Dr. Forough Zarea Fazlelahi is a Lecturer in Entrepreneurship at QUT Business School's School of Management. She holds a PhD from QUT (2021) and focuses on entrepreneurship, technology transfer, and strategic alliance dynamics. Her research examines spinoff networks, entrepreneurial passion, and university commercialization efficiency using methods like DEA analysis and fsQCA. She has published in top journals such as Journal of Small Business Management , Asia Pacific Journal of Management , and Journal of Vocational Behavior . Key荣誉包括2023年ACERE最佳定量论文奖和2021年Heizer奖决赛入围者提名。 Dr. Zarea Fazlelahi supervises HDR students and is proficient in econometric software (R, STATA, MATLAB) and LLM applications. She leads projects on innovation policy and public research funding efficiency, contributing to the Australian Centre for Entrepreneurship Research.
Susana Vieira is an Associate Professor in Mechanical Engineering at Instituto Superior Técnico (Universidade de Lisboa). She specializes in mechatronic systems design and optimization techniques. Her research applies machine learning to industrial challenges, including scheduling, fault diagnosis, and sustainable resource management. Recent work explores reinforcement learning for energy networks and multi-objective optimization. Publications focus on AI-driven solutions for logistics, renewable energy, and healthcare systems, emphasizing algorithmic efficiency.
Dr. Fabio Caraffini is an Associate Professor in Computer Science at Swansea University's School of Mathematics and Computer Science. He holds dual PhDs in Mathematical Information Technology (University of Jyväskylä, 2016) and Computer Science (De Montfort University, 2014), along with BSc and MSc degrees in Engineering from the University of Perugia. His research focuses on computational intelligence, particularly heuristic optimization methods like evolutionary algorithms and differential evolution. He also holds an honorary position as Senior Research Fellow at De Montfort University (2022–2024). Education History: BSc in Electronics Engineering (University of Perugia, 2008) MSc in Telecommunications Engineering (University of Perugia, 2011) PhD in Mathematical Information Technology (University of Jyväskylä, 2016) PhD in Computer Science (De Montfort University, 2014) Research Interests: Dr. Caraffini's work bridges theoretical optimization and practical applications. Key areas include evolutionary computing, structural bias analysis in algorithms, and interdisciplinary AI applications such as medical imaging, climate risk modeling, and robotics. His SOS Platform and BIAS toolbox are notable contributions to algorithm benchmarking and bias detection. Recent projects include AI-driven solutions for crop mapping, medical record analysis, and rail scheduling optimization. Publications & Trends: His 150+ publications span journals like Information Sciences , IEEE Transactions , and Applied Soft Computing . Themes include algorithmic robustness, constraint handling, and real-world optimization challenges. Notable works address differential evolution improvements, climate transition risk prediction, and medical decision support systems. Awards & Grants: Fellow of the Higher Education Academy (FHEA) Recipient of multiple research grants for projects in optimization and AI applications Advising & Collaboration: Actively supervises PhD students in AI-driven optimization and interdisciplinary applications. Collaborates with institutions globally on topics like microgrid energy management and pandemic prediction through self-organizing maps. Labs & Teams: Engaged in Swansea's Computational Foundry and the Morgan Advanced Studies Institute (MASI), contributing to cross-disciplinary research initiatives in AI and computational science.
Sergio Jiménez Celorrio is a Full Professor at the Department of Computer Systems and Computation of the Polytechnic University of Valencia. He has held previous positions including Ramón y Cajal fellow at the University of Melbourne, Juan de la Cierva fellow at Universitat Pompeu Fabra, and teaching assistant at Universidad Carlos III de Madrid, where he earned a Distinguished Thesis Award in 2011. His research focuses on automated planning, Bayesian inference, and machine learning synergies. He has co-organized the 7th International Planning Competition and contributed to top AI conferences. Education: PhD in Artificial Intelligence from Universidad Carlos III de Madrid (2011, Distinguished Thesis Award). Research interests emphasize automated planning frameworks, heuristic search, and integrating machine learning with planning systems. Awards include the IJCAI 2016 Distinguished Paper Award and Sister Conferences Best Paper Award at IJCAI 2022. His work spans over 50 publications in venues like AI Journal, JAIR, and IJCAI. Advises PhD student Diego Aineto García and collaborates on grants and competitions. Active in organizing conferences and workshops.
Dr. Maxence Delorme is an Associate Professor in Operations Research at Tilburg University, specializing in combinatorial optimization for practical applications. His research develops exact algorithms for complex scheduling, packing, and satellite operation problems. Current projects include kidney exchange optimization, vertical farming energy efficiency, and Mars observation satellite coverage. His work combines mathematical modeling with computational efficiency to solve large-scale optimization problems in healthcare and space technology. Recent publications demonstrate innovations in constraint handling for scheduling problems and heuristic designs for packing challenges.
Rene Peeters is an Assistant Professor at Tilburg University, affiliated with the Department of Econometrics and Operations Research within the Tilburg School of Economics and Management (TiSEM). His research focuses on discrete mathematics, algebraic graph theory, and combinatorial optimization. He holds a Ph.D. from Tilburg University (1991–1995) and has been a faculty member since 1995. His work spans theoretical contributions to graph theory and practical applications in logistics, including urban freight transportation and vehicle routing problems. In logistics research, he addresses challenges such as optimizing delivery routes, outsourcing strategies, and stakeholder collaboration in urban settings. His technical contributions include advancements in variable neighborhood search algorithms and matrix theory, particularly in analyzing adjacency matrices and (0,1)-matrices. Peeters teaches courses like Combinatorial Optimization and coordinates the Improving Society Lab for EOR (Econometrics and Operations Research).
Andrew Ching, PhD (University of Minnesota), is a full professor at the Johns Hopkins University's Carey Business School with joint appointments in the Department of Economics and the Bloomberg School of Public Health. He co-founded the Digital Business Development Initiative (DBDI) and holds roles in Hopkins Business of Health Initiative and the Canadian Centre of Health Economics. Prior roles include faculty positions at University of Toronto and Ohio State University, along with visiting professorships at UCLA, Cornell, and others. He serves on editorial boards for journals like Marketing Science and Management Science , and Hong Kong Research Grant Council's Business Studies Panel. His research focuses on structural models analyzing consumer and firm behavior under complex environments, including rational inattention, exploration-exploitation dilemmas, and bounded rationality. Applications span prescription drug demand, nursing home markets, technology adoption, payment methods, and video game markets. Recent work integrates AI/ML tools for adaptive learning modeling. Key awards include the Young Economist Award (European Economic Association), SSHRC grants, and Distinguished Visiting titles at CUHK and Peking University. His students have won MSI and ISMS dissertation awards. Articles appear in Econometrica , Marketing Science , and Management Science . Education includes a PhD in Economics from the University of Minnesota, MAs from Minnesota and UBC, and a BA from ANU. Teaching focuses on customer analytics and health marketing.
Bettina Speckmann is a full Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU Eindhoven), where she leads the Applied Geometric Algorithms group. She holds additional appointments as EAISI Health Professor and EAISI Foundational Professor, and is affiliated with the Data Science Center Eindhoven. Her research bridges theoretical algorithm design with practical applications in spatial computing. Her research interests lie primarily in computational geometry and geometric algorithms, with strong applications in GIScience, Smart Mobility (including moving object analysis and automated cartography), geo-visualization, visual analytics, and e-Humanities. She focuses on developing efficient algorithms and data structures for spatial data, combining rigorous theoretical methods with practical engineering for real-world impact. Her recent publications (2025) show a strong trend in geometric data processing, particularly in polycube segmentations, dual loop algorithms, density estimation for moving groups, and topological analysis using merge trees and Fréchet distances. These works reflect her interdisciplinary focus on computational geometry, visualization, and data structures. Scientific awards received include: Netherlands Prize for ICT Research (2011) NWO Vici Award (2012) PEriTiA Prize (2020) Bettina Speckmann has advised numerous students and researchers through her group and has secured major grants, including the NWO Vici. She has served in leadership roles such as PC co-chair for Graph Drawing (GD 2011), PC chair for ICALP Track A (2015), and PC co-chair for SoCG (2018). She teaches courses such as Data Structures and Heuristic Algorithms. She leads the Applied Geometric Algorithms group, which actively collaborates with industry partners like HERE Global B.V., Fugro NL Land B.V., and OCLC B.V., and contributes to UN Sustainable Development Goals in areas related to data and mobility.
Hila Peleg is an Assistant Professor in the Department of Computer Science at the Technion – Israel Institute of Technology, where she co-leads the TecSE lab with Prof. Shachar Itzhaky. Her research lies at the intersection of Programming Languages, Software Engineering, and Human-Computer Interaction, focusing on program synthesis and interactive developer tools. Her research interests center on creating intelligent, theory-driven tools that enhance programmer productivity and correctness. She explores interaction models that integrate formal methods like separation logic into practical synthesis systems, enabling more versatile and reliable code generation. Her work spans both foundational models and real-world applications, from web layout synthesis to computational crafting. The trend in her recent publications shows a strong focus on interactive and practical program synthesis, blending formal verification with user-centered design. She investigates how synthesis can be made more usable through live programming, best-effort results, co-design of tools and languages, and integration with developer workflows. Her work increasingly emphasizes the human aspect of programming tools. Distinguished Paper Award, PLDI 2021 Distinguished Artifact Award, SPLASH 2020 Hila Peleg advises multiple graduate students, including PhD and MSc candidates, and leads the ERC-funded EXPLOSYN project, which supports advanced research in program synthesis. She has taught advanced courses such as User-Centered Programming Tools and seminars in programming languages, and is actively involved in the academic community through conference service and organization. She is a core member of the TecSE lab, which focuses on advancing software engineering through programming language theory and interactive systems. The lab fosters interdisciplinary research at the boundary of formal methods and human-centered tool design.
Snezana Mitrovic Minic is an Adjunct Professor in the Department of Mathematics at Simon Fraser University, Surrey. She holds a PhD in Computing Science from Simon Fraser University, an MSc in Applied Mathematics from the University of Belgrade, and a BSc in Mathematics from the same institution. PhD : School of Computing Science, Simon Fraser University MSc : Applied Mathematics Program, Faculty of Electrical Engineering, University of Belgrade BSc : Faculty of Mathematics, University of Belgrade Her research lies at the intersection of operations research and applied discrete mathematics, with focus areas including discrete optimization, graph theory, vehicle routing, scheduling, and algorithm design. She has conducted significant research on the dynamic pickup and delivery problem with time windows (PDPTW), contributing benchmark test instances widely useful in algorithmic development. She has collaborated with leading researchers such as Prof. Abraham Punnen, Prof. Peter Borwein, Prof. Gilbert Laporte, Prof. Binay Bhattacharya, and Dr. Emina Krcmar on projects involving integer programming, health care modeling, and heuristic methods in logistics and forestry. Her teaching portfolio includes courses such as MATH 343, MATH 157, CMPT 307, and CMPT 201, covering calculus, discrete mathematics, data structures, and algorithms. Dr. Mitrovic Minic is professionally affiliated with major operations research societies: IFORS (International Federation of Operational Research Societies) CORS (Canadian Operational Research Society) EURO (Association of European Operational Research Societies) EWG Transportation (EURO Working Group on Transportation) INFORMS (Institute for Operations Research and the Management Sciences) She has over ten years of industry experience as a software engineer and analyst in real-time control systems, bridging theoretical research with practical software development. Her academic work is supported by a strong technical background and active participation in the global OR community.
Wil Michiels is a Full Professor (part-time) at Eindhoven University of Technology (TU/e), affiliated with the Security group within the Department of Mathematics and Computer Science. His research focuses on cryptography and cybersecurity, particularly in white-box cryptography, cryptanalysis, and secure implementations. He collaborates with industry partners like NXP, working one day a week at TU/e while maintaining his role at NXP. Michiels' research explores topics such as differential computation analysis (DCA), fault injection attacks, and traceability mechanisms in cryptographic systems. His work emphasizes practical security challenges, including defending against reverse engineering and ensuring incompressibility in cryptographic primitives. Notable contributions include studies on grey-box attacks and watermarking techniques for pay-TV systems. His publications highlight advancements in cryptographic protocols and secure software distribution. Despite no explicit mention of awards, his active role in both academia and industry underscores his contributions to applied cryptography. Michiels' ancillary activities at NXP reflect his industry engagement, though specific grants or lab affiliations are not detailed in the provided texts.
Enes Bajrovic is a researcher affiliated with the Faculty of Computer Science, focusing on high-performance computing (HPC), big data processing, and performance portability. His work spans task-based parallelism, runtime systems, and optimization frameworks for heterogeneous architectures. He has contributed to major European projects like PEPPHER and AutoTune, which aim to advance HPC software tools and autotuning methodologies. His research emphasizes practical applications of parallel computing in domains such as mobile networks and scientific simulations. Education: Dipl.-Ing. Dr.techn., BSc in Computer Science His research interests include developing frameworks for compute- and data-intensive applications, leveraging technologies like Kubernetes, OpenCL, and Intel Xeon Phi coprocessors. He has authored numerous peer-reviewed publications on topics such as pipeline patterns, autotuning algorithms, and hybrid execution models. His work bridges theoretical advancements in parallel computing with real-world software engineering challenges. Bajrovic has collaborated on projects funded by the European Commission’s FP7 program, contributing to deliverables like runtime systems, tuning frameworks, and benchmarking tools. His research also addresses the integration of big data processing with HPC, particularly in telecommunications and distributed computing environments.
Dr. Onur Kilic is an Associate Professor at the Faculty of Economics and Business, University of Groningen. He holds a BSc and MSc from Hacettepe University (2016) and a PhD from the University of Groningen (2011). His research focuses on mathematical modeling and optimization in production systems, inventory management, scheduling, and maintenance. He has published in top-tier journals including European Journal of Operational Research and INFORMS Journal on Computing. Kilic's work addresses practical challenges in supply chain optimization, stochastic systems, and energy logistics. Education: BSc/MSc: Hacettepe University (2016) PhD: University of Groningen (2011) Research Interests: Inventory Control and Stochastic Systems Production Planning and Scheduling Optimization in Supply Chains Mathematical Modeling for Industrial Applications Energy Logistics and Offshore Wind Farm Operations Recent Articles Highlight: His 2024 publications address condition-based maintenance optimization, production loss reduction in food manufacturing, and advanced inventory heuristics. His work on offshore wind farm decommissioning (2022) and LNG inventory policies (2020) demonstrates expertise in energy sectors. Grants and Projects: Co-PI: Service Logistics for Offshore Energy Production (NWO grant, 2019-present) PI: Stochastic Inventory Control in Hybrid Systems (TUBITAK grant, 2014-2018) Labs/Teams: Actively involved in operations research and management science initiatives within the Faculty of Economics and Business.
Ricardo Mallol Poyato is an Associate Professor at the University of Alcalá, affiliated with the Department of Signal and Communication Theory within the College of Engineering. His research focuses on optimization algorithms applied to energy systems, particularly in microgrid design, renewable energy integration, and evolutionary computation. He leads the GHEODE research group (Modern Heuristics and Network Design Research Group), specializing in heuristic optimization for communication networks and energy systems. He earned his doctorate from the University of Alcalá in 2016 with a thesis titled Optimización del diseño y la operación de redes eléctricas inteligentes mediante computación evolutiva , supervised by Dr. Sancho Salcedo Sanz and Dr. Pablo Díaz Villar. His work bridges theoretical algorithm development with practical applications in energy infrastructure and engineering education. Key research interests include: Optimal design of microgrid topologies Renewable energy resource allocation Evolutionary algorithms for energy systems Thermal management of solar modules Computational methods for control systems His publications emphasize innovative optimization techniques like coral reefs algorithms and harmony search, applied to battery scheduling, distributed generation placement, and scenario-based microgrid operation under variable pricing. He has developed educational software tools for solar energy instruction and contributed to lightweight construction technologies using infrared heating systems.
Mark Leung is a Professor of Management Science and the Associate Dean for Undergraduate Studies at the University of Texas at San Antonio (UTSA), Carlos Alvarez College of Business, Department of Management Science & Statistics. He has been a faculty member at UTSA since 1999, establishing himself as a prominent researcher and educator in operations management and business analytics. University: University of Texas at San Antonio College: Carlos Alvarez College of Business Department: Department of Management Science & Statistics Position: Professor and Associate Dean for Undergraduate Studies Leung's research spans multiple domains at the intersection of operations research, finance, and artificial intelligence. His primary research interests include business forecasting and modeling, financial market and investment strategies, neural network and artificial intelligence techniques in business and data mining, and supply chain and operations management. His work demonstrates a consistent focus on applying advanced quantitative methods to solve complex business problems, particularly in financial engineering and operational optimization. His recent publications reveal a strong emphasis on machine learning applications for financial hedging, particularly in energy markets, where he has developed innovative cross-learning machine approaches that outperform traditional methods. Leung has also published extensively on supply chain optimization, auction bidder behavior, and production system management. Col. Jean Migliorino and Lt. Col. Philip Piccione Endowed Research Award (2001) University of Texas System Chancellor's Council Outstanding Teaching Award (2002, 2005) University of Texas System Regents' Outstanding Teaching Award (2013) Endowed 1969 Commemorative Award for Overall Faculty Excellence (2016) Undergraduate Research Faculty Mentorship Award (2018) As Associate Dean for Undergraduate Studies, Leung has played a significant role in shaping business education at UTSA. His teaching excellence has been consistently recognized through multiple awards including the All-Star Professor Award (2013-2016) and the Best Undergraduate Professor Award (2012). He teaches across all levels (undergraduate, graduate, and doctoral) in business forecasting, production and service operations, supply chain management, and applied business statistics. Leung's research program demonstrates strong industry relevance, particularly in financial engineering applications where his work on machine learning approaches for energy market hedging has provided practical solutions for risk management. His collaborations with researchers across multiple disciplines have resulted in a substantial publication record in high-quality journals.
