Erdinç Altuğ serves as a Professor in the Department of Mechanical Engineering at Istanbul Technical University, specializing in advanced aerial robotics and control systems. His work bridges theoretical control methodologies with practical UAV applications. Research interests focus on Unmanned Aerial Vehicle design and fault tolerance Quadcopter dynamics and vertical takeoff systems Adaptive control for parametric variations Rapid prototyping of hybrid VTOL platforms His recent publications demonstrate consistent innovation in autonomous flight systems, particularly in fault-tolerant operational modal analysis and modular multi-drone configurations. Current projects include: Hibrit İnsansız Hava Aracı Ile Otonom Teslimat Sistemi Geliştirilmesi (TUBITAK, 2020-2022) Mini Jet Motorlu Dikine Kalkıp İnebilen Otonom Taşıyıcı Robot Geliştirilmesi (TUBITAK, 2018-2021) Kampüs içi ve bina içi ortamlarda çalışacak otonom taşıma aracı algoritmaları (SRP, 2018-2021) Supervising 26 graduate works, his research impacts both academic and industrial UAV development.
Alireza Shokri is a Professor of Digital Operations and Supply Chain Excellence and Head of the Operations, Supply Chain and Logistics Management subject group at Northumbria University's Department of Operations, Marketing and Systems. He directs the Centre for Digital Supply Chain Excellence and serves on the UK National Digital Supply Chain Programme's Academic Advisory Board. Previously, he led the BA (Hons) International Business Management Programme and held practitioner roles in the food sector. He earned his PhD in Lean Six Sigma applications from Teesside University (2011), following degrees in Agriculture Engineering (University of Zanjan) and Food Technology (Teesside University). His research focuses on digital supply chains, operational excellence (OPEX), Lean Six Sigma, and sustainability in manufacturing. Key projects include a £1.3M Digital Catapult-funded initiative on spare parts supply chains and a British Academy-funded study on green Lean Six Sigma. He has led EU-funded projects (GETM3/GEMT4) totaling €2.2M and collaborates with organizations like the NHS and SMEs. Shokri is an editorial board member for the International Journal of Lean Six Sigma and reviews for top journals like the International Journal of Operations and Production Management. He is a Chartered Quality Institute member, Fellow of the Higher Education Academy, and certified Lean Six Sigma Green Belt. Supervising three PhD students, his work bridges academia and industry, emphasizing 'Research in Practice'.
LIU Peng is an Assistant Professor of Quantitative Finance (Practice) at the Lee Kong Chian School of Business, Singapore Management University. He holds a Ph.D. in Statistics and Data Science (Part-time) from the National University of Singapore (2021), an M.S. in Business Analytics (2015), and a B.Eng. in Electronic Science and Technology (2012). Prior to his academic role, he worked as a Manager at Standard Chartered Bank (2019–2022) and in analytics roles at Marina Bay Sands and IBM. Education: Ph.D. (NUS), M.S. (NUS), B.Eng. (Beijing Technology and Business University) His research focuses on generalization in deep learning, sparse estimation, portfolio optimization via reinforcement learning, financial text mining, risk management, and Bayesian optimization. His work bridges theoretical advancements with practical applications in quantitative finance and data science. Notable contributions include studies on explainable neural networks, Bayesian optimization frameworks for portfolio management, and risk analytics integrating human decision-making. His recent articles emphasize model risk assessment, cost-aware optimization, and financial data analysis. Awards: Best Ph.D. Graduate Research Award (NUS, 2020), Google TensorFlow Developer Certificate (2020–2023) He teaches courses in quantitative finance, machine learning, and risk management, and has secured grants including the Research Capability Building Fund (2023–2025). His research aligns with strategic priorities in digital transformation and financial innovation.
Dr. Yu (Chelsea) Jin is an Assistant Professor in the Department of Industrial Engineering at the University at Buffalo, specializing in quality inspection, predictive modeling, and data analytics for advanced manufacturing systems. She holds a PhD in Industrial Engineering from the University of Arkansas, an ME from the University of Michigan, and dual BS degrees in Network Engineering and Finance from Jinan University. Her research focuses on integrating machine learning and physics-based models to optimize manufacturing processes, such as additive manufacturing, PCB assembly, and pharmaceutical distribution systems. She has developed frameworks like ReflowNet for reflow oven optimization and physics-informed neural networks for thermal profile prediction. Her work emphasizes both theoretical advancements and practical applications in smart manufacturing and healthcare logistics. Dr. Jin's recent publications highlight contributions to generative AI for knowledge retrieval, AGV system optimization, and multi-source transfer learning for pandemic modeling. She actively collaborates with industry partners to bridge academic research and real-world manufacturing challenges.
Dr. Nail Tahirov is an Assistant Professor in Operations & Supply Chain Management at Durham University Business School. He holds a PhD in Production and Supply Chain Management from the Technical University of Darmstadt, Germany, and conducted postdoctoral research at the University of Zurich, Switzerland. His research focuses on applying management science techniques to optimize operations across industries, particularly in internal logistics, scheduling, and corporate education. Key areas include sustainable operations, multi-channel supply chain design, and process optimization in manufacturing/service sectors. His publications span European Journal of Operational Research , International Journal of Production Economics , and others, addressing topics like last-mile distribution networks, service-level anchoring in demand forecasting, and closed-loop supply chain optimization. His work emphasizes practical applications such as encroaching manufacturer strategies, workforce scheduling in hospitality, and automated warehouse logistics. Tahirov’s research integrates theoretical frameworks with real-world consultancy projects, aiming to resolve operational inefficiencies in both manufacturing and service industries. No scientific awards are explicitly listed in the provided materials. His advising and grant activities are currently unspecified, though his research collaborations involve institutions like TU Darmstadt, University of Zurich, and industry partners. No dedicated lab or team affiliations are noted in the profile.
Dr. Ding Ze Yang is a Lecturer in the Department of Electrical and Robotics Engineering at Monash University Malaysia. He holds a PhD (2023) and Bachelor's degree (2019) in Engineering from the same institution. His research focuses on Industrial AI, emphasizing data-driven soft sensors for industrial process monitoring, with applications in manufacturing, energy, and logistics. He has published in journals like IEEE Transactions on Industrial Informatics and Soft Robotics. Education: PhD in Engineering, Monash University Malaysia (2019–2023) Bachelor of Engineering (Honours) in Electrical and Computer Systems Engineering, Monash University Malaysia (2015–2019) Research Interests: Industrial AI, deep learning, data-driven modeling, process monitoring, autonomous systems, and soft sensor development. His work addresses challenges in predictive maintenance, process optimization, and sustainable manufacturing through AI-driven solutions. Publications: Recent work includes contributions to soft sensor modeling, transfer learning for multi-agent systems, and Kalman filter optimization. These publications highlight advancements in industrial AI applications. Collaborations: Active collaborations include projects on soft robotics, energy storage systems, and autonomous transportation. He is open to supervising PhD students in these areas.
Professor Felix Schmid holds the position of Honorary Professor in the School of Civil Engineering at the University of Birmingham. He specializes in railway systems engineering, focusing on train control, signaling, economics, and strategic management. He directs the MSc in Railway Systems Engineering and Integration and has developed short programs for organizations like Bechtel and London Underground. His professional affiliations include memberships in the Institution of Mechanical Engineers and the Institution of Railway Signalling Engineers, with roles such as Councillor in the Union of European Railway Engineers’ Associations. Education and Qualifications: Dip.El.Ing.ETH (Swiss Federal Institute of Technology Zurich) PhD in Civil Engineering Chartered Engineer (CEng) European Railway Engineer (EurailIng) Research interests revolve around railway safety, operational efficiency, and systems integration. His work addresses challenges in mega railway projects, urban rail innovation, and infrastructure resilience. He has contributed to over a dozen peer-reviewed articles on topics such as reliability management, accident analysis, and safety-performance relationships. Prof. Schmid’s academic contributions extend to external examining roles at institutions like the University of East London and Kingston University. He delivers lectures on railway capacity management and straw-bale construction. His professional service includes committee roles at Brunel University and the Union of European Railway Engineers’ Associations. Notable awards include Fellowships from the Institution of Mechanical Engineers and the Institution of Railway Signalling Engineers. His external engagements emphasize promoting railway transport and advancing training facilities in the West Midlands.
Aaron J Molstad is an Assistant Professor in the Department of Statistics at the University of Minnesota – Twin Cities, within the College of Science and Engineering. His research lies at the intersection of statistical methodology and genomic data science, with a focus on developing rigorous and scalable methods for modern high-dimensional datasets. His research interests include high-dimensional statistics, covariance and precision matrix estimation, regression modeling with structured responses, variable selection, and integrative analysis of omics data. He develops methods tailored for compositional data, multivariate responses, and ancestry-specific genetic association studies, contributing to both theoretical statistics and public health applications. The recent publications and funded projects highlight a strong trend in developing objective, reliable, and heterogeneous-aware statistical frameworks for genomics and biomedicine. His work emphasizes methodological innovation with direct applicability to complex biological data, particularly in diverse populations and multi-omics integration. Awarded grants from the National Science Foundation and the National Institutes of Health demonstrate recognition of his research’s significance and impact. These include projects on inference from omics data, new regression models for categorical responses, and integrative genomics in African American populations. Objective and reliable methods for inference from modern omics data (NSF, 2024–2027) Collaborative Research: New Regression Models for Multiple Categorical Responses (NSF, 2024–2025) Integrative Genomics into Genetic Association Studies of Blood Pressure and Stroke in African Americans (NIH/Fred Hutchinson, 2023–2024) Dr. Molstad advises and collaborates on major genomic studies involving protein expression, blood pressure, stroke, and ancestry-specific effects. While specific PhD students are not listed, his role as Principal Investigator on multiple grants indicates mentorship of graduate researchers and postdoctoral scholars. He is also active in the broader statistical community, with publications in top-tier journals such as Biometrika , Biometrics , and Genome Biology .
Jennifer J. Blackhurst is an Adjunct Professor in the Department of Business Analytics at the Tippie College of Business, University of Iowa. She has held several key academic and administrative roles, including Professor in Business Analytics (2021–2025), Associate Dean for Graduate Professional Programs (2020–2025), and the Leonard A. Hadley Chair/Professor in Business Analytics (2019–2024). Her career reflects deep engagement in supply chain research, academic leadership, and editorial contributions to top journals. Her research focuses on supply chain risk and disruption management, supplier assessment and selection, supply chain coordination, and innovation. She explores how organizations can build resilience through strategic adaptation, network design, and behavioral competencies. Her work integrates complex systems theory, empirical analysis, and data-driven modeling to address real-world supply chain challenges. The recent publications highlight a strong trend in understanding supply chain resilience through network science, agent-based modeling, and systemic risk frameworks. Her research spans both technical and human dimensions, examining not only structural vulnerabilities but also organizational behaviors and knowledge-based competencies that influence risk mitigation. Key themes include disruption propagation, robustness measurement, and the dual role of innovation in both enhancing performance and potentially increasing vulnerability. Scientific Awards and Honors: Best Paper Award - Transportation Journal and APICS, 2018 Outstanding Associate Editor - Decision Sciences Journal, 2017 MBA Business Analytics Professor of the Year - Tippie College of Business, 2017 Outstanding Associate Editor - Decision Sciences Journal, 2013 Emerging Leaders Academy - Iowa State University, 2013 - 2014 Citations of Excellence Award - Emerald Management Reviews, 2011 Jennifer Blackhurst has played a significant role in academic service through editorial and review activities, serving as Senior Editor for the Journal of Business Logistics and on the editorial boards of several leading journals including IEEE Transactions on Engineering Management , Decision Sciences Journal , and Journal of Operations Management . While no formal advising or grant information is listed, her leadership roles and extensive publication record suggest active mentorship and research supervision. She is a member of the Council for Supply Chain Management Professionals and the Decision Sciences Institute, further demonstrating her national engagement in the field.
Matthias Mnich is a Professor and Head of the Institute for Algorithms and Complexity at Hamburg University of Technology (TUHH), within the School of Electrical Engineering, Computer Science and Mathematics. He also serves as Deputy Dean International, reflecting his leadership in academic administration and international collaboration. He is a principal investigator at the Helmholtz Graduate School for the Structure of Matter, further emphasizing his interdisciplinary impact. His research lies at the intersection of theoretical computer science and practical algorithm design, focusing on parameterized algorithms , approximation algorithms , combinatorial optimization , scheduling , and algorithmic game theory . His work often bridges theoretical guarantees with real-world applications in energy systems, quantum computing, and logistics. The recent publications (2023–2025) highlight his sustained excellence in top-tier venues such as FOCS, ICALP, ESA, STACS, and journals like Mathematical Programming and ACM Transactions on Algorithms . These works explore foundational problems in vector bin packing , integer programming , graph algorithms , and kernelization , while also applying algorithmic techniques to microgrid energy optimization and quantum algorithm engineering . He is deeply embedded in the theoretical computer science community, having served on program committees of major conferences including: STACS 2023 ESA 2024 FOCS 2023 ICALP 2024 IJCAI 2019–2025 AAAI 2018 SWAT 2018 He has successfully supervised several PhD students to completion, including Matthias Kaul , Roland Vincze , and Alexander Göke , many of whom have taken postdoctoral positions at institutions like the University of Bonn and University of Augsburg. His current research projects include PATTERN (2025–2031) , Hamburg Quantum Computing (2024–2029) , and Kernelization for Big Data , indicating long-term funding and strategic research directions. He leads the Institute for Algorithms and Complexity (E-11) , fostering a research environment focused on high-impact algorithmic research.
Agnieszka Jagoda is a Professor at the Department of Strategic Management and Logistics at the Wrocław University of Economics – Jelenia Góra Branch. Her research focuses on supply chain management, project teams, cross-organizational collaboration, sustainability, and digitalization in human resources. She supervises doctoral students and actively publishes in areas such as sustainable logistics, environmental behavior, and stakeholder analysis. Her work bridges theoretical frameworks with empirical studies, emphasizing practical implications for business and policy. Key research interests include last-mile delivery sustainability, environmental awareness comparisons across nations, and the integration of digital tools in HR management. Notable projects involve analyzing stakeholder perspectives in circular economy initiatives and examining human flows within supply chains. Her empirical studies often employ mixed-methods approaches, combining qualitative focus groups with quantitative analyses. Consultations are held via MS Teams during summer semesters, reflecting her engagement with modern communication tools. While no awards are explicitly listed, her prolific publication record indicates recognition in academic and practitioner circles.
Associate Professor Iain MacGill at the University of New South Wales leads interdisciplinary research at the intersection of renewable energy integration , electricity market design , and policy frameworks for low-carbon transitions. As a core member of the Centre for Energy and Environmental Markets , he develops computational models for coordinating distributed energy resources in restructured power systems. PhD in Electrical Engineering (UNSW) B.Eng. & M.Eng.Sci. (University of Melbourne) His work examines technical-economic-commercial challenges of renewable integration, with recent focus on: 24/7 zero-emission energy tracking frameworks Temporal matching in renewable procurement Open-source tools for green hydrogen value chains Residential solar-battery interaction dynamics Current research projects involve smart grid technologies , community microgrid economics , and climate-resilient energy systems . He collaborates with institutions like ARENA , CSIRO , and ARC on grants addressing grid stability, cost allocation, and policy innovation.
Dr. Kristin Knipfer is a Senior Research Fellow at the TUM School of Management and Executive Director of the TUM Institute for LifeLong Learning . Her research focuses on leadership as a catalyst for organizational learning and innovation, examining how leaders influence team dynamics in academic, entrepreneurial, and corporate settings. Leadership development in academia and business Organizational learning mechanisms Knowledge management systems Digital transformation in leadership education Her recent publications explore leader identity construal, narcissistic leadership impacts, and team reflection processes. She has received multiple awards including the TUM Digital Innovations in Management Education Award and the Richard A. Swanson Research Excellence Award nomination. She leads evidence-based leadership programs for academic leaders and has co-developed digital tools like the TUM Leadership Toolbox and EMMA digital leadership coach. Her work bridges theory and practice through collaborations with institutions like the Vienna University of Economics and Business.
Iraklis Lazakis is a Reader in Maritime Operations and Maintenance at the Department of Naval Architecture, Ocean and Marine Engineering (NAOME), within the Faculty of Engineering at the University of Strathclyde. He joined the university as a PhD researcher in 2007 and began his academic career in 2011, establishing himself as a key figure in maritime systems research and education. His research interests span a broad range of topics including ship operations, systems maintenance and reliability, condition monitoring, risk and asset management, shipyard productivity, and offshore renewable energy systems (wind, wave, and tidal). His work bridges academic theory with industrial application, drawing from his 8 years of prior industry experience in maritime surveys, accident investigations, and ship repairs. The trends in his recent publications reflect a strong focus on data-driven and digital solutions for sustainable maritime operations. Key themes include the development of simulation and optimization tools, application of virtual reality for safety, cost reduction in offshore wind O&M, and decarbonization strategies such as onboard CO2 capture. His work increasingly integrates AI, digital twins, and human factors to enhance system performance and crew wellbeing. He has received numerous accolades, including: SNAME Faculty Advisor of the Year (2024) SNAME WES Best Paper Award (2023) Multiple Knowledge Transfer Partnerships Certificates of Excellence (2020, 2022) Laureate of the Franz Edelman Award (2012) ISSC Committee IV.2 Membership (2012–2015) Lazakis actively supervises undergraduate, postgraduate, and PhD students, and leads or contributes to a wide portfolio of research and knowledge exchange projects. His recent projects include decarbonizing UK shipping, structural surveys of vessels like Calmac and the Royal Yacht Britannia, and development of low-cost underwater gliders. He plays a strategic role in supporting colleagues with funding applications, publications, and industry collaboration. His work contributes to UN Sustainable Development Goals related to sustainable energy and industry innovation.
Marc Hanheide is a Professor of Intelligent Robotics and Interactive Systems at the University of Lincoln 's School of Computer Science. With a career spanning EU projects like VAMPIRE, COGNIRON, CogX, and STRANDS, his work focuses on long-term robotic behavior, human-robot spatial interaction, and cognitive system architectures. He has secured over 12 major grants from organizations including EPSRC, BBSRC, and the European Commission. Key Research Areas : Autonomous robotics, HRI, AI, cognitive systems, agricultural robotics Current Projects : STRANDS (long-term behavior), AgriFoRwArdS (robotics training), NCNR (nuclear robotics) Major Contributions : Human-aware navigation modules, topology optimization for robot fleets, causal analysis frameworks Scientific Awards: While no specific awards are listed, his numerous EPSRC grants and leadership in multi-institutional projects highlight his impact. He has over 172 publications and collaborates with institutions like CoR-Lab and CITEC.
