Professor . Silviu-Iulian NICULESCU , PhD
Directeur de Recherche au CNRS, membre de l'équipe Inria "Disco"France
November 9th, 2022
(Opening Ceremony and Plenary)
Title: " Delay as a control parameter. A guided tour"
Silviu-Iulian NICULESCU was born in Petrosani, Romania in 1968. He received the B.S. degree from the Polytechnical Institute of Bucharest, Romania, the M.Sc., and Ph.D. degrees, both in Automatic Control, from the Institut National Polytechnique de Grenoble, France, and the “Habilitation à Diriger des Recherches” (HDR) in Automatic Control from Université de Technologie de Compiègne, in 1992, 1993, 1996, and 2003, respectively. From 1992 to 1997, he was with the Department of Automatic Control and Computers, University « Politehnica » Bucharest, Romania. From 1997 to 2006, he was with HEUDIASYC (“Heuristics and diagnosis of complex systems”) laboratory, Compiègne, France as a Researcher at CNRS (French National Center for Scientific Research). He also held a PostDoctoral position in the Department of Applied Mathematics, ENSTA, Paris, France, from 1996 to 1997. In September 2006, he joined L2S (Laboratory of Signals and Systems), Gif-sur-Yvette, where he is currently Research Director (“Senior Researcher”) at CNRS. He was the head of the laboratory for 10 years (2010-2019). Co-founder of the Inria team « DISCO » (common team of Inria with CNRS and CentraleSupélec, located at L2S) in 2010, he is also an active member of the team.
Dr. Niculescu is author or co-author of ten books (Diderot: 1997; Birkhauser, Briefs: 2015; SIAM: 2007 and 2015; Springer: LNCIS – 2001, CES – 2014, AIC – 2015, SpringerBriefs – 2 in 2015 1 in 2016, and 1 in 2020) and co-editor of six volumes (SIAM, 1999; Pergamon Press, 2001; Springer 2004; Springer 2007; Springer 2009). He is author or co-author of more than 500 book chapters or scientific papers. He has been the IPC Chairman of the 3rd IFAC Workshop on Time-Delay Systems (Santa Fe, NM, USA, December 2001) , of the 8th IFAC Workshop on Time-Delay Systems (Sinaia, Romania, September 2009), 13th European Control Conference (Strasoburg, France, June 2014), and the main organizer or co-organizer of the 1st CNRS-NSF Workshop on Time-Delay Systems (Paris: La Défense, January 2003), and of the two European Summer School in Automatic Control (Grenoble, September 2000; Grenoble, July 2013) devoted to time-delay systems. He was the guest co-editor of five special issues in the area of delay systems (Journal of Mathematical Modelling of Natural Phenomena (MMNP) in 2009, Asian Journal of Control in 2005, IMA Journal of Mathematical Control and Information in 2002 and 2010, and Kybernetika in 2001).
Dr. Niculescu has been scientific responsible of 15 international cooperation programs and projects (with Belgium, Mexico, Romania and Eastern European countries, South Korea, Hong Kong, Turkey and United States). He is member of the IPC of 45 International Conferences, and he was an Associate Editor of the IEEE Transactions on Automatic Control (2003-2005). Since 2011, he is an Associate Editor of European Journal of Controland IMA Journal of Mathematical Control and Information. IEEE Fellow since 2018, Dr Niculescu is the chair of the IFAC Technical Committee « Control Linear Systems » (TC 2.2) since 2017 and he was the chair of the IFAC Research Group on « Time-delay systems » (2007 and vice-chair of the IFAC Technical Committee on Control Linear Systems (TC 2.2) for the period 2011-2017. Since 2012, he is the founding editor and the scientific responsible of the Springer (book) series: Advances in Delays in Dynamics (ADD@S).
Dr. Niculescu was awarded the CNRS Silver and Bronze Medals for scientific research, the Best Paper Presentation Award at American Control Conference, Chicago, IL and the Ph.D. Thesis Award from INPG, Grenoble (France) in 2011, 2001, 2000, and 1996, respectively. He was also awarded the title of « Doctor Honoris Causa » of University of Craiova (Romania) in 2016. His research interests include delay systems, robust control, operator theory, and numerical methods in optimization, and their applications to the design of engineering systems.
Professor Daniel Ulises Campos Delgado, PhD
Professor of Autonomous University of San Luis Potosi (UASLP)
School of Sciences
November 10th, 2022
Title: "Hybrid Classification Approach for Correlated Multimodality Images: Unmixing Processing + Artificial Intelligence"
Correlated multimodal images allow to capture spatial-temporal or spatial-spectral information simultaneously from a scene. These types of images had found applications in diverse fields, as earth observation to identify types of vegetation, medical diagnosis to detect cancerous lesions in the skin or oral cavity, food inspection to distinguish contaminants, non-destructive testing to perceive defects in materials, among others. One of the main challenges in this field is to make an efficient and fast processing of the vast acquired information. In this talk, I will focus on the classification problem of correlated multimodal images by a hybrid approach. Hence, first, linear and nonlinear unmixing are used to extract features to guide the classification process by applying the algorithm “extended blind end-member and abundance extraction”, which was developed by our research team. Next, machine learning and deep learning are applied to achieve the final pixel labeling. In the talk, I will focus on the applications to medical diagnosis and non-destructive testing for our hybrid classification approach.
Daniel U. Campos Delgado received the B.S. degree in electronics engineering from the Autonomous University of San Luis Potosi (UASLP), Mexico, in 1996, and the M.S.E.E. and Ph.D. degrees in electrical engineering from Louisiana State University (LSU), USA, in 1999 and 2001, respectively. In 2001, he joined the School of Sciences of UASLP as a Professor. He has published more than 80 peer-reviewed papers in scientific journals, and 100 in international congresses. His research interests include estimation and detection, optimization algorithms, fault diagnosis, control theory, and digital signal processing. In these areas, he has received international funding for collaborative work with University of California (Santa Barbara), Texas A&M University, and Institute of Molecular Bioimaging and Physiology (Milan); and in the period august/2014 to may/2015, he was a Visiting Scholar in the Biomedical Engineering Department of Texas A&M University. His research products have been cited more than 1,500 (h-index: 20) and 2,000 times (h-index: 20) according to Web of Science and SCOPUS, respectively. Dr. Campos Delgado has been advisor or co-advisor of 30 bachelor thesis projects, 24 Master thesis works, and 9 Doctoral dissertations. He is currently a member of the Mexican Academy of Sciences (AMC) and Sigma Xi, and a Senior Member in the IEEE. In 2001, the College of Engineering of LSU granted him the “Exemplary Dissertation Award”, and in 2009 and 2013, he received awards as a Young Researcher from UASLP and AMC. In May/2021, he received the State Award for Scientific and Technological Research by COPOCYT. From July/2016 to June/2020, Dr. Campos Delgado was the Dean of the Faculty of Sciences in UASLP, and since January/2021, he is
the Director of the Research Institute of Optical Communication. Since May/2019, he is an associate editor for IEEE Latin America Transactions (ISSN: 1548-0992), and since October/2018, he is also a reviewer for Mathematical Reviews/MathSciNet. Dr. Campos-Delgado has been reviewer for many journals from IEEE, IET, OSA and American Mathematical Society; and he was recently selected as a member of the bank of experts from Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación (Spain). In June/2020, he joined the Board of Communication Theory in Frontiers in Communications and Networks as an Associate Editor.
Professor Qiang Huang, PhD
Professor, Fellow of IISE and ASME
Epstein Department of Industrial and Systems Engineering
University of Southern California
United States od America (USA)
November 11th, 2022
Title: "An Impulse Response Formulation for Machine Learning of 3D Printing Accuracy"
Machine learning for additive manufacturing (ML4AM) has emerged as a viable strategy in recent years to enhance 3D printing performance. However, the amount of data required for model training and the lack of ability to infer process insights can be serious barriers to industrial applications. Due to the nature of low-volume fabrication of infinite product variety in 3D printing, ML4AM also faces ``small data, big tasks" challenges to learn heterogeneous point cloud data and control the quality of new designs. This talk presents the critical connection of the impulse response formulation in control theory with small-sample machine learning of 3D printing accuracy. This fabrication-aware formulation builds the foundation for applying well-established control theory to the intelligent quality control of 3D printing. It not only provides theoretical underpinning and justification of our previous work on ML4AM, but also enable new control opportunities.
Dr. Qiang Huang is currently a Professor at the Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California (USC), Los Angeles. His research focuses on AI and Machine Learning for Manufacturing, in particular, Machine Learning for Additive Manufacturing (ML4AM). He was the holder of Gordon S. Marshall Early Career Chair in Engineering at USC from 2012 to 2016. He received IISE Fellow and ASME Awards, NSF CAREER award, and 2021 IEEE CASE Best Conference Paper Award, 2013 IEEE Transactions on Automation Science and Engineering Best Paper Award, among others. He has five patents on ML4AM. He is a Department Editor for IISE Transactions and an Associate Editor for ASME Transactions, Journal of Manufacturing Science and Engineering.
Professor Antonio Ramírez Treviño, PhD
Professor of Center for Research and Advanced Studies of the
National Polytechnic Institute
CINVESTAV - Centro de Investigación y de Estudios Avanzados del
Instituto Politécnico Nacional - Unidad Guadalajara
Title: Fault Diagnosis in Petri Nets
In this problem both, the model and set of potential system faults are known, and the actual occurrence of a fault must be determined from the system outputs during its evolution.
First, we review the basic concepts about fault diagnosis and Petri nets (PN). Afterwards, we present sufficient structural conditions to guarantee the non-concurrent diagnosability property in a PN structure. In this case, the non-existence of infinite length indistinguishable output cycles is enough to determine that faults are diagnosable; from the PN structure perspective, it is equivalent to the non-existence of T-semiflows that could be fired with independence of the fault occurrence. Later, the concurrent diagnosability is presented to deal with system exhibiting concurrence.
Subsequently, the diagnosability problem in Timed Continuous Petri net (TCPN) is also addressed from a structural perspective. Since TCPNs are positive affine switched linear systems, the diagnosability is more complex to analyze, and reported results are based on the analysis of the paths from potential faults to sensors. When the transfer functions from potential faults to the outputs are all different from each other, then every fault is diagnosable. Then, a brief review of the results about fault diagnosis in linear systems using unobservability spaces is presented, establishing
bridges between the diagnosis in linear systems and Petri nets. Finally, the distributed diagnosis problem, using the notion of quotient Petri net, is addressed. The advantage of this approach is that diagnosability can be achieved efficiently, because T-semiflows that could be fired with independence of fault occurrence are efficiently obtained.
Antonio Ramírez-Treviño received the B.Sc. degree in electrical engineering from Universidad Autonoma Metropolitana, Mexico City, Mexico, in 1986, the M.Sc. degree from Cinvestav, Mexico, in 1990, and the Ph.D. degree from the University of Zaragoza, Spain, in 1993. He is currently a Professor with Cinvestav Unidad Guadalajara, Mexico. His research interests include controllability, observability, and diagnosis of discrete event and hybrid systems, as well as scheduling policies for real time systems.