optimization method (2024)
    • Structure Optimization of Intercooler Bionic Fins Based on Artificial Neural Network and Genetic Algorithms (2024)
    • Volatility spillover between carbon market and related markets in time-frequency domain based on BEKK-GARCH and complex network analysis (2024)

The Institute of Electrical and Electronics Engineers (IEEE) Since 2019

  • IEEE Transactions on Reliability (TR) – 2 articles
    • Aero-Engine Gas-Path Performance Prognostic Model Based on Long Short Term Memory Neural Network (2019)
    • A Generic Tool Condition Monitoring System under Dynamic Operating Profile (2019)
  • IEEE Transactions on Systems, Man and Cybernetics: Systems (SMCA) – 2 articles
    • Bayesian Deep Learning based Prognostic Model for Equipment without Label Data Related to Lifetime (2021)

 

Springer Nature Since 2021

  • Scientific Reports – 3 articles
    • Remaining Useful Lifetime Prediction via Deep Domain Adaptation (2021)
    • An agile, data driven approach for target selection in rTMS therapy for anxiety symptoms: Proof of concept and preliminary data for two novel targets (2022)
    • Advancing Aircraft Engine RUL Predictions: An Integrated Approach of Feature Engineering and Aggregated Feature Importance with Cross-Validation (2023
  • Welding in the World (WITW) 1 article
    • A Comparison of Heuristic, Statistical, and Machine Learning Methods for Heated Tool Butt Welding of Two Different Materials (2022)
  • The Journal of Supercomputing 1 article
    • Union-net: Lightweight deep neural network model suitable for small data sets
  • Energy, Ecology and Environment 1 article
    • Lithium-Ion Battery Remaining Useful Life Prediction: A Federated Learning-based Approach (2024)

ความสนใจ/ความเชี่ยวชาญ

Universities’ Tennis Club Member, at PSU and NDSU since 2008

  • Joined universities’ tennis sports clubs when in both Prince of Songkla University (PSU), Thailand and North Dakota State University (NDSU), USA to participate in the club activities and completions as well as leisure matches and practices

PSU Undergraduate International Study Visit Program

at Otto von Guericke University of Magdeburg, Magdeburg, Germany (14th – 22nd October 2009)

  • Attended the two-week International Study Visit Program (Highly selective program) in Logistic Engineering cooperated by the Department of Engineering, Prince of Songkla University, Hat Yai, Thailand.

PSU English Debater,

at Mahidol University International College EUTH Competition, Bangkok, Thailand (26th – 30th August 2011).

  • Member of the university’s debate team as a debater in the 7th European Union Thailand National Intervarsity English Debate Championship.

PSU International Representative for International Seminar,

at the State University of Medan–UNIMED, Medan, Indonesia (22nd November – 1st December, 2011).

  • Nominated by the university as a member of the presentation team in the International Seminar on “Character Building through Local Wisdom.”
  • Participated in the global IEEE conference as an attendee. Observed the doctoral journal/research presentations about the Applications of Computational Intelligence related to the various fields.

CEO for One Month Candidate

at Adecco Group, Bangkok, Thailand (May, 2015)

  • Semi-finalist Candidate of the Adecco Thailand-CEO for One Month project. This project seeks talented young-blood professional workers to join the CEO-Top Level Management team of Adecco group regional.

อาจารย์ท่านอื่น

ผศ. ดร.วรพจน์ อังกสิทธิ์

ผศ. ดร.ทิพวรรณ ปิ่นวนิชย์กุล

ผศ. ดร.จิรศิลป์ จยาวรรณ

รศ. ดร.เจริญชัย โขมพัตราภรณ์

ผศ. ดร.มงคล อัศวดิลกฤทธิ์

ผศ. ดร.ปฏิภาณ แซ่หลิ่ม

ดร.บุญเกียรติ เอี้ยววงษ์เจริญ

ดร.ดั้นดุสิต โปราณานนท์

ผศ. ดร.ปารเมศ วรเศยานนท์

ผศ. ดร.ทวีศักดิ์ กฤษเจริญ

รศ. ดร.ชุมพล มณฑาทิพย์กุล

ผศ. ดร.วัชรพจน์ ทรัพย์สงวนบุญ

ผศ. ดร.กานดา บุญโสธรสถิตย์

ผศ. ดร.พงษ์ชัย อธิคมรัตนกุล

ผศ. ดร.วรัญญา ติโลกะวิชัย

ดร.รังสรรค์ เกียรติ์ภานนท์

ดร.สุจิต พงษ์นุ่มกุล

ดร.กฤษฎา จุติมงคลกุล

ผศ. ดร.ศุภชาต เอี่ยมรัตนกูล

ผศ.ศุภวัชร์ มาลานนท์

ดร.อลิสา คงทน