Objective and scope
The two-day workshop, divided into two main thematic blocks – Optimization in Machine Learning and Optimization with Fractional Calculus Methods – is primarily designed for PhD students and other interested participants. The sessions will be conducted by invited lecturers, who are recognized experts in these fields.
The main objectives of the workshop are to deepen participants’ theoretical knowledge, enhance their research competencies, and provide an inspiring environment for establishing international scientific collaboration.
Thus, the workshop offers a valuable opportunity to gain both theoretical insights and practical skills in applying state-of-the-art computational technologies in applied mathematics and engineering.
Prof. Yuri Luchko is a Full Professor in the Department of Mathematics, Physics, and Chemistry at Berlin University of Applied Sciences and Technology. His research focuses on applied mathematics, particularly fractional calculus, fractional differential equations, and their applications. He earned his PhD in Mathematics from Belarusian State University in Minsk in 1993 under the supervision of Semyon Yakubovich. His work has significantly advanced the theory of fractional derivatives, including the development of operators with Sonin kernels for modeling memory-dependent processes. He began his academic career as a postdoctoral researcher at the Free University of Berlin from 1994 to 2000. He then worked at the European University Viadrina in Frankfurt (Oder) from 2000 to 2006 before joining BHT in 2006 as a professor. He has authored or edited around 200 peer-reviewed papers and 20 books, receiving over 13,000 citations. In 2024, he received the Best Paper Award at the IFAC Conference on Fractional Differentiation and Its Applications (FDA) in Bordeaux and serves as an associate editor of Fractional Calculus and Applied Analysis.
Google Scholar – Profile of Prof. Dr. Yuri Luchko
Prof. Jean-Christophe Pesquet (IEEE Fellow 2012, EURASIP Fellow 2022) received the engineering degree from Supélec in 1987, the Ph.D. and HDR degrees from the University Paris-Sud in 1990 and 1999, respectively. From 1991 to 1999, he was a Maître de Conférences at the University Paris-Sud. From 1999 to 2016, he was a Professor with the University Paris-Est, and from 2012 to 2016, he was the Deputy Director of the CNRS Laboratoire d’Informatique of the university. He is currently a Distinguished Professor with CentraleSupélec, University Paris-Saclay and the Director of the CVN (Inria team). He was also a senior member of the Institut Universitaire de France from 2016 to 2021. In 2005, J.-C. Pesquet was technical chairman of ICASSP and he is also technical chairman of ICIP 2022. He was a member of the SPTM technical committee (2000-2005 and 2011-2016) and served as an associate editor for IEEE SPL (2004-2006). He was an associate editor for IEEE TSP (2009-2013), a senior area editor for the same journal (2010-2015), and a member of the committee for the best paper award of EURASIP JASP (2007-2019). He is now an associate editor of SIAM Journal on Imaging Sciences. His research interests are focused on optimization methods in data science.
Google Scholar – Profile of Prof. Jean-Christophe Pesquet
Prof. Dariusz Uciński was born in Gliwice, Poland, in 1965. He studied electrical engineering at the Higher College of Engineering in Zielona Góra, Poland, from which he graduated in 1989. He received Ph.D. (1992) and D.Sc. (2000) degrees in automatic control and robotics from the Technical University of Wrocław, Poland. In 2007 he was conferred the title of state professor, the highest scientific degree in Poland. He is currently a full professor at the University of Zielona Góra, Poland. His major activities have been concentrated on measurement optimization for parameter estimation of systems modelled by partial differential equations. In 2005 his comprehensive monograph entitled Optimal Measurement Methods for Distributed Parameter System Identification was published by CRC Press in Boca Raton, FL. He is regularly featured in the Stanford/Elsevier’s Top 2% Scientist Ranking. Other areas of expertise include optimum experimental design, optimal control, robotics, parallel computing and machine learning.
Google Scholar – Profile of Prof. dr hab. inż. Dariusz Uciński