KIM-PHUC TRAN

 Education

• HDR degree (Dr. habil. , Habilitation à Diriger des Recherches )  in Automation and Computer Engineering, University of Lille, France, Thesis topic: Monitoring, Anomaly Detection, and Optimization of Industrial Systems with Statistical and Machine Learning Techniques , defended February 24, 2022 

• PhD degree in Automation and Applied Informatics, University of Nantes, France

  • Thesis topic: Monitoring of mixture type processes 

  • Period: Avril 2014 - September 2016

• DAE degree (BAC+7 ) in Automated Manufacturing Engineering  at the Program of Excellence Engineer between Vietnam and France (PFIEV), University of Science and Technology - The University of Da Nang , Vietnam

  • Thesis topic:  Two-stage helical gearbox fault detection and diagnosis based on continuous wavelet transformation of time-synchronous averaged vibration signals

  • Period: July 2009- September 2011

• Engineer degree (BAC+5 )  in Automated Manufacturing Engineering  at the Program of Excellence Engineer between Vietnam and France (PFIEV), University of Science and Technology - The University of Da Nang , Vietnam

  • Thesis topic:  Cybersecurity for Industrial Control Systems: SCADA,  PLC, and HMI

  • Period: July 2004- September 2009

Research experience

• 02/2022 : Senior Associate Professor of Artificial Intelligence and Data Science (Maître de Conférences HDR, equivalent to a UK Reader) in Division of  Automation and Industrial Informatics  at Graduate School MADIS-631, University of Lille, ENSAIT& GEMTEX, Roubaix, France.

• 09/2018-02/2022 : Associate Professor of Artificial Intelligence and Data Science in Division of Automation and Industrial Informatics  at Graduate School MADIS-631, University of Lille, ENSAIT& GEMTEX, Roubaix, France.

• 4/2019-5/2019: Visiting Researcher Scholar at University of Kent, UK.

• 3/2019-4/2019: Visiting Researcher Scholar at Ghent University, Belgium.

• 3/2017-8/2018: Visiting Researcher Scholar at the Division of Data Science, Ton Duc Thang University, Vietnam.

• 12/2017-08/2018: Postdoctoral researcher in Artificial Intelligence at LMBA, UMR CNRS 6205, Vannes, France. 

• 12/2016-11/2017 :Postdoctoral researcher in Artificial Intelligence at GIPSA-Lab, UMR CNRS 5216, Saint-Martin-d’Hères, France.

• 09/2016-11/2016: Visiting Researcher Scholar at Université de Nantes and IRCCyN, UMR CNRS 6597, Nantes, France.

• 6/2018-7/2016: Visiting Researcher Scholar with DAAD Research Grants at Helmut-Schmidt University, Hamburg, Germany.

• 5/2014-9/2016: PhD student at Université de Nantes and IRCCyN, UMR CNRS 6597, Nantes, France.

• 2/2014-4/2016: Intern at IRCCyN, UMR CNRS 6597, Nantes, France.

• 5/2013-2/2014: Lecturer at Dong A University, Department of Electronics and Electrical Engineering, Danang, Vietnam.

• 12/2009-04/2013: Lecturer at Phan Chau Trinh University, Department of Electronics and Electrical Engineering, Quangnam, Vietnam.

Qualifications and Certificates

• 02/2022 : Qualified functions of Full Professor in Computer Engineering, Automation and Signal Processing (section 61 -Génie informatique, automatique et traitement du signal), N° de qualification : 17261304997.

• 01/2017 : Qualified functions of Associate Professor in Computer Engineering, Automation and Signal Processing (section 61 -Génie informatique, automatique et traitement du signal), N° de qualification : 17261304997.

• 02/2017 : Qualified functions of Associate Professor in Applied Mathematics and Mathematical Applications (section 26 -Mathématiques appliquées et applications des mathématiques), N° de qualification : 17261304997.

Research Interests

• Explainable, Trustworthy, and Transparent Artificial Intelligence:  Self-Supervised Learning, Adversarial Machine Learning,  Anomaly Detection, Federated Learning, Federated Reinforcement Learning, 1-bit Machine Learning Models, Multimodal Deep Learning, Quantum Machine Learning, Physics-informed Machine Learning, Inverse Reinforcement Learning, Analog AI

• Ethical and Human-centered Artificial Intelligence: Human-Centered Edge AI, Embedded AI, Wearable AI Devices, Human-Centered Design to Address Biases in AI, Augmented Intelligence,  Human-Robot relations and collaborations, Human Impact, Augment Human Capabilities, and Intelligence 

• Safety and Reliability of Artificial Intelligence: Adversarial Attack Detection, Detecting Poisoning Attacks, Cybersecurity for AI Systems, Blockchain Empowered Federated Learning, Consensus Protocol, Evolutionary Computing, Swarm Algorithms

• Trustworthy AI for Robotics and Autonomous Systems:  Human-centered AI for Trustworthy Robots and Autonomous Systems, Ethical robotics, autonomous systems and AI, Responsible AI for Long-term Trustworthy Autonomous Systems

• Statistical Computing: Statistical Process Monitoring,  Advanced Control Charts, Quality Control, Interpreting out-of-control signals using Machine Learning,  Control Chart Pattern Recognition (CVPR) with Machine Learning, Screening and Early Detection and Monitoring of Infectious Diseases

• Intelligent Decision Support Systems: Embedding domain knowledge for Machine Learning, Clinical Decision Support Systems, Supply Chain Optimization, Production Optimization, Demand Forecasting,  Cybersecurity for industrial control systems, Fault Detection and Diagnostics, Predictive Maintenance, Natural Language Processing for Fashion Trends Detection

• Digital Twins: Digital Twins in Healthcare, Digital Twin Application for Production Optimization, Digital Twin Drives Smart Manufacturing

• Applications of AI, Edge Computing, and Data Science in Industry 5.0: Digital Transition and AI, Twin Green and Digital Transition, AI for Health and Wellbeing, Smart Healthcare, Smart Manufacturing, Workplace Safety Wearables, Reliability Engineering, AI-aided Knowledge Discovery,  Sustainable Fashion, Hardware Bit-Flipping Attack, Energy-Harvesting-Based IoT Wearables

Awards

• 2021-2025: Award for Scientific Excellence (Prime d'Encadrement Doctoral et de Recherche) given by the Ministry of Higher Education, Research and Innovation, France.

• 2016: DAAD Award Research Grant, German Academic Exchange Service, Germany

Academic responsabilities

• 2021- : Founder member of CybCom,  Hauts-de-France department, France

• 2020- : Member of the Executive Committee of the GEMTEX research laboratory, ENSAIT, France

• 2020- : Coordinator of Cybersecurity axis for GRAISyHM , Hauts-de-France department, France

• 2018- : Coordinator for projects of the International semester in ENSAIT

• 2020-:  Member of the Tex-CARE chair, the circular fashion chair: Industry 4.0 and Circular Economy  at the University of Lile, France

• 2018-: Head of the International Chair in Data Science and Explainable Artificial Intelligence at Dong A University & International Research Institute for Artificial Intelligence and Data Science (IAD), Vietnam

Editorial activities

• Editorial Board Member for Engineering Applications of Artificial Intelligence 

• Associate Editor  for IEEE Transactions on Intelligent Transportation Systems 

• Associate Editor  for Frontiers in Computational Neuroscience

• Editorial Board Member for Advanced Materials & Sustainable Manufacturing

• Editorial Board Member for Artificial Intelligence Evolution 

• Guest Editor for EAI Endorsed Transactions on AI and Robotics 

Expertise 

• 2017-:Senior Scientific Advisor at Dong A University & International Research Institute for Artificial Intelligence and Data Science (IAD), Vietnam

• 2019: Expert in the research project OPTIPROFIL (collaborate between the UCL Social Media Lab, UCLouvain and the University of Liège) funded by Walloon Region,  Belgium 

• 2020-: Expert and evaluator for Research and Innovation program of Government of the French Community, Belgium 

•  2022-: Expert and evaluator for the Natural Sciences and Engineering Research Council of Canada

• 2023-: Expert and evaluator for the CY Generations, CY Cergy Paris University, France

• 2023-: Expert and evaluator for the ANRT (Association Nationale de la Recherche et de la Technologie ou le dispositif des Conventions industrielles de formation par la recherche (Cifre)). 

Collaborators

• Prof. Philippe CASTAGLIOLA, Université de Nantes and LS2N, UMR CNRS 6004, France.

• Prof. Bruno Agard, Ecole Polytechnique de Montreal , Canada.

• Prof. Shujun LI, School of Computing, University of Kent, Canterbury, Kent, CT2 7NF, UK. 

• Prof. Fadel Megahed, Miami University (OH), USA.

• Prof. Giovanni CELANO, Università di Catania, Catania, Italy.

• Prof. Sven KNOTH, Helmut Schmidt University, Hamburg, Germany.

• Prof. Narayanaswamy BALAKRISHNAN, McMaster University, Hamilton, ON L8S 4K1, Canada.

• Prof. Michael KHOO, Universiti Sains Malaysia, Penang, Malaysia.

• Prof. Athanasios RAKITZIS, University of Aegean, Karlovasi, Samos, Greece.

• Prof. Petros MARAVELAKIS, University of Piraeus, Piraeus, Greece.

• Prof. El-Houssaine AGHEZZAF, Industrial Systems Optimization and Control (ISyOC), Ghent University, Belgium.

Teaching

Master's courses 

• Machine learning and Python

• Data Structures and Algorithms with Python

• Information Systems

• Product Lifecycle Management

• Supply Chain and Logistics Optimization

• Production Management and Logistics 

• Wearable Technology

Courses for Ph.D. programs at Graduate School MADIS-631, University of Lille, France

• Machine Learning 

Courses for Ph.D. programs at the South China University of Technology, China

• Artificial Intelligence for Smart Manufacturing 

Thematic school on Data Science

• 2022: 20èmes Journées d'Étude en Statistique (JES) CNRS, Fréjus, 03-07 octobre 2022

Visiting PhD Students

1. Dorra Sellami (Thesis topic: The contribution of artistic multi-mediations in the therapy of children with leukemia), Ph.D. student at Higher Institute of Arts and Crafts of Sfax,  Tunisia, from 09/2023 to 12/2023.

2. Anouare Louati (Thesis topic: Mass customization in the fashion industry), Ph.D. student at Higher Institute of Arts and Crafts of Sfax,  Tunisia, from 09/2023 to 12/2023.

Postdoc

• 09/2022-8/2023: Thu Ha DO (Project: Digital Fashion with AI )

• 5/2021-5/2022: Adel NADI (Project: Explainable Machine Learning for Anomaly Detection with Applications)

• 4/2021-3/2022: Quoc-Thong NGUYEN (Project: AI and Machine Learning For Fashion Industry )

• 1/2020-3/2021: Quoc-Thong NGUYEN (Project: Smart manufacturing with Artificial intelligence, IIoT, and Big Data )

• 7/2019-1/2020: Huu- Du NGUYEN (Project: Multi-State models: inference and applications)

 External examiner for doctoral /master defense

• Dorra RAHALI , Statistical Monitoring of Time and Amplitude between Events , PhD (Doctorat) Automatique et Informatique Appliquée, Université de Nantes, France, 24/06/2020

•  Tan Kin Leong, Optimal designs of the exponentially weighted moving average median chart based on median run length and expected median run length, Master Physical and Mathematical Science, Universiti Tunku Abdul Rahman, Petaling Jaya, Malaysia ,30/06/2020

Congress Organization

1. General Chair of the International  Workshop on Responsible Artificial Intelligence and Applications in Integrated Circuit Industry, Manufacturing, and Healthcare, December 21, 2023, Danang, Vietnam

2. General Chair of the EAI SaSeIoT 2023 - 7th EAI International Conference on Safety and Security in Internet of Things, October 24-26, 2023, Bratislava, Slovakia

3. General Chair of the Explainable Artificial Intelligence for Industry 5.0, September 5-6, 2023, Danang, Vietnam

4. Member of the Organizing Committee of the First IEEE International Conference on Medical Artificial Intelligence (IEEE MedAI 2023), November 18-19, Beijing, China

5. Program Chair of the ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2023) 

6. Member of the Organizing Committee and Chair of the First International Conference on Intelligence of things (ICIT 2022), Hanoi, Vietnam

7. Program Chair of the ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2019) 

8. Member of the Organizing Committee of the 7th Conference on Information Technology and Its Applications - CITA 2018 

9. Program Chair of the ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2020) 

10. Member of the Organizing Committee of the 8th Conference on Information Technology and Its Applications - CITA 2019 

Funding

• Below is the list of selected ongoing projects that I am a Principal Investigator (PI) or co-PI

1. XAIDS_IChair(2018-2028): International Chair in Data Science and Explainable Artificial Intelligence,  funding for the development of the International Research Institute for Artificial Intelligence and Data Science (IAD) at Dong A University, Vietnam (PI, TOTAL COST: 500 K EUR).

2. SHSFL(2020-2024): "Smart Healthcare System with Federated Learning" funded by the grant (REF LABEX/EQUIPEX), a French State fund managed by the National Research Agency under the frame program “Investissements d’Avenir” I-SITE ULNE / ANR-16-IDEX-0004 ULNE.  (PI, TOTAL COST: 211  K EUR).

3. ALRC (2019-2022):  "Artificial Intelligence and Data Science for Fashion Industry in the Big Data Era" funded by conseil régional Hauts-de-France (co-PI, TOTAL COST: 135 K EUR). 

4. CSFMAI (2020-2023):" Artificial Intelligence based Anomaly Detection in Online Process Mining " funded by Rosenberger Group (co-PI, TOTAL COST: 250 K EUR).

5. CAIRC (2020-2021): "Collaborative assessment tool with Artificial Intelligence to ensure Responsible purchasing in the Clothing industry" funded by Clear Fashion   (co-PI, TOTAL COST: 195 K EUR).

6. AIMatchMarket (2021-2022): "Machine learning for the fashion industry " funded by MatchMarket (co-PI, TOTAL COST: 35 K EUR).

7. ADIoT  (2022-2026): "Anomaly detection in IoT Multivariate Time Series data with Statistical and Machine Learning techniques " funded by the University of Liège, Belgium (Co-PI, TOTAL COST: 450  K EUR).

8. EIoTIA (2022-2023): "E‐textiles, the Internet of Things, and Artificial Intelligence with health applications " funded by the French Embassy in Vietnam (PI, TOTAL COST: 4500  EUR).

• Below is the list of selected ongoing projects that I am a member 

1. SYMPHONIES(2021-2025): "Development of digital twins for the design of products and the simulation of their impact on physiology in the field of phlebology" funded by the French National Program, partners: PSPC, SIGVARIS, TMM Software, IFTH, Ecole Nationale Supérieure des Mines de Saint-Etienne - INDA Lyon - ENSAIT (TOTAL COST: 10.54 millions EUR ). 

2. DigitalFashion(2022-2025): "Collaborative Online International Learning in Digital Fashion" funded by the ERASMUS+  research and innovation program under grant agreement N. 2021-1-RO01-KA220-HED-000031150 (TOTAL COST: 308 325 EUR ). 

3. ALRC (2022-2026):  "Regeneration and development of reinforcements based on recycled carbon fibers, optimization of parameters by numerical methods" funded by conseil régional Hauts-de-France (TOTAL COST: 135 K EUR). 

4. FBD_BModel (2017-2020): "Fashion Big Data Business MODEL " funded by the European Union’s Horizon 2020 research and innovation program under grant agreement N. 761122 (TOTAL COST: 3 763 474 EUR ). 

5. LACMC (2020-2022): "Launch and support of Tex-CARE, the circular fashion chair:  Industry 4.0 and Circular Economy" funded by conseil régional Hauts-de-France (TOTAL COST: 196 K EUR). 

Publications

2024

1. M. Imran, H.L. Dai, F.S;  Zaidi, X. Hu, K.P. Tran, and J. Sun. (2024), Analyzing Out-of-Control Signals of T2 Control Chart for Compositional Data using Artificial Neural Networks, Expert Systems With Applications, https://doi.org/10.1016/j.eswa.2023.122165 

2. J.W. Teoh, W.L. Teoh, Michael B.C. Khoo, K.P. Tran & M.H. Lee (2024) An integrated optimal-GICP design for the SPRT control chart with estimated process parameters based on the average number of observations to signal, Quality Technology & Quantitative Management, DOI: 10.1080/16843703.2024.2312010

3. S. Rita, Q.T. Nguyen, A.L. Sandra, K.P. Tran, S. Thomassey (2024). Evaluating the sales potential of new products using Machine Learning techniques and data collected from mobile applications, International Journal of Clothing Science and Technology, https://doi.org/10.1108/IJCST-07-2023-0099 

2023

1. H.D. Nguyen,  A.D. Nadi, K.D. Tran, G. Celano, P. Castagliola, K.P. Tran , (2023).The Shewhart-type RZ control chart for monitoring the ratio of autocorrelated variables, International Journal of Production Research, https://doi.org/10.1080/00207543.2022.2137594 

4. A .A. Nadi, B. S. Gildeh, J. Kazempor, K.D. Tran, K.P. Tran, (2023). Conditional reliability sampling plan for Weibull quantiles under progressive type-II censoring: Cost-effective optimization strategies, Applied Mathematical Modelling, https://doi.org/10.1016/j.apm.2022.11.004 

5. A. Raza, K.P. Tran, L. Koehl, and S. Li (2023), "AnoFed: Adaptive Anomaly Detection for Digital Health Using Transformer-Based Federated Learning and Support Vector Data Description ". Engineering Applications of Artificial Intelligence, https://doi.org/10.1016/j.engappai.2023.106051 

6. H.D. Nguyen, H.L. Nguyen, N.H. Kieu, V.H. Nguyen, T.H. Truong, K.P. Tran, (2023). Trans-Lighter: A Light-Weight Federated Learning-based Architecture for Remaining Useful Lifetime Prediction. Computers in Industry, https://doi.org/10.1016/j.compind.2023.103888 

7. F.S. Zaidi, H.L Dai, M.  Imran, K.P. Tran,(2023). Analyzing Abnormal Pattern of Hotelling T2 Control Chart for Compositional Data using Artificial Neural Networks, Computers & Industrial Engineering, https://doi.org/10.1016/j.cie.2023.109254 

8. F.S. Zaidi, H.L Dai, M.  Imran, K.P. Tran,(2023). Monitoring Autocorrelated Compositional Data Vectors using an Enhanced Residuals Hotelling T2 Control Chart, Computers & Industrial Engineering, https://doi.org/10.1016/j.cie.2023.109280 

9. A. Saghir, X. Hu, K.P. Tran, Z. Song,(2023). Optimal design and evaluation of adaptive EWMA monitoring schemes for Inverse Maxwell distribution, Computers & Industrial Engineering, https://doi.org/10.1016/j.cie.2023.109290 

10. M.  Imran, H.L. Dai, F.S. Zaidi, K.P. Tran, Z. Abbas, H.Z. Nazir, (2023). Incorporating principal component analysis into Hotelling T2 control chart for compositional data monitoring, Computers & Industrial Engineering, https://doi.org/10.1016/j.cie.2023.109755 

2022

1. A. Raza, K.P. Tran, L. Koehl, and S. Li (2022), "Designing ECG Monitoring Healthcare System with Federated Transfer Learning and Explainable AI". Knowledge-Based Systems, https://doi.org/10.1016/j.knosys.2021.107763 

2. Huong, T. T., Bac, T. P., Long, A. Q., Le, T. D., Dan, T. C., Le, X. H., & Tran, K. P. (2022). Light-Weight Federated Learning-based Anomaly Detection for Time-Series data in Industrial Control Systems. Computers in Industry, https://doi.org/10.1016/j.compind.2022.103692 

3. Huong, T. T., Bac, T. P., K.N. Ha, K.P Tran.(2022). Federated Learning-Based Explainable Anomaly Detection for Industrial Control Systems. IEEE Access, IEEE, 2022, 10, pp.53854-53872. ⟨10.1109/ACCESS.2022.3173288⟩ 

4. R.Afshari, A.D. Nadi, A.Johannssen, N.Chukhrova, K.P. Tran.(2022), The effects of measurement errors on estimating and assessing the multivariate process capability with imprecise characteristic, Computers & Industrial Engineering, 2022, https://doi.org/10.1016/j.cie.2022.108563 

5. R. Sleiman, A. Mazyad, M. Hamad, K.P. Tran, S. Thomassey, (2022). Forecasting sales profiles of products in an exceptional context: COVID-19 pandemic , International Journal of Computational Intelligence Systems, https://doi.org/10.1007/s44196-022-00161-x 

6. Z. He, K.P. Tran, S. Thomassey, X. Zeng and C. Yi (2022), "Multi-Objective Optimization of the Textile Manufacturing Process Using Deep-Q-Network Based Multi-Agent Reinforcement Learning", Journal of Manufacturing Systems, https://doi.org/10.1016/j.jmsy.2021.03.017 

7. H. D. Nguyen, K. P. Tran, S. Thomassey, M. Hamad (2022), "Forecasting and Anomaly Detection approaches using LSTM and LSTM Autoencoder techniques with the applications in Supply Chain Management", International Journal of Information Management, https://doi.org/10.1016/j.ijinfomgt.2020.102282 

2021

1. H. D. Nguyen, K. P. Tran, D. Tran (2021), "The effect of measurement errors on the performance of the Exponentially Weighted Moving Average control charts for the Ratio of Two Normally Distributed Variables ", European Journal of Operational Research, https://doi.org/10.1016/j.ejor.2020.11.042 

2. K.D. Tran, H.D. Nguyen T.H. Nguyen, K.P. Tran (2021), “Design of a Variable Sampling Interval EWMA Median Control Chart in Presence of Measurement Errors  ” Quality and Reliability Engineering International, https://doi.org/10.1002/qre.2726 

3. T.T. Huong, T.P. Bac, D.M. Long, B.D. Thang, N.T. Binh, T.D.  Luong, K.P. Tran (2021), "LocKedge: Low-Complexity Cyberattack Detection in IoT Edge Computing", IEEE Access, https://ieeexplore.ieee.org/document/9352785

4. Q T Nguyen, V Giner-Bosch, K D Tran, C Heuchenne , K.P. Tran (2021). One-sided Variable Sampling Interval EWMA Control Charts for Monitoring the Multivariate Coefficient of Variation in the Presence of Measurement Errors, International Journal of Advanced Manufacturing Technology, https://link.springer.com/article/10.1007/s00170-021-07138-8

5. Z. He, J.Xu, K.P. Tran, S. Thomassey, X. Zeng and C. Yi (2021), "Modeling of textile manufacturing processes using intelligent techniques: a review", International Journal of Advanced Manufacturing Technology, https://doi.org/10.1007/s00170-021-07444-1 

6. T.H. Truong, P.B.Ta, M.L. Dao, D.L. Tran, M.D. Nguyen, A.Q. Le, D.T. Bui, K.P. Tran (2021), "Detecting Cyberattacks using Anomaly Detection in Industrial Control Systems: A Federated Learning approach ",  Computers in Industry, https://doi.org/10.1016/j.compind.2021.103509 

7. K.D. Tran, Q. Khaliq , A.Nadi , TH.Nguyen, K.P. Tran (2021), "One-sided Shewhart control charts for monitoring the ratio of two normal variables in Short Production Runs ", Journal of Manufacturing Processes, https://doi.org/10.1016/j.jmapro.2021.07.031 

8. K.P.Tran (2021). Artificial Intelligence for Smart Manufacturing: Methods and Applications. Sensors, 21, 5584, https://doi.org/10.3390/s21165584

9. Z. He, K.P. Tran, S. Thomassey, X. Zeng and C. Yi (2020), "A Deep Reinforcement Learning Based Multi-Criteria Decision Support System for Optimizing Textile Chemical Process   ", Computers in Industry, 125 (2021): 103373. https://doi.org/10.1016/j.compind.2020.103373

2020

1. Z. He, K.P. Tran, S. Thomassey, X. Zeng and C. Yi  (2020), "Modeling Color Fading Ozonation of Reactive-Dyed Cotton Using Extreme Learning Machine, Support Vector Regression and Random Forest ", Textile Research Journal, https://doi.org/10.1177/0040517519883059

2. H.D. Nguyen, K.P. Tran and C. Heuchenne (2020), "CUSUM control charts with Variable Sampling Interval for monitoring the ratio of two normal variables", Quality and Reliability Engineering International, https://doi.org/10.1002/qre.2595

3. H.D. Nguyen, K.P. Tran and T.N Goh (2020), Variable Sampling Interval Control Charts for Monitoring the Ratio of Two Normal Variables , Journal of Testing and Evaluation, https://www.doi.org/10.1520/JTE20190327

4. H.D. Nguyen, K.P. Tran, G. Celano, P.E. Maravelakis, P. Castagliola (2020). On the effect of the Measurement Error on Shewhart-t and EWMA-t Control Charts. International Journal of Advanced Manufacturing Technology, https://doi.org/10.1007/s00170-020-05222-z 

5. H.D. Nguyen and K.P. Tran (2020), “Effect of the measurement errors on two one-sided Shewhart control charts for monitoring the ratio of two normal variables ” Quality and Reliability Engineering International, https://doi.org/10.1002/qre.2656 

6. H.D. Nguyen, H., Nguyen, Q. T., Nguyen, T. H., Balakrishnan, N., & Tran, K. P. (2020). The Performance of the EWMA Median Chart in the Presence of Measurement Error. Artificial Intelligence Evolution, 48-62, https://doi.org/10.37256/aie.112020401

7. F. Zaidi, P. Castagliola, K.P. Tran, M.C. Khoo  (2020), “Performance of the MEWMA-CoDa Control Chart in the Presence of Measurement Errors  ” Quality and Reliability Engineering International, https://doi.org/10.1002/qre.2705

2019

1. P. Castagliola, K.P. Tran, G. Celano, A.C. Rakitzis and P. Maravelakis (2019), "An EWMA-Type Sign Chart with Exact Run Length Properties", Journal of Quality Technology, 10.1080/00224065.2018.1545497 

2. P.H. Tran, K.P. Tran and A.C. Rakitzis (2019), “A Synthetic median control chart for monitoring the process mean with measurement errors” Quality and Reliability Engineering International. https://doi.org/10.1002/qre.2447

3. H.D. Nguyen, Q.T. Nguyen, K.P. Tran, Ho P.D (2019), "On the Performance of VSI Shewhart control chart for monitoring the Coefficient of Variation in the Presence of Measurement Errors", Journal of Advanced Manufacturing Technology, https://doi.org/10.1007/s00170-019-03352-7 

4. K.P. Tran, Castagliola P, T.H. Nguyen, A. Cuzol (2019), "Design of a Variable Sampling Interval EWMA Median Control Chart" , International Journal of Reliability, Quality and Safety Engineering, https://doi.org/10.1142/S0218539319500219 

5. V. Giner-Bosch, K.P. Tran, P. Castagliola, M.B.C. Khoo " An EWMA Control Chart for the Multivariate Coefficient of Variation", Quality and Reliability Engineering International, https://doi.org/10.1002/qre.2459

6. Q.T. Nguyen, K.P. Tran, P Castagliola, G. Celano, S. Lardjane (2019), "One-Sided Synthetic control charts for monitoring the Multivariate Coefficient of Variation",  Journal of Statistical Computation and Simulation, https://doi.org/10.1080/00949655.2019.1600694 

7.  F. Zaidi, P. Castagliola, K.P. Tran, M.C. Khoo (2019), "Performance of the Hotelling T2 Control Chart for Compositional Data in the Presence of Measurement Errors ", Journal of Applied Statistics, https://doi.org/10.1080/02664763.2019.1605339 

8.  Q.T. Nguyen, K.P. Tran, C. Heuchenne, T.H. Nguyen, H.D. Nguyen (2019), "Variable Sampling Interval Shewhart control charts for monitoring the Multivariate Coefficient of Variation ",  Applied Stochastic Models in Business and Industry, https://doi.org/10.1002/asmb.2472 

9. K.P. Tran, H.D. Nguyen, P.H. Tran, C. Heuchenne (2019), "On the Performance of CUSUM control charts for monitoring the Coefficient of Variation with Measurement Errors", Journal of Advanced Manufacturing Technology, https://doi.org/10.1007/s00170-019-03987-6 

10.  T.H. Truong, B. Ta, Q. T. Nguyen, H.D. Nguyen, K.P. Tran (2019), "A data-driven approach for Network Intrusion Detection and Monitoring based on Kernel Null Space", Industrial Networks and Intelligent Systems , http://dx.doi.org/10.4108/eai.13-6-2019.159801

2018

1. K.P. Tran (2018), "Designing of new Run Rules t control charts for Monitoring Changes in the Process Mean", Chemometrics and Intelligent Laboratory Systems, https://doi.org/10.1016/j.chemolab.2018.01.009 

2. K.P. Tran, P. Castagliola, G. Celano and M.C. Khoo (2018), "Monitoring Compositional Data using Multivariate Exponentially Weighted Moving Average Scheme", Quality and Reliability Engineering International, https://doi.org/10.1002/qre.2260

3.  H.D. Nguyen, K.P. Tran and C. Heuchenne (2018), Monitoring the ratio of two normal variables using variable sampling interval exponentially weighted moving average control charts. Quality and Reliability Engineering International, https://doi.org/10.1002/qre.2412 

4. K.P. Tran, C. Heuchenne, and N. Balakrishnan (2019), On the performance of coefficient of variation charts in the presence of measurement errors. Quality and Reliability Engineering International,  https://doi.org/10.1002/qre.2402

2017

1. K. P. Tran and S. Knoth (2017), "Steady-state ARL analysis of ARL-unbiased EWMA-RZ control chart monitoring the ratio of two normal variables", Quality and Reliability Engineering International, https://doi.org/10.1002/qre.2259

2. K. P. Tran (2017), "Run Rules median control charts for monitoring process mean in manufacturing", Quality and Reliability Engineering International. Vol. 33(8), pp. 2437-2450. https://doi.org/10.1002/qre.2201 

2016

1. K.P. Tran , P. Castagliola and G. Celano (2016), "Monitoring the Ratio of Population Means of a Bivariate Normal distribution using CUSUM Type Control Charts", Statistical Papers. https://doi.org/10.1007/s00362-016-0769-4 

2. K. P. Tran, P. Castagliola and G. Celano (2016), "The performance of the Shewhart-RZ control chart in the presence of measurement error", International Journal of Production Research. Vol. 54, pp. 7504-7522.https://doi.org/10.1080/00207543.2016.1198507 

3. K.P. Tran (2016), "The efficiency of the 4-out-of-5 Runs Rules scheme for monitoring the Ratio of Population Means of a Bivariate Normal distribution", International Journal of Reliability, Quality and Safety Engineering. https://doi.org/10.1142/S0218539316500200 

4. K.P. Tran, P. Castagliola and N. Balakrishnan (2016), "On the performance of Shewhart median chart in the presence of measurement errors", Quality and Reliability Engineering International. Vol. 33(5), pp. 1019-1029. https://doi.org/10.1002/qre.2087 

5. P.H. Tran and K.P. Tran (2016), "The Efficiency of CUSUM schemes for monitoring the Coefficient of Variation", Applied Stochastic Models in Business and Industry. Vol. 32(6), pp. 870-881. https://dl.acm.org/doi/abs/10.1002/asmb.2213

6. K.P. Tran, P. Castagliola and G. Celano (2016), "Monitoring the Ratio of Two Normal Variables Using Run Rules Type Control Charts", International Journal of Production Research. Vol. 54(6), pp. 1670-1688. https://doi.org/10.1080/00207543.2015.1047982 

2015

1. K.P. Tran, P. Castagliola and G. Celano (2015), "Monitoring the Ratio of Two Normal Variables Using EWMA Type Control Charts", Quality and Reliability Engineering International. Vol. 32(5), pp. 1853-1869. Wiley Online Library. https://doi.org/10.1002/qre.1918 

Books

2024

1. K.P. Tran, S. Li, C. Heuchenne, T.H. Truong (Eds.) The Seventh International Conference on Safety and Security with IoT (selected papers), 2024 Springer Nature Switzerland AG

2023

2. K.P. Tran (Ed.) Artificial Intelligence for Smart Manufacturing - Methods, Applications, and Challenges , 2023 Springer Nature Switzerland AG, 

2022

3. K.P. Tran (Ed.) Machine Learning and Probabilistic Graphical Models for Decision Support Systems, 2022 Taylor & Francis / CRC Press

2021

4. K.P. Tran (Ed.) Control Charts and Machine Learning for Anomaly Detection in Manufacturing, 2021 Springer Nature Switzerland AG, 

Chapters in books

2024

1. T.T. V. Nguyen, T.H. Nguyen, K.D. Tran, C. Heuchenne, and K. P. Tran (2023), “Monitoring the Ratio of Two Normal Variables and Compositional Data: A Literature Review and Perspective”. In Advances of Computational Techniques for Smart manufacturing in the Industry 5.0: Methods and Applications., Taylor & Francis / CRC Press

2.  A. Saghir, K.D. Tran, and K. P. Tran (2023), “Explainable Machine Learning based Control Charts for high-dimensional non-stationary time series data in IoT Systems: Challenges, Methods, and Future Directions”. In Advances of Computational Techniques for Smart manufacturing in the Industry 5.0: Methods and Applications., Taylor & Francis / CRC Press 

2023

1. K.P. Tran(2023), "Introduction to Artificial Intelligence for Smart Manufacturing”. In Artificial Intelligence for Smart Manufacturing - Methods, Applications, and Challenges, Springer Nature Switzerland AG, https://doi.org/10.1201/9781003189886 

2. H.D. Nguyen, K.P. Tran*(2023), " Artificial Intelligence for Smart Manufacturing in Industry 5.0: Methods, Applications, and Challenges”. In Artificial Intelligence for Smart Manufacturing - Methods, Applications, and Challenges, Springer Nature Switzerland AG, https://link.springer.com/book/9783031305092

3. H.D. Nguyen, P.H. Tran, T.H. Do, K.P. Tran (2023), " Quality control for Smart Manufacturing in Industry 5.0”. In Artificial Intelligence for Smart Manufacturing - Methods, Applications, and Challenges, Springer Nature Switzerland AG, https://link.springer.com/book/9783031305092

4.  T.H. Do, P.B. Ta, K.D. Tran, K.P. Tran (2023), "Efficient and Trustworthy Federated Learning-based Explainable Anomaly Detection: Challenges, Methods, and Future Directions”. In Artificial Intelligence for Smart Manufacturing - Methods, Applications, and Challenges, Springer Nature Switzerland AG, https://link.springer.com/book/9783031305092

5. P.B. Ta, T.H. Do, K.D. Tran, K.P. Tran (2023), "Explainable Artificial Intelligence for Cybersecurity in Smart Manufacturing”. In Artificial Intelligence for Smart Manufacturing - Methods, Applications, and Challenges, Springer Nature Switzerland AG, https://link.springer.com/book/9783031305092 

6.  H. Zhang, Z. He, Y. Man, J. Li, M. Hong, K.P. Tran (2023), "Multi-objective optimization of flexible flow-shop intelligent scheduling based on a hybrid intelligent algorithm”. In Artificial Intelligence for Smart Manufacturing - Methods, Applications, and Challenges, Springer Nature Switzerland AG, https://link.springer.com/book/9783031305092

7. G. Chen, Z. He, Y. Man, J. Li, M. Hong, K.P. Tran (2023), "Fault Prediction of Papermaking Process Based on Gaussian Mixture Model and Mahalanobis Distance”. In Artificial Intelligence for Smart Manufacturing - Methods, Applications, and Challenges, Springer Nature Switzerland AG, https://link.springer.com/book/9783031305092 

8. T. Nguyen, K.D. Tran, A. Raza, Q.T. Nguyen, H.M. Bui, K.P. Tran (2023), " Wearable technology for Smart Manufacturing in Industry 5.0”. In Artificial Intelligence for Smart Manufacturing - Methods, Applications, and Challenges, Springer Nature Switzerland AG, https://link.springer.com/book/9783031305092

2022

1. Q. T. Nguyen, T N. Tran, C. Heuchenne, and K. P. Tran (2022), “Decision Support Systems for Anomaly Detection with the Applications in Smart Manufacturing: a survey and perspective”. In Machine Learning and Probabilistic Graphical Models for Decision Support Systems, Taylor \& Francis / CRC Press, https://doi.org/10.1201/9781003189886 

2. T .T. V . Nguyen, C. Heuchenne, and K. P. Tran  (2022), “Machine learning for compositional data analysis in Support of the Decision Making Process”. In Machine Learning and Probabilistic Graphical Models for Decision Support Systems, Taylor \& Francis / CRC Press, https://doi.org/10.1201/9781003189886 

3. H. D. Nguyen, and K. P. Tran  (2022), “Decision Support System using LSTM with Bayesian optimization for Predictive Maintenance: Remaining Useful Life Prediction”. In Machine Learning and Probabilistic Graphical Models for Decision Support Systems, Taylor & Francis / CRC Press, https://doi.org/10.1201/9781003189886 

4. T. H. Nguyen, H. D. Nguyen, D. D. K. Nguyen, K .D. Tran, and K. P. Tran  (2022), “Enabling Smart Supply Chain Management with Artificial Intelligence”. In Machine Learning and Probabilistic Graphical Models for Decision Support Systems, Taylor \& Francis / CRC Press,https://doi.org/10.1201/9781003189886 

5. H. D. Nguyen, K. P. Tran, P. Castagliola, and F. M. Megahed  (2022), “Enabling smart manufacturing with Artificial Intelligence and Big Data: a survey and perspective”. In Advanced Manufacturing Methods , Taylor \& Francis / CRC Press,  https://doi.org/10.1201/9781003189886 

6. Z. Lu, Z. He, K.P. Tran, S. Thomassey, X. Zeng, and M. Hongd  (2022), "Decision Support Systems for Textile Manufacturing Process with Machine Learning". In Machine Learning and Probabilistic Graphical Models for Decision Support Systems, Taylor \& Francis / CRC Press, https://doi.org/10.1201/9781003189886 

7. P.H. Tran, K.P. Tran, C. Heuchenne and H.D.Nguyen (2022), Monitoring Coefficient of Variation using CUSUM control charts . In Handbook of Engineering Statistics, 2nd ed , Springer US, https://link.springer.com/chapter/10.1007/978-1-4471-7503-2_18

2021

1.  P.H.Tran, A. A. Nadi, T.H. Nguyen, K.D.Tran, and K.P. Tran (2021), “Application of Machine Learning in Statistical Process Control Charts: A Survey and Perspective”. In Control Charts and Machine Learning for Anomaly Detection in Manufacturing, Springer Nature Switzerland, accepted,  https://doi.org/10.1007/978-3-030-83819-5_2

2.  K.P. Tran (2021), “Introduction to Control Charts and Machine Learning for Anomaly Detection in Manufacturing”. In Control Charts and Machine Learning for Anomaly Detection in Manufacturing, Springer Nature Switzerland, accepted,  https://doi.org/10.1007/978-3-030-83819-5_1

2020

1. P. Castagliola, K.P. Tran, G. Celano, and P. Maravelakis (2020), The Shewhart Sign Chart with Ties: Performance and Alternatives. In Distribution-free Methods for Statistical Process Monitoring and Control, Springer Berlin / Heidelberg, ISBN: 978-3-030-25081-2.

2.  H.D. Nguyen, K.P. Tran, X. Zeng, L. Koehl,and G. Tartare (2020), An Improved Ensemble Machine Learning algorithm for Wearable Sensor Data Based Human Activity Recognition. In Reliability and Statistical Computing, Springer Berlin / Heidelberg, accepted.

3. Z. He, K.P. Tran, S. Thomassey, X. Zeng and C. Yi (2020), Application of Artificial Intelligence in modeling a textile finishing process. In Reliability and Statistical Computing, Springer Berlin / Heidelberg, accepted.

Refereed Proceedings

2023

1. Raza, A., Tran, K. P., Koehl, L., & Li, S. (2023). Proof of Swarm Based Ensemble Learning for Federated Learning Applications. In Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing (pp. 152-155), https://doi.org/10.1145/3555776.3578601

2. H.D. Nguyen, L.H. Nguyen, K.P. Tran, K.P. Tran, “Artificial Intelligence for Smart Manufacturing in Industry 5.0: Methods, Applications, and Challenges”, ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2022), Danang, Vietnam, January 8-10, 2023

3. H.D. Nguyen, P.H. Tran, T.H. Do, C. Heuchenne, K.P. Tran,“Towards Applicability of Machine Learning in Quality Control for Smart Manufacturing”, ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2022), Danang, Vietnam, January 8-10, 2023

4. T. Nguyen, K.D. Tran, A. Raza, Q.T. Nguyen, M.H. Bui, K.P. Tran,“Wearable Technology for Smart Manufacturing in Industry 5.0 Applications, Challenges, and Case Studies”, ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2022), Danang, Vietnam, January 8-10, 2023

5. T. T.V. Nguyen, C. Heuchenne, K.P. Tran, “Machine learning for compositional data analysis in Support of the Decision-Making Process”, ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2022), Danang, Vietnam, January 8-10, 2023

6. T. T.V. Nguyen, C. Heuchenne, K.D. Tran, K.P. Tran, (2023), “A novel Transformer-based Anomaly Detection approach for ECG Monitoring Healthcare System”, EAI SaSeIoT 2023 - 7th EAI International Conference on Safety and Security in Internet of Things, October 24-26, 2023, Bratislava, Slovakia, https://link.springer.com/chapter/10.1007/978-3-031-53028-9_7

7. A. Saghir, H.Beniwal, K.D. Tran, A. Raza, L.Koehl, X.Zeng, K.P. Tran, (2023), “Explainable Transformer-Based Anomaly Detection for Internet of Things Security”, EAI SaSeIoT 2023 - 7th EAI International Conference on Safety and Security in Internet of Things, October 24-26, 2023, Bratislava, Slovakia, https://link.springer.com/chapter/10.1007/978-3-031-53028-9_6

2022

1. M. Orabi, K.P. Tran, S. Thomassey, P. Egger  (2022). Enable Anomaly detection in Electroplating. In FLINS/ISKE 2020, Tianjin, China, August , 2022. 

2. R. Sleiman, K.P. Tran, S. Thomassey (2022), Natural Language Processing for Fashion Trends Detection. In 2022 IEEE International Conference on Electrical, Computer and Energy Technologies (ICECET), Prague, Czech Republic.

3. T.H. Do, X. H. Nguyen, V. H. Nguyen, H. D. Nguyen, T. H. Truong & K. P. Tran (2022). Explainable Anomaly Detection for Industrial Control System Cybersecurity. In Proceedings of The IFAC 10th conference on MANUFACTURING MODELING, MANAGEMENT AND CONTROL,  June 22-24, 2022, Nantes, France.

4. TTV Nguyen, C Heuchenne & K. P. Tran (2022). Anomaly Detection for Compositional Data using VSI MEWMA control chart. In Proceedings of The IFAC 10th conference on MANUFACTURING MODELING, MANAGEMENT AND CONTROL,  June 22-24, 2022, Nantes, France.

2021

1. R. Sleiman, A. Mazyad, K.P. Tran, S. Thomassey, H. Moez (2021), Long term demand forecasting system for demand driven manufacturing . In APMS 2021 International conference Advances in Production Management Systems, Nantes, France.

2020

1. Tran, P. H., Nguyen, T., Tran, K. P., & Heuchenne, C. (2020, September). Wearable Sensor Data Based Human Activity Recognition using Deep Learning: A new approach. In FLINS/ISKE 2020, Germany, August , 2020. 

2. He, Z., Tran, K. P., Thomassey, S., Zeng, X., & Yi, C. (2020). A reinforcement learning based decision support system in textile manufacturing process. In FLINS/ISKE 2020, Germany, August , 2020. 

3. Tran, P.H., Rakitzis, A.C., Nguyen, H.D., Nguyen, T., Tran, H., Tran, K.P. and Heuchenne, C  (2020), "New Methods for Anomaly Detection: Run Rules Multivariate Coefficient of Variation Control Charts ", In Proceedings of the 2020 International Conference on Advanced Technologies for Communications. Nha Trang, Vietnam 

2019

1.     Q.T. Nguyen, H.D. Nguyen, K.P. Tran.,  P. Castagliola , and E. Frénod. “Real-Time Production Monitoring approach for Smart Manufacturing with Artificial Intelligence techniques”, ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2019), Danang, Vietnam, July 3-5, 2019

2.      H.D. Nguyen, K.P. Tran, S. Thomassey. “Anomaly detection using Long Short Term Memory Networks and its applications in Supply Chain Management”, 9th IFAC Conference on Manufacturing Modelling, Management and Control, Berlin, Germany, August 28-30, 2019 

3.    H.D. Nguyen, K.P. Tran,  X. Zeng, L. Koehl,  P. Castagliola , and  P. Bruniaux. “Industrial Internet of Things, Big Data, and Artificial Intelligence in a Smart Factory: a survey and perspective”, ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2019), Danang, Vietnam, July 3-5, 2019

4.   H.D. Nguyen, K.P. Tran. “Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach”, ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2019), Danang, Vietnam, July 3-5,2019

5. Z. He, K.P. Tran, S. Thomassey, X. Zeng and C. Yi “Modeling Color Fading Ozonation of Textile Using Artificial Intelligence”, ISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2019), Danang, Vietnam, July 3-5, 2019 

6.  T.H. Truong, B. Ta, Q. T. Nguyen, H.D. Nguyen, K.P. Tran (2019), "A data-driven approach for Network Intrusion Detection and Monitoring based on Kernel Null Space", INISCOM 2019 – 5th EAI International Conference on Industrial Networks and Intelligent Systems, Vietnam, 2019

7.  T.H. Nguyen, H.D. Nguyen, K.D. Tran, K.H. Phung, T.H. Truong, T.N. Nguyen, L.H. Nguyen, K.P. Tran (2019), "One-Sided Synthetic-RZ Control Charts: a New Method for Anomaly Detection ", In Proceedings of the 6th IEEE Conference on Information and Computer Science. Hanoi, Vietnam 

2018

1. P.H. Tran K.P. Tran TTPT and Le T (2018), "Real Time Data-Driven approaches for Credit Card Fraud Detection", In 2018 International Conference on E-Business and Applications. 

2. P.H. Tran K.P. Tran TTTN and C.N. (2018), "A Variable Sampling Interval EWMA distribution-free control chart for monitoring services quality", In 2018 International Conference on E-Business and Applications (ICEBA 2018).

3. Q.T. Nguyen, K.P. Tran, P. Castagliola, T.T. Huong, M.K. Nguyen, S. Lardjane. Nested One-Class Support Vector Machines for Network Intrusion Detection. Proceedings of the Seventh IEEE International Conference on Communications and Electronics (ICCE), Hue, Vietnam, 18-20 July, 2018.

4. K.P. Tran H. D. Nguyen, Q. T. Nguyen, and W. Chattinnawat (2018) "One-Sided synthetic control charts for monitoring the Coefficient of Variation with Measurement Errors", In processdings of The IEEE International Conference on Industrial Engineering and Engineering Management , 16-19 December, 2018, Bangkok, Thailand.

5. K.P. Tran, P. Castagliola, T.H. Nguyen and A. Cuzol (2018), "The Efficiency of the VSI Exponentially Weighted Moving Average Median Control Chart", In 24nd ISSAT International Conference on Reliability and Quality in Design,  August 2-4, 2018, Toronto, Ontario, Canda.

2017

1. P. Castagliola, K.P. Tran, G. Celano , A.C. Rakitzis and P. Maravelakis(2017), "An EWMA-Type Sign Chart with Exact Run Length Properties", In Proceedings of the International Symposium on Statistical Process Monitoring 2017. 

2. V.V. Trinh, K.P. Tran and A.T. Mai (2017), "Anomaly detection in wireless sensor networks via support vector data description with Mahalanobis kernels and discriminative adjustment", In Proceedings of the 4th NAFOSTED Conference on Information and Computer Science. Hanoi, Vietnam 

3. V.V. Trinh, K.P. Tran and T.H. Truong (2017), "Data driven hyperparameter optimization of one-class support vector machines for anomaly detection in wireless sensor networks", In Proceedings of the 2017 International Conference on Advanced Technologies for Communications. Quy Nhon, Vietnam 

2016

1. K.P. Tran , P. Castagliola and G. Celano (2016), "The Efficiency of the 4-out-of-5 Runs Rules Scheme for monitoring the Ratio of Population Means of a Bivariate Normal distribution", In 22nd ISSAT International Conference on Reliability and Quality in Design. Los Angeles, CA, USA 

Invited talks

2023

1. K.P. Tran (2023), “Secure and Robust Federated Learning with Explainable Artificial Intelligence for Healthcare Systems”, 35th Panhellenic, Athens, May, 25 - 28, 2023.

2. K.P. Tran (2023), “Explainable and Trustworthy Artificial Intelligence for Smart Healthcare System: A Federated Learning Approach”, International Conference Explainable Artificial Intelligence for Industry 5.0, Da Nang, September, 6, 2023.

3. K.P. Tran (2023), “A brief introduction to the International  Workshop on Responsible Artificial Intelligence and Applications in Integrated Circuit Industry, Manufacturing, and Healthcare”, International  Workshop on Responsible Artificial Intelligence and Applications in Integrated Circuit Industry, Manufacturing, and Healthcare, December 21, 2023, Danang, Vietnam.

4. H.D. Nguyen, K.P. Tran (2023), “Artificial Intelligence for Smart Manufacturing in Industry 5.0: Methods, Applications in Semiconductor Industry, and Challenges”, International  Workshop on Responsible Artificial Intelligence and Applications in Integrated Circuit Industry, Manufacturing, and Healthcare, December 21, 2023, Danang, Vietnam

5. M. Orabi, K.P. Tran, S. Thomassey, P. Egger, (2023), “Innovations in Anomaly Detection for Catalyxing Operational Excellence in Complex Manufacturing Processes”, International  Workshop on Responsible Artificial Intelligence and Applications in Integrated Circuit Industry, Manufacturing, and Healthcare, December 21, 2023, Danang, Vietnam

6. SAF Mortezanejad, R Wang, GM Borzadaran, R Ding, KP Tran, (2023), “Profile control chart based on maximum entropy”, International  Workshop on Responsible Artificial Intelligence and Applications in Integrated Circuit Industry, Manufacturing, and Healthcare, December 21, 2023, Danang, Vietnam

7. T. T.V. Nguyen, C. Heuchenne, K.D. Tran, K.P. Tran, (2023), “A novel Transformer-based Anomaly Detection approach for ECG Monitoring Healthcare System: a perspective”, International  Workshop on Responsible Artificial Intelligence and Applications in Integrated Circuit Industry, Manufacturing, and Healthcare, December 21, 2023, Danang, Vietnam

2022

8. K.P. Tran (2022), “Machine learning and statistical techniques for monitoring and anomaly detection”, Statistical Week 2022, Münster, Germany, 22 September 2022. 

9. K.P. Tran (2022), “Designing ECG monitoring healthcare system with Federated Learning and Explainable AI”, International Webinar on Artificial Intelligence & Data Science in Industry 4.0, Dong A University, Vietnam, 14 July 2022. 

10. K.P. Tran (2022), “Monitoring, anomaly detection, modeling, and optimization of industrial systems with statistical and machine learning techniques”, DO LAAS-CNRS seminar, LAAS-CNRS, France, 16 May 2022. 

11. K.P. Tran (2022), Machine learning for anomaly detection”, LCOMS Seminar, frENBIS , France,  6 May 2022. 

12. K.P. Tran (2022), “Machine learning for anomaly detection: methods, applications and challenges ”, frENBIS Webinar, frENBIS , France,  8 April 2022. 

13. K.P. Tran (2022), “Statistical methods and machine learning for monitoring and anomaly detection”, Dynamical Systems, Probability and Statistics Seminar , LMBA / UMR 6205 , France,  7 April 2022. 

2021

14. K.P. Tran (2021), “Machine Learning and Control Chart for Anomaly Detection: Methods, Applications, and Challenges”, International Webinar on Artificial Intelligence and Data Science with Applications 2021, Dong A University, Vietnam, 20 December 2021. 

2018

15. K.P. Tran (2018), “Advanced Statistical Process Control, Big Data and Machine learning: a perspective”, International Symposium on Business and Industrial Statistics (ISBIS) 2018, University of Piraeus, Greece, 4-6 July 2018. 

Keynote Speech 

2024

1. K. P. Tran (2024), "Edge Artificial Intelligence for Predictive Maintenance in Smart Manufacturing", 4th International Conference on Mechanical Design and Smart Manufacturing (MDSM2024), August 23-25, 2024 in Wuhan, China.

2023

2. K. P. Tran (2023), "Secure, Robust, and Explainable Federated Learning for Smart Healthcare Systems", The 5th Int'l Conference on Machine Learning, Pattern Recognition and Intelligent Systems (MLPRIS 2023), July 14-16, 2023 in Guilin, China .

3. K. P. Tran (2023), "Explainable  Federated Learning for Smart Manufacturing", 2023 Int'l Conference on Industrial and Mechanical Engineering (CIME 2023), Oct.30 - Nov.1, 2023 in Xi'an, China.

2021

4. K. P. Tran (2021), "Forecasting and Anomaly Detection approaches using LSTM and LSTM Autoencoder techniques with the applications in Supply Chain Management", The 4th Int'l Conference on Machine Learning, Pattern Recognition and Intelligent Systems (MLPRIS 2021), July 16-18, 2021 in Kunming, China.