Dipl.-Ing. Dr. Gerald Franzl is a Researcher at the University for Continuing Education Krems' Center for Distributed Systems and Sensor Networks. He holds a PhD and Dipl.-Ing. in Electrical Engineering from TU Wien. His career includes roles at MEDIORNET GmbH (2004–2007), IES Austria (2016–2019), and contributions to projects like SONDER and cFlex since 2020. He focuses on smart energy systems, optical networks, and EV charging infrastructure. Education: TU Wien (PhD 2015, Dipl.-Ing. 2002). Certifications: Junior Project Manager (IPMA Level_D), ISTQB Tester, and Digital Transfer Manager. Research interests include QoS routing, energy community frameworks, and interoperability standards. Key projects include Digitally Integrated Power Supply for EV Charging at Work (2023–2026) SONDER and cFlex energy communities (2019–2023) Publications span smart grid optimization, EV charging simulation, and energy market integration. His work emphasizes cross-sector knowledge transfer and sustainable energy solutions.
Chadjiconstantinidis Stathis is a Professor at the Department of Statistics and Insurance Science, University of Piraeus. He earned his Doctorate in Statistics (1990) and Diploma in Mathematics (1985) from Aristotle University of Thessaloniki. His academic roles include undergraduate and postgraduate teaching across multiple institutions including the University of Athens and Athens University of Economics and Business. Research Focus: His work spans actuarial mathematics, risk theory, and statistical optimization. Primary domains include: Ruin theory and bankruptcy modeling in insurance contexts Collective risk models with dependencies Optimal experimental designs for statistical efficiency Reliability theory and stochastic pattern analysis Publications: His 15 most recent articles show consistent focus on risk modeling (compound processes, ruin probabilities) and statistical design optimization (D-optimal cyclic designs). Actuarial mathematics dominates newer works (2005–2013), while earlier publications emphasize experimental design combinatorics. Academic Leadership: Department President (2007–2009) Director of Master’s Program in Actuarial Science & Risk Management (2007–2011) Deputy Chairman of Actuary Licensing Committee (Ministry of Finance) Senate Member at University of Piraeus (1997–1998, 2007–2009) Doctoral Supervision: Mentored dissertations on risk theory and statistics pedagogy. Current advisees not specified.
Victor Pestien is an Associate Professor in the Department of Mathematics at the College of Arts and Sciences, University of Miami. His research focuses on stochastic models, queueing theory, and discrete-time network analysis. Role: Associate Professor, Mathematics University: University of Miami Victor Pestien's work examines stochastic networks , Markov processes , and queueing systems with applications in computer networks and decision models. His studies analyze throughput limits, occupancy distributions, and reward functions under varying service rate dependencies. Key publication trends include discrete-time cyclic networks (2002-2008), Markov-achievable payoffs (1993, 1998), and noisy-channel transmission (1994). Collaborations with researchers like S. Ramakrishnan and Hans Daduna highlight his focus on network stability and throughput optimization. Victor Pestien's email is pestien@miami.edu .
Irene Crimaldi is an Associate Professor of Statistics at IMT Lucca (Italy) since 2011. She serves on the Scientific Board of IMT's PhD programs . Her academic journey includes roles as a researcher and part-time professor at the University of Bologna (2006-2011) and a tenured assistant professor at IMT Lucca (2011-2014). Crimaldi holds a cum laude degree in Mathematics from the University of Pisa and a cum laude PhD in Financial Mathematics from the Scuola Normale Superiore (Pisa). She has received scholarships from Istituto Nazionale di Alta Matematica and fellowships from University of Pisa and University of Bologna . Her research focuses on Probability and Statistics with applications in Economics, Social Sciences, Computer Science, and Engineering . Key areas include interacting reinforced stochastic processes , network modeling , urn models , species sampling , and stable convergence . She has co-authored influential works on synchronization phenomena, systemic risk in OTC markets, and latent attribute network models. Crimaldi's peer-reviewed publications span 15 most recent articles (2013-2025) addressing synchronization rates, network dynamics, and systemic risk. These works employ stable convergence, central limit theorems, and reinforcement mechanisms, contributing to disciplines like stochastic processes, financial mathematics, and network science. She actively collaborates with institutions such as the University of Bologna , University of Pisa , and IMT Lucca , integrating mathematical rigor with real-world applications in financial systems and social networks.
Maud Van den Broeke is a Full Professor in the field of Operations Management at IÉSEG School of Management in Lille, France since 2016. She holds a Ph.D. in Business Economics from KU Leuven (2016) and additional Master's degrees from Vlerick Business School (2011) and KU Leuven (2010). Ph.D. in Business Economics - KU Leuven (2016) Master in General Management - Vlerick Business School (2011) Master in Commercial Engineering - KU Leuven (2010) Her research focuses on Operations Management with emphasis on innovation ambidexterity, supply chain flexibility, and production optimization. Recent publications examine: Roles of flexibility in innovation and performance Educational simulations for operations research R&D investment dynamics Cost-minimizing platform design Forecast adjustment behaviors Notable achievements include: Finalist, Franz Edelman Award (2017) Best Thesis Award, VIB (2010) She teaches Introduction to Operations Management at the bachelor level and has contributed to refereed journals including Journal of Business Research , European Journal of Operational Research , and Omega .
Sid Banerjee is Assistant Professor in Operations Research at Cornell Engineering, developing stochastic models and algorithms for large-scale systems including online marketplaces and transportation networks. Research creates optimization frameworks for ridesharing platforms, two-sided market segmentation, and efficient resource allocation under uncertainty. Methods combine queueing theory, game theory, and approximation algorithms. Honored with INFORMS awards, he investigates collaborative platform incentives, personalized recommendation systems, and dynamic pricing strategies for shared vehicle systems. Teaching covers stochastic processes, algorithm design, and optimization methods at undergraduate and graduate levels.
Mark E. Lewis is the Maxwell M. Upson Professor of Engineering at Cornell University, affiliated with the School of Operations Research and Information Engineering within the College of Engineering. He previously served as an Associate Dean and Senior Associate Dean for diversity and faculty development in Cornell Engineering, and co-founded the INFORMS Minority Issues Forum to support underrepresented minorities in academia. His leadership roles include chairing the INFORMS Applied Probability Society and serving on the Provost’s Task Force to Enhance Faculty Diversity. Education: Ph.D. in Industrial & Management Engineering (Georgia Tech, 1998), Master’s in Theoretical Statistics (Florida State, 1995), and undergraduate degrees in Mathematics and Political Science (Eckerd College, 1992). Postdoctoral work at the University of British Columbia’s Center for Operations Excellence. Prior faculty positions at University of Michigan and University of Michigan. Research focuses on dynamic control of service systems using stochastic dynamic programming and Markov decision processes. Key areas include resource allocation in queueing networks, inventory systems, transportation, and healthcare. Sub-areas involve bias optimality, non-stationary systems, and MDP convergence. Applications span telemedicine, emergency medical services, and large-scale computing networks. Recent publications emphasize telemedicine physician staffing, constrained queueing optimization, and flexible server scheduling in dynamic systems. Articles reflect a strong focus on healthcare systems, network science, and stochastic control. Recipient of Faculty Award for Excellence in Research, Teaching & Service through Diversity (2021) PECASE Award (2002) Frontiers on Engineering Participant (2007) Named INFORMS president-elect for 2025-2026 Advising contributions include mentoring doctoral students in diversity-focused programs and co-creating the Ephraim Garcia Engineering Society. Grants secured include funding for Cornell Sloan and Colman fellowships for underrepresented students, and postdoctoral fellowships. He also oversees Diversity Programs in Engineering to provide academic support for first-generation and minority students. Labs/Teams: Active in Cornell’s Office of Faculty Development and Diversity, co-chair of the 2009 INFORMS Applied Probability Conference, and collaborates with the Cornell Center for Health Equity (through service roles).
Bas Luttik is an Associate Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), with a secondary appointment as an EAISI Foundational Associate Professor. His research focuses on concurrency theory, process algebra, and formal methods applied to railway systems. He holds an MSc and PhD from the University of Amsterdam, followed by postdoctoral work at Vrije Universiteit Amsterdam. His academic contributions include foundational work on parallel decomposition, process algebra semantics, and the integration of concurrency theory with automata theory, notably through the theory of Reactive Turing machines. Education background: MSc Computer Science (1996), University of Amsterdam PhD Computer Science (2002), University of Amsterdam (supervised by Jan Friso Groote at CWI) Research interests emphasize formal verification, process algebra, and practical applications in railway safety. Notable awards include the FMICS Best Paper Award (2018). He teaches courses like Logic and Set Theory, developing innovative digital tools for self-paced learning and homologation recommendation systems. Active in conference organization, he has chaired program committees for EXPRESS/SOS (2011–2013) and contributed to CONCUR, TTCS, and others. His work bridges theoretical foundations (e.g., bisimulation, executability) with applied systems (e.g., EULYNX railway interfaces). Supervised 30+ students, though specific names are not listed here. Research collaborations span international teams, focusing on concurrency, automata, and formal methods in critical systems.
Dr. Setareh Farajollahzadeh is an Assistant Professor of Operations Management at the Desautels Faculty of Management, McGill University. She holds a Ph.D. in Operations Management and Statistics from the Rotman School of Management, University of Toronto (2017–2023), an MBA (with thesis) from Sharif University of Technology (2014–2016), and a B.S. in Industrial Engineering from Sharif University of Technology (2010–2014). Her research focuses on socially responsible and revenue management operations problems, employing techniques such as network games, queueing theory, capacity management, learning, and data-driven algorithms. Key research areas include pricing strategies, sustainable operations, and data science applications in online marketplaces. She co-founded the Rotman Young Scholar Seminar series to foster academic collaboration. Her recent work explores topics like robust price experimentation, diversity in labor markets, stadium restroom design for equity, and consumer preference learning. Over 2023–2025, her research has been applied commercially (e.g., PricingService.ai) and recognized in conferences like INFORMS, CORS, and MSOM. Notable Awards: Winner of CORS Student Paper Competition (2023), INFORMS Case Competition (2023), and Finalist for DEI Best Student Paper Award (2023). Active in organizing academic sessions, including the Retail and Revenue Management cluster at the 2025 CORS conference. Labs/Teams: Co-founder of the Rotman Young Scholar Seminar series, promoting interdisciplinary research collaboration among junior scholars.
Veronica Ciocanel is an Assistant Professor of Mathematics (Primary) and Biology (Joint) at Duke University, with a focus on mathematical modeling and analysis in cell and developmental biology. Her research integrates applied mathematics, stochastic processes, and topological data analysis to study intracellular transport, filament organization, and symmetry transitions in biological systems. Education: PhD in Applied Mathematics, Brown University (2017) MSc in Applied Mathematics, Brown University (2013) BS in Mathematics and French, Duke University (2012) Research Interests: Mathematical modeling of mRNA transport and cytoskeletal dynamics Parameter inference and identifiability in biophysical models Applications of topological data analysis to biological systems Modeling symmetry transitions and pattern formation Scientific Awards: 2025 Lee A. Segel Prize for Best Paper in Bulletin of Mathematical Biology 2015 Red Sock Award (SIAG/Dynamical Systems) for Best Poster Presentation Professional Activities: Active mentor in undergraduate research programs Organizer of workshops and conferences in mathematical biology Collaborations with experimental labs (e.g., Mowry, Rolls, Silver) Labs/Teams: Collaborates with interdisciplinary teams in mathematical biology, cell biology, and computational topology.
Martin Reisslein is a Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His research focuses on advanced networking technologies, cybersecurity, and edge computing, with a specialization in Time-Sensitive Networking (TSN), 5G, and network coding. He collaborates closely with institutions like the National Research Data Infrastructure (NFDI) and has published extensively in top-tier journals and conferences. His work spans theoretical and applied domains, including hardware-software co-design for low-latency systems, cybersecurity for satellite and IoT networks, and AI-driven resource management in transportation networks. Recent projects highlight contributions to TSN testbeds, molecular communication simulations, and unified threat management systems for home networks. Reisslein has co-authored over 270 publications, with notable contributions in IEEE Transactions on Networking, Communications Surveys & Tutorials, and the Journal of Signal Processing Systems. His research emphasizes practical implementations, such as hardware-aligned TSN simulations and flexible measurement frameworks for edge computing.
Jong-Deok Kim is an active researcher in wireless communication and IoT systems, with frequent collaborations on publications spanning dynamic channel bonding, network optimization, and low-power protocols. His work addresses challenges in Wi-Fi, LoRa, and millimeter-wave networks, focusing on throughput, latency, and reliability. Research Focus: Wireless networks, edge computing, and blockchain for IoT. Key Topics: Channel allocation, federated learning, and error compensation methods. His recent publications highlight trends in adaptive algorithms for dense networks, hybrid positioning systems, and federated learning applications. Awards and grants are not explicitly mentioned in the provided data.
Prof. Dr. Simone Neumann is a Professor of Sustainable Logistics and Mobility at the University of Hamburg, affiliated with the Business School. Her research focuses on optimizing transportation systems, particularly airplane boarding processes and storage automation. She leads a team including Yağmur Gül, Philipp Koch, Christiane Andresen, and Paul Mohr. Department: Sustainable Logistics and Mobility Address: Moorweidenstraße 18, Room 2007, 20148 Hamburg Contact: Tel: +49 40 428 38-9233 | Email: simone.neumann@uni-hamburg.de Her research interests span operational efficiency, passenger behavior analysis, and logistics automation. Recent work includes studies on intermodal transport coordination, agent-based modeling for boarding efficiency, and 5G applications in intralogistics. She is involved in the DDLitLab: Data Literacy for Algorithmic Decision Support project. Publications highlight contributions to transportation optimization and logistics innovation, with a focus on sustainable systems and data-driven decision-making.
Dr. Yassine Ouazene is an Associate Professor at the Université de Technologie de Troyes (UTT, France) since 2014, with an HDR (Accreditation to Supervise Research) from the University of Technology of Compiègne (2024). He holds a PhD and Master’s in Optimization and Safety of Systems (UTT, 2013 and 2010) and an Industrial Engineering degree from the National Polytechnic School of Algiers (2009). His research focuses on combinatorial optimization and operations research, applied to production planning, energy management, and smart pricing. He has authored over 100 publications, including 27 journal articles, and received awards such as the IEEE-IFAC CODIT Best Paper Award (2014), Booster Research Prizes (2020, 2022), and the National Council of Universities’ Premium of Scientific Excellence (2019). Current work includes healthcare system resilience, energy-efficient scheduling, and Industry 4.0 applications in manufacturing. He leads projects at the intersection of optimization algorithms, production systems, and sustainable innovation. His academic contributions span dynamic pricing models, nurse scheduling optimization, and multi-criteria decision-making in energy and healthcare sectors. He collaborates with industry partners on practical implementations of his research findings.
Adrien Wartelle is an Associate Professor at Toulouse Institute of Computer Science Research (IRIT) and Institut National Universitaire Champollion since September 2025, specializing in health and production system modeling through statistical, queuing, and optimization tools. His primary affiliation is with the Argumentation, Décision, Raisonnement, Incertitude et Apprentissage (ADRIA) team within IRIT's Faculty of Computer Science. His research focuses on health system optimization with expertise in emergency department operations, multimorbidity analysis, and semiconductor manufacturing optimization. Key methodologies include queuing models, digital twin development, machine learning applications, and statistical analysis of complex systems. His work bridges healthcare operations and industrial engineering through data-driven approaches to system crowding and resource allocation. Analysis of his 14 publications reveals strong emphasis on emergency department congestion measurement (60% of works), semiconductor manufacturing optimization (20%), and healthcare patient flow modeling (20%). His recent work demonstrates increasing integration of machine learning with traditional queuing theory, particularly in real-time congestion indicators for healthcare systems. Scientific Recognition: Nominated for academic prize for pathway of excellence (2019) 14 publications with 1,041 reads and 52 citations Collaborations with Mines Saint-Étienne, University of Technology of Troyes, and Centre Hospitalier de Troyes Wartelle maintains active research in both healthcare and semiconductor domains, having completed post-doctoral research at Mines Saint-Étienne (2023-2025) focused on semiconductor manufacturing systems after his PhD at University of Technology of Troyes (2019-2022) on emergency department optimization. His technical expertise spans C++, R, Linux environments, and object-oriented programming for simulation and optimization applications.
