Laboratoire de recherche textile

Kim-Phuc TRAN

Associate Professor & Research Supervisor
  • CONTACT

Research

Human Centered Design Group

  • Research skill : Machine Learning, Digital Signal Processing, Neural Networks and Artificial Intelligence, Operations Management
  • Associate professor & research supervisor – Section CNU 61

Research interests

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

Research links

PROJECTS

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).

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 763474 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). 

ACADEMIC RESPONSABILITIES

EDITORIAL ACTIVITIES

EXPERTISE

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BOOKS & CHAPTERS

2021

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

 

978-3-030-83819-5

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2022

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

K.P. Tran (Ed.) Artificial Intelligence for Smart Manufacturing – Methods, Applications, and Challenges , 2022 Springer Nature Switzerland AG

2022

  1. 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://www.taylorfrancis.com/chapters/edit/10.1201/9781003189886-3/decision-support-systems-anomaly-detection-applications-smart-manufacturing-survey-perspective-quoc-th%C3%B4ng-nguyen-tung-nhi-tran-c%C3%A9dric-heuchenne-kim-phuc-tran

  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://www.taylorfrancis.com/chapters/edit/10.1201/9781003189886-8/machine-learning-compositional-data-analysis-support-decision-making-process-thi-thuy-van-nguyen-c%C3%A9dric-heuchenne-kim-phuc-tran

  3. 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://www.taylorfrancis.com/chapters/edit/10.1201/9781003189886-5/decision-support-system-using-lstm-bayesian-optimization-predictive-maintenance-remaining-useful-life-prediction-huu-du-nguyen-kim-phuc-tran

  4. 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://www.taylorfrancis.com/chapters/edit/10.1201/9781003189886-12/enabling-smart-supply-chain-management-artificial-intelligence-thi-hien-nguyen-huu-du-nguyen-kim-duc-tran-dinh-duy-kha-nguyen-kim-phuc-tran.

  5. 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://www.taylorfrancis.com/chapters/edit/10.1201/9780367822385-1/enabling-smart-manufacturing-artificial-intelligence-big-data-huu-du-nguyen-kim-phuc-tran-philippe-castagliola-fadel-megahed.

  6. 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://www.taylorfrancis.com/chapters/edit/10.1201/9781003189886-6/decision-support-systems-textile-manufacturing-process-machine-learning-zaohao-lu-zhenglei-kim-phuc-tran-sebastien-thomassey-xianyi-zeng-mengna-hong
  1. 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, accepted.

2021

  1. 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. 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, https://doi.org/10.1007/978-3-030-25081-2_3

  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, https://link.springer.com/chapter/10.1007/978-3-030-43412-0_13

  3. 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, https://link.springer.com/chapter/10.1007/978-3-030-43412-0_5

CONGRESS ORGANIZATION

REFERED PROCEEDINGS

  1. Orabi, K.P. Tran, S. Thomassey, P. Egger (2022). Enable Anomaly detection in Electroplating. In FLINS/ISKE 2020, Tianjin, China, August , 2022.
  2. 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. 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.
  1. 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.

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

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

  1. 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. 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. 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. 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. 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, CanAda.
  1. 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. 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. 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
  1. 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

TEACHING

  • Machine learning and Python
  • Data Structures and Algorithms in Python
  • Information Systems
  • Product Lifecycle Management
  • Supply Chain and Logistics Optimization
  • Production Management and Logistics
  • Wearable Technology

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.

other responsabilities

GEMTEX
 2 allée Louise et Victor Champier BP 30329
59056 ROUBAIX CEDEX 1 – FRANCE

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