Metaheuristic Optimization, Machine Learning and AI – Virtual Workshop

Dates:  March 8-12, 2021
Times:  Various

Deadline for Registrations was February 26, 2021

Simulated Annealing and Genetic Algorithms are widely known in statistics, but there are more modern general-purpose optimization algorithms, such as swarm-based algorithms and evolutionary algorithms, that have received scant attention in statistical research.  Examples of swarm-based algorithms are   Particle swarm, Bat, Cuckoo, Competitive Swarm, and examples of evolutionary algorithms are Differential Evolution and Imperialistic Competitive algorithm.  Recent work has increasingly shown this powerful class of nature-inspired meta-heuristic algorithms can flexibly tackle high-dimensional complex optimization problems in multiple disciplines, when they are used singly or when they are hybridized with other types of algorithms. Interestingly, these algorithms do not seem to require technical assumptions for them to work well and many also do not have proof of convergence. This workshop aims to promote discussions on recent advances in metaheuristics and their abundant use in machine learning and diverse applications in AI.

Confirmed Speakers:

Alan R. Vazquez, Department of Statistics, University of California Los Angeles USA
Christian Blum, Artificial Intelligence Research Institute Spain
Ray-Bing Chen, Department of Statistics, National Cheng Kung University Taiwan
Carlos A. Coello Coello, Department of Computer Science, Cinvestav-IPN Mexico
Abhishek Gupta, Singapore Institute of Manufacturing Technology, A*Star Singapore
Yaochu Jin, Department of Computer Science, University of Surrey UK
Seongho Kim, Department of Oncology, School of Medicine and Biostatistics Core, Karmanos Cancer Institute USA
Jinglai Li, School of Mathematics, University of Birmingham UK
Dietmar Maringer, Department of Business and Economics, University of Basel Switzerland
Soumya D. Mohanty, Department of Physics and Astronomy, U of Texas RGV USA
Jonas Mueller, Amazon Web Services USA
Frederick Phoa, Institute of Statistical Science, Academia Sinica Taiwan
Christina Ramirez, Department of Biostatistics, University of California Los Angeles USA
Christine Shoemaker, Department of Industrial Systems Engineering and Management, National University of Singapore
Noah Simon, Department of Biostatistics, University of Washington USA
Ponnuthurai Suganthan, School of Electrical & Electronic Engineering, Nanyang Technological University Singapore
Xin Tong, Department of Mathematics, National University of Singapore
Stefan Wager, Department of Graduate School of Business and Department of Statistics, Stanford University USA
Xin-She Yang, Department of Design Engineering and Mathematics, Middlesex University London UK
Gang George Yin, Department of Mathematics, University of Connecticut USA
Qingfu Zhang, Department of Computer Science, City University of Hong Kong

Postdoc/Graduate Student Speakers:

Marzie Rasekh, Department of Bioinformatics, Boston University USA
Mitchell Schepps, Department of Biostatistics, UCLA USA
Ye Tian, Department of Computing, Hong Kong Polytechnic University, Hong Kong and Institutes of Physical Science and Information Technology, Anhui University China

Schedule and Supporting Media

Printable Tentative Schedule
Titles and Abstracts
Registered Participants

Questions: dsbs@samsi.info