Keynote Speakers

Jatinder N. D. Gupta (University of Alabama in Huntsville, U.S.A)

Title:  Rigor and Relevance in Analytics Research

Abstract:  There is a constant debate as to the balance of rigor and relevance in Analytics research. The academicians often claim that the rigor of research is important, while the practitioners believe that relevance is more important.  Many believe that the gap in the perceptions of the practitioners and the academicians cannot be narrowed. At the same time, others believe that several compatibilities exist between the developments in analytics (rigor) and their applications to practical situations (relevance). This presentation discusses the issues surrounding the rigor and relevance in analytics by using the field of scheduling research to make it more useful in solving practical problems.

Bio: Jatinder (Jeet) N. D. Gupta is currently an Eminent Scholar and Professor Emeritus at the University of Alabama in Huntsville, Alabama.   In his career, He held several academic, technical, and managerial positions in the University of Illinois in Springfield, US Postal Service, US Department of Energy, where he received the superior job performance award, University of Baltimore, Ball State University, and University of Alabama in Huntsville. Dr. Gupta is an international authority in research and teaching related to production scheduling, planning, and control on one hand and supply chain and information technology on the other. He is also a frequent keynote speaker at various international conferences and editor of special issues and books. Dr. Gupta’s current research interests include Business Analytics, Corporate Governance, Renewable Energy Supply Chains, Energy Policies for Renewable Energy, Enterprise Resources Planning (including SAP), Information Security, Supply Chain and Logistics Management, Information and Decision Technologies, Scheduling, Planning and Control, Enterprise Integration, and Social Aspects of Corporate Activities. 

Deren Han (Beihang University, China)

Title:  Non-convex Pose Graph Optimization in SLAM via Proximal Linearized Riemannian ADMM

Abstract: Pose graph optimization (PGO) is a well-known technique for solving the pose-based simultaneous localization and mapping (SLAM) problem. In this paper, we represent the rotation and translation by a unit quaternion and a three-dimensional vector, and propose a new PGO model based on the von Mises-Fisher distribution. The constraints derived from the unit quaternions are spherical manifolds, and the projection onto the constraints can be calculated by normalization. Then a proximal linearized Riemannian alternating direction method of multipliers (PieADMM) is developed to solve the proposed model, which not only has low memory requirements, but also can update the poses in parallel. Furthermore, we establish the iteration complexity of O(1/ε²) of PieADMM for finding an ε-stationary solution of our model. The efficiency of our proposed algorithm is demonstrated by numerical experiments on two synthetic and four 3D SLAM benchmark datasets.

Bio: Deren Han is a Professor and Doctoral Supervisor, currently serving as the Dean of the School of Mathematical Sciences at Beihang University. His research focuses on numerical methods for large-scale optimization problems and variational inequalities, as well as their applications in transportation planning and magnetic resonance imaging. He has been awarded the Youth Science and Technology Award by the Chinese Operations Research Society and the Jiangsu Provincial Science and Technology Progress Award. He has led several major research projects, including the National Natural Science Foundation of China (NSFC) Distinguished Young Scholars Fund and key NSFC projects. In addition to his academic roles, he holds some positions such as Vice Chair of the Chinese Operations Research Society and serves as an associate editor for several journals, including Journal of the Operations Research Society of China, Journal of Global Optimization, and Asia-Pacific Journal of Operational Research.

Yong Yin (Doshisha University, Japan)

Tittle: Seru Production Systems as the Backbone of Smart Manufacturing: Challenges and Research Pathways

Abstract: As AI technologies, robotics, and electric vehicles rapidly reshape the manufacturing landscape, traditional lean production systems are increasingly unable to meet the demands of dynamic, high-variability markets. This talk introduces the Seru Production System, a modular and parallelized approach that enables faster, more flexible responses in smart manufacturing environments. Widely adopted in electronics and emerging in EV sectors like Tesla, Seru systems represent a strategic shift from conventional assembly lines. Despite their advantages, Seru systems pose new challenges in workforce coordination, system design, and production management, opening up rich avenues for research. This talk explores Seru's role as a core enabler of smart manufacturing and highlights the theoretical and practical questions it raises—making it a compelling topic for both industry practitioners and academic researchers.

Bio: Yong Yin is a professor of Doshisha University in Japan, specializing in the field of production management. He is one of the principal pioneers in the research of the Seru Production System. His work on Seru production has been published in top-tier journals in the field of operations management. In terms of academic service, he also serves as an overseas review expert for the Changjiang Scholars Program, among other roles.

Donglei Du (University of New Brunswick, Canada)

Tittle: The Core of Nonlinear Combinaitorial Games

Abstract: The core, a widely studied solution concept in cooperative game theory, has traditionally been analyzed using ad hoc methods for specific games. Recent research, however, has shifted toward systematic frameworks based on optimization models, such as linear, integer, or combinatorial programming games, offering broader theoretical insights and practical applications. This work advances this systematic approach by enabling core analysis for cooperative games derived from nonlinear integer programs (binary and non-binary). Unlike prior methods relying on strong relaxations (e.g., LP or convex relaxations requiring objective function agreement), we propose a novel technique using significantly weaker relaxations. Our method’s versatility is demonstrated through applications to previously unstudied games, underscoring its independent theoretical value and expanding the toolkit for analyzing complex cooperative games.

Bio: Donglei Du is a professor in Operations Research at the Faculty of Management (FOM), University of New Brunswick (UNB), Canada. His main research interests are quantitative investment management, combinatorial optimization, approximations algorithms, robust optimization, social network analysis, algorithmic game theory, supply chain management, facility location, and machine scheduling. His publications have appeared in top-tier journals, including Operations Research, Algorithmica, SIAM Journal on Discrete Mathematics, European Journal of Operation Research, Omega etc. His academic achievement was recognized by several awards from UNB at both the university and faculty levels, including the University Research Scholar (UNB, 2014), University Merit Award (UNB, twice, 2006 and 2012), Excellence in Research Award (FOM, 2007), and Annual Research Award (FOM, 2004).