David Stanford is a Professor in the Department of Statistical and Actuarial Sciences at the University of Western Ontario. He earned his Ph.D. from Carleton University in 1981. His office is located in WSC 211 and he can be contacted via phone (519-661-2111 x83612) or email. Research Focus: Dr. Stanford's research spans several interconnected domains including: Queueing Theory : Specializing in multi-server systems, priority queues, and service optimization Actuarial Science : Risk modeling, ruin theory, and insurance mathematics Healthcare Operations : Applying stochastic models to transplant systems and patient flow Environmental Modeling : Forest fire prediction using compound Poisson processes His work frequently combines theoretical stochastic processes with practical applications in healthcare and environmental systems. Publication Trends: Analysis of recent publications shows a strong focus on queueing theory applications in healthcare systems, particularly modeling patient flow and organ transplant logistics. His actuarial research emphasizes advanced ruin probability calculations and risk process modeling. Environmental applications feature stochastic approaches to natural disaster prediction.
Shensheng Tang is a Professor of Physics and Engineering at Bethel University, College of Arts and Sciences. He joined the university in 2024, bringing extensive academic and industry experience in electrical and computer engineering. He holds a Ph.D. in Electrical Engineering from the University of Toledo and a B.S. from Tianjin University. Ph.D. in Electrical Engineering, University of Toledo, 2006 B.S. in Electrical Engineering, Tianjin University, 1990 Dr. Tang's research focuses on wireless and computer networking, IoT, cloud/fog/edge computing, embedded systems, FPGA, cybersecurity, AI/ML, and performance modeling. His work integrates theoretical modeling with practical applications in smart grids, healthcare IoT, and 5G/Wi-Fi convergence. He has published over 100 peer-reviewed papers, with recent publications emphasizing fog-based IoT performance, cloud system modeling, FPGA acceleration, and network security using spatiotemporal models and machine learning. His publication record reveals a strong trend in applying analytical models—particularly queueing theory, Markov processes, and signal modeling—to optimize network performance, reliability, and security in distributed and resource-constrained environments. He frequently explores cross-layer design in wireless networks and integrates AI techniques for traffic analysis and threat detection. MWSU 2012 Dr. James V. Mehl Outstanding Faculty Scholarship Award Best Paper Award, IEEE/CIC ICCC 2016 Excellent Presentation Award, IEEE ICCSN 2016 Spotlight Paper, IEEE TPDS July 2013 Marquis Who's Who in America (2010–2016 editions) Marquis Who's Who in Science and Engineering (10th–12th editions) Dr. Tang has advised numerous students and researchers throughout his career, though specific names are not listed. He has secured significant research output and editorial leadership roles, serving as Editor-in-Chief for the Journal of Science and Engineering Research (JSER) and Journal of Smart Technology Applications (JSTA), and as editor for several international journals including MDPI's IoT. He has chaired program committees and organizing committees for major conferences such as CMVIT, CCISP, ASSE, and ICCSN. His professional service includes active roles in IEEE (Senior Member), ACM SIGMETRICS, INFORMS, and Sigma Xi. He leads research in performance modeling and optimization for next-generation networks and is involved in editorial and conference leadership that shapes discourse in smart technologies, IoT, and cybersecurity.
Eren Çil is an Associate Professor of Operations and Business Analytics at the Lundquist College of Business , University of Oregon, and serves as the Academic Director for the Oregon MBA program. He holds the Robert J. and Leona M. DeArmond Research Scholar title, reflecting his contributions to service operations research. Education : PhD in Operations Management from Northwestern University (2010), MS in Industrial Engineering from Koç University (2006). Professional Affiliations : Member of INFORMS, POMS, and M&SOM societies. Research Interests focus on service operations management , queueing theory , game theory , strategic pricing , and supply chain optimization . His work addresses challenges in large-scale service systems, competitive pricing dynamics, and sustainable supply chain design. Recent Publications demonstrate interdisciplinary applications spanning healthcare operations, retail strategies, and service platforms. Key themes include dynamic pricing , resource allocation , and system optimization under uncertainty. Notable Contributions include studies on: Emergency department admissions in the context of ride-sharing platforms Mass customization strategies in competitive markets Recycling incentives in closed-loop supply chains Customer retaliation and disguised queues Queueing control policies for multi-class systems Collaborations with scholars like Michael Pangburn and Nagesh Murthy highlight his focus on practical problem-solving in service and healthcare operations.
Marla Bell is a Professor of Mathematics and Associate Dean for Student Success at the College of Science and Mathematics, Kennesaw State University. She specializes in applied statistics and data analysis, with over 30 years of academic experience rooted in mathematical sciences. Ph.D. in Mathematical Sciences (1993) from Clemson University M.S. in Mathematical Sciences (1989) with Statistics concentration B.S. in Mathematics (1986) summa cum laude Her teaching portfolio includes graduate courses in mathematical statistics, statistical methods, and regression analysis, alongside undergraduate instruction in statistical software applications. Research interests span: Statistical modeling for public health applications Markov renewal processes in queueing theory Applied regression techniques Mathematical systems analysis
Mehrdad Moharrami is an Assistant Professor in the Department of Computer Science at the University of Iowa . He specializes in reinforcement learning, Markov decision processes, and random graph models for economics and computational systems. Education : BSc in Mathematics and Electrical Engineering from Sharif University of Technology; MSc in Electrical Engineering and Mathematics from University of Michigan; PhD in Electrical Engineering from University of Michigan (2020) His research focuses on robust reinforcement learning algorithms under distributional shifts and network structure analysis using parameterized random graphs. Recent work explores societal systems modeling and risk-sensitive control frameworks. Moharrami's publications demonstrate interdisciplinary expertise across computer science, mathematics, and network science , with notable contributions to: Risk-sensitive reinforcement learning (ICML 2025, Mathematics of Operations Research 2024) Random graph modeling (COLT 2025, Random Structures & Algorithms 2024) Network optimization (IEEE Transactions on Network Science 2024, IEEE Transactions on Information Theory 2023) Scientific recognition includes: Rackham Predoctoral Fellowship (2019) NSF MPS Workshop participation (2022) Multiple conference best paper nominations Iranian National Olympiad medals (2007-2008) As co-organizer of major workshops (SIGMETRICS 2022, Performance 2023), he actively contributes to academic community development while maintaining active referee roles for top journals like IEEE/ACM Transactions on Networking and Mathematics of Operations Research.
Hubert Missbauer is a Full Professor for Production and Logistics Management at the University of Innsbruck. He holds a Diploma (1982) and Doctorate (1986) in Business Administration from the University of Linz, with a Habilitation in Business Administration (1994) focusing on manufacturing planning systems. His research emphasizes production planning concepts, workload control, and optimization in manufacturing systems, particularly in steel production. He co-organizes the International Working Seminar on Production Economics and serves on the editorial board of the International Journal of Production Economics . Research interests include order release optimization, production scheduling in steel industries, and quantitative methods in operations management. Recent work focuses on Lagrangian decomposition algorithms, behavioral perspectives in workload control, and integrated scheduling in steel production processes. He has published extensively in top-tier journals like International Journal of Production Research and European Journal of Operational Research . Education: University of Linz (Diploma 1982, PhD 1986, Habilitation 1994) Affiliations: Institute for Information Systems, Production and Logistics Management at University of Innsbruck Key Projects: Steel production scheduling, iterative LP-simulation algorithms, behavioral studies in manufacturing control Editorial Roles: Guest Editor for International Journal of Production Economics since 2020 His work bridges theoretical models (e.g., clearing functions, transient analysis) with practical applications in industries like steelmaking and construction. Recent presentations include discussions on Lagrangian approaches at the INFORMS Annual Meeting (2024) and EURO conferences.
Francesco Viti is an Associate Professor in Engineering Science (Traffic Planning and Management) at the University of Luxembourg, leading the MobiLab Transport Research Group within the Department of Engineering. His research focuses on mobility analysis, transport electrification, intelligent transport systems, and data science applications in transportation. He coordinates projects on public transport electrification, Mobility-as-a-Service (MaaS), and freight logistics optimization. Viti has authored over 250 publications and serves as an associate editor for journals like Transportation Research Part C. He advises the Luxembourgish government and the European Commission on transportation policy. Research Interests: Viti’s work spans traffic flow theory, transport electrification, MaaS modeling, and data-driven solutions for urban mobility challenges. Current projects include optimizing electric feeder bus services, analyzing ride-hailing fleet management under dynamic energy prices, and enhancing freight train operations through maintenance simulation. Key Contributions: His group develops models for synthetic population generation, demand estimation using crowdsourced data, and network equilibrium under interacting mobility providers. Recent studies explore the integration of digital twins for urban mobility and CCAM systems, as well as the impact of total cost of ownership on MaaS adoption.
Sara Alouf is an Associate Researcher and Vice-Head of the Network Engineering and Operations (NEO) project team at Inria Sophia Antipolis Méditerranée. She holds a Habilitation from Université Côte d'Azur (2017), a Ph.D. in Network Sciences (2002), and an M.Sc. (1999) from Université Nice Sophia Antipolis, along with an Electrical and Electronics Engineering Degree from Lebanese University (1998). Her research focuses on stochastic modeling , caching systems , and performance evaluation of communication networks , with past work in green networking , peer-to-peer storage , and delay-tolerant networks . Education: Habilitation (2017) - Université Côte d'Azur Ph.D. (2002), M.Sc. (1999) - Université Nice Sophia Antipolis Electrical Engineering (1998) - Lebanese University Her recent work involves no-regret caching algorithms , stochastic solar energy models , and count-min sketch analysis , while earlier research addressed power saving in cellular networks and WiMAX sleep mode optimization . Articles span topics like multi-level cache hierarchies , peer-to-peer storage reliability , and evolutionary network protocols . She has co-authored three patents related to congestion avoidance and RTT estimation . Scientific awards include the Best Paper Award at IFIP Wireless Days 2009 . Professional service highlights: Board of Directors - ACM SIGMETRICS (2019-2023) Editorial roles at IEEE/ACM Transactions on Networking and Elsevier journals Conference organization for ACM Sigmetrics/IFIP Performance (2016, 2024) and ITC (2015, 2023) She has taught Performance Evaluation of Networks at Université Nice Sophia Antipolis, Probabilities and Statistics (with Giovanni Neglia), and Optimization of Business Processes at Vrije Universiteit Amsterdam. Her lab (NEO) investigates network stochastic models , green IT solutions , and train control communication systems .
Samira Shirzaei Nichols serves as an Assistant Professor in the Department of CISA (Computer Information Systems and Analytics) at the College of Business, University of Central Arkansas (UCA), with contact details including email sshirzaei@uca.edu, office COB 305D, and phone (501) 450-5331. Her academic role integrates quantitative analytics with real-world problem-solving across public health, social equity, and business operations. Her research spans Operations Research, Public Health, and Gender Equity, employing machine learning, statistical modeling, and simulation to address epidemiological forecasting (HIV/COVID-19), gender pay disparities in academia/business, and service system optimization. Key methodologies include ARIMA/SARIMA time-series analysis, RNN neural networks, mixed-methods approaches, and Society 5.0 simulation frameworks, demonstrating interdisciplinary rigor in translating theoretical models to societal challenges like refugee health access and grocery store operational efficiency. Analysis of her 15 publications (2014-2025) reveals an accelerating focus on public health crises since 2020, with 60% of recent work dedicated to pandemic response modeling and gender equity analysis. While early research centered on supply chain optimization (2014-2018), post-2020 outputs pivot toward urgent health applications—evidenced by 5 COVID-19 forecasting studies—and structural inequities, using comparative data (2018 vs. 2021) to quantify gender pay gaps across academic disciplines. Her work consistently bridges technical analytics with human-centric outcomes. No information is available regarding student advising, grant funding, laboratory facilities, or research teams from the provided sources, though her prolific publication record indicates active scholarly engagement.
Prof. Michal Tzur is a distinguished faculty member at Tel Aviv University's Industrial Engineering Department within The Iby and Aladar Fleischman Faculty of Engineering. She has served as department chair during two separate terms (2004-2006 and 2019-2021) and previously held faculty positions at the Wharton School of the University of Pennsylvania and as a visiting faculty member at Northwestern University's Department of Industrial Engineering and Management Sciences. From 2015-2017, she served as president of the Operations Research Society of Israel (ORSIS). Her research spans multiple critical domains in operations research and industrial engineering, with particular focus on Online Transportation Problems, Machine Learning combined with Optimization, Humanitarian Logistics, Vehicle Sharing Systems, Supply Chain Management, and Inventory Management. Her work demonstrates a consistent evolution from foundational theoretical work in inventory and lot-sizing problems toward increasingly applied research addressing contemporary challenges in transportation, humanitarian logistics, and shared mobility systems. Notably, her recent publications show a strong emphasis on fairness considerations in resource allocation and optimization problems. Prof. Tzur's publication record reveals a clear trajectory from foundational work in inventory theory and lot-sizing problems toward increasingly applied research addressing real-world challenges. Her work on bike-sharing systems represents one of her most impactful research streams, with multiple publications analyzing different aspects of vehicle sharing systems. More recently, she has made significant contributions to humanitarian logistics, with several papers addressing critical challenges in disaster response and resource allocation, earning her a Best Paper Award in 2018. Best Paper Award for 'Designing Humanitarian Supply Chains by Incorporating Actual Post-Disaster Decisions' in European Journal of Operational Research (2018) Prof. Tzur has successfully advised numerous doctoral students, with seven PhD students listed in her record including Mor Kaspi, Iris Forma, Reut Noham, Ohad Eisenhandler, Adi Sarid, Gal Neria, and Gabriel Deza. Her collaborative approach is evident in many of her publications, particularly with colleagues like Tal Raviv, with whom she has jointly supervised several students and co-authored multiple papers. While specific grant information isn't detailed in the provided text, her sustained research output across multiple domains suggests successful funding acquisition throughout her career. Though specific lab information isn't explicitly provided in the text, Prof. Tzur's research appears to be conducted through collaborative efforts within the Industrial Engineering Department at Tel Aviv University, with strong connections to the Operations Research community in Israel and internationally. Her recent work on humanitarian logistics and transportation systems suggests involvement in research groups focused on applied optimization for societal benefit.
Dr. Emre Süren serves as a Researcher at KTH Royal Institute of Technology within the Division of Network and Systems Engineering and concurrently leads Cybercampus Sweden's Royal Hacking Lab as its Head. His dual roles position him at the forefront of national cybersecurity research with extensive collaborations across EU Horizon projects, Swedish government entities, and international academic institutions. His research spans critical domains including LLM security, IoT hacking, cyber threat intelligence, and digital forensics, with particular emphasis on AI-driven vulnerability research. Current work focuses on developing frameworks like CORTEX for AI-enhanced threat intelligence and Applied VORTEX for AI-based vulnerability discovery, supported by substantial grants from Vinnova, Swedish Research Council, and EU Horizon programs. Dr. Süren's publication portfolio demonstrates consistent innovation in security research, with recent articles exploring procedural generation for power systems security, penetration testing methodologies for connected households, and practical IoT threat research frameworks. His work increasingly integrates AI/ML techniques to address evolving cybersecurity challenges, particularly in zero-day exploit detection and IoT security. National Academic Infrastructure for Supercomputing grants (NAISS) for LLM-based threat intelligence EU Horizon funding for DFIRent (AI-assisted digital forensics) Swedish Research Council funding for Applied VORTEX (5.7M SEK) Digital Futures funding for CORTEX (3M SEK) Vinnova Cybercampus grant (17.5M SEK total) As an active educator, he supervises numerous PhD and Master's students on projects ranging from mobile application security to AI-powered honeypot architectures. His technical committee service includes NordSec, DFIR Review, and IEEE Security & Privacy, while his practical contributions include open-source tools like Memotopsy (memory forensics) and PatrIoT (IoT vulnerability research methodology).
Remco Dijkman is a Full Professor in Information Systems and chair of the Information Systems group at Eindhoven University of Technology (TU/e) within the Industrial Engineering and Innovation Sciences school. He leads research in Business Process Management with a focus on data-driven optimization of business processes. His work bridges theoretical advancements with practical applications in transportation and high-tech supply chains. Dr. Dijkman received his PhD and Master's degrees in computer science from the University of Twente. His academic journey includes visiting positions at New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. PhD in Computer Science - University of Twente Master's in Computer Science - University of Twente Professor Dijkman's research focuses on the detection, diagnosis and prediction of optimal execution scenarios, mathematical models for quantitative analysis of business processes, and resource assignment optimization. His work integrates advanced techniques including queueing models, stochastic programming, and deep reinforcement learning to solve complex business process challenges. He has particular expertise in applying these methods to transportation logistics and high-tech supply chain planning, where he investigates how data-driven predictions can improve transport order assignment and supply chain planning. His recent publications demonstrate a strong trend toward integrating artificial intelligence techniques with traditional operations research methods. The research shows increasing sophistication in handling uncertainty in business processes, with a growing emphasis on real-time decision making and optimization. His work spans theoretical advancements in process modeling and practical applications in logistics and supply chain management, reflecting his commitment to bridging academic research with industry needs. Professor Dijkman serves on the editorial board of Information Systems journal and has published over 100 papers in prestigious venues including Information Systems, Computers in Industry, and Transactions on Software Engineering and Methodology. He currently leads or participates in several major research projects including DynaPlex, CERTIF-AI, SLEM, and FENIX. Additionally, he serves as research director for high-tech supply chain at the European Supply Chain Forum, a networking organization with over 50 multinational companies. His adjunct professorship at Queensland University of Technology demonstrates his international academic engagement. Professor Dijkman's research group focuses on developing advanced methods for business process analysis and optimization, with particular emphasis on handling uncertainty and making real-time decisions in complex business environments. The team works closely with industry partners to ensure practical relevance of their research, particularly in transportation and high-tech manufacturing sectors.
Stanislav Lange is an Associate Professor at the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU). His research focuses on network function virtualization, 5G/6G network slicing, quality of service (QoS), quality of experience (QoE), and machine learning applications for network management. His recent publications address decentralized autoscaling, 5G New Radio scheduling impacts, and survivability of network slices during outages. Key trends in his work include network intelligence, in-network computing, and deterministic performance guarantees in virtualized environments. Lange contributes to teaching courses in network programming, cybersecurity, and computer networks for instrumentation. His collaborations span IEEE conferences and journals, addressing challenges in network virtualization, resource optimization, and next-generation communication systems.
Fraser A. Daly serves as Associate Professor in the Department of Actuarial Mathematics & Statistics within the School of Mathematical and Computer Sciences at Heriot-Watt University, Edinburgh. His academic appointment includes leadership roles as undergraduate admissions tutor and instructor for statistical modeling and programming courses. From 2022-2024, he directed the Scottish Mathematical Sciences Training Centre (SMSTC), a consortium serving nine Scottish universities, and previously held positions as MSc Financial Mathematics programme director and Royal Statistical Society Applied Probability section vice chair. Research interests center on applied probability with emphasis on distributional approximation techniques. His work develops theoretical frameworks for approximating complex probability distributions using tractable models like Gaussian or Poisson distributions, with explicit error bounds. Key application areas include random graphs and networks , Markov processes , and actuarial models . The research fingerprint reveals strong focus on approximations (100%), randomness (53%), distribution theory (51%), and Poisson approximation (41%), with significant contributions to Gaussian distribution analysis and graph theory. Analysis of his 15 most recent publications (2021-2025) shows consistent focus on Stein's method applications, distributional approximations across diverse contexts (asymmetric Laplace, geometric-type, negative binomial), and network theory applications. The work demonstrates interdisciplinary reach spanning probability theory, statistical inference, epidemiology modeling, and actuarial science, with increasing emphasis on random graph asymptotics and optimal control in stochastic systems. Professional service includes editorial contributions such as the 2019 Stochastic Networks special issue introduction, reflecting leadership in the probability community. His role in directing SMSTC from 2022-2024 demonstrates commitment to graduate mathematical education across Scotland. Actively supervising PhD students, Daly welcomes projects in random graphs, Markov processes, and actuarial models. His research program shows sustained productivity with 21 total publications including multiple high-impact articles in journals like Scandinavian Actuarial Journal and Journal of Statistical Physics , with growing citation impact (29 Scopus citations for his 2016 Conway-Maxwell-Poisson work).
Dr. Yasir Ali Shah is a Lecturer in Computer Science at Ulster University's School of Computing, Engineering and the Built Environment , based at the Derry~Londonderry campus. His research focuses on hardware design, cryptography, and secure communication systems. Specialization: Post-Quantum Cryptography, Elliptic Curve Cryptography (ECC), FPGA/ASIC implementations Key Contributions: Optimization of cryptographic algorithms for IoT security, high-throughput hardware architectures Recent publications highlight advancements in post-quantum cryptography, including NTT/INTT optimizations, ECC hardware accelerators, and lightweight cipher implementations. His work spans both theoretical and applied domains, with a 2024 study on CPR efficacy indicating interdisciplinary collaborations. Selected trends in research output: 2024: 5 major papers on post-quantum crypto, IoT security, and medical applications 2023: Error-resistant NTT architectures and license plate recognition algorithms 2022: Optical interconnect designs and antiparasitic drug evaluations
