Find Academic Supervisors

• Generalization in deep learning
• Sparse estimation
• Portfolio optimization using reinforcement learning
• +6 more

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.

• Quality Inspection and Control
• Predictive Modeling
• Smart Manufacturing Systems
• +3 more

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.

• Sustainable operations and circular supply chains
• Multi/Omni-channel distribution and supply chain network design
• Process optimization in manufacturing and service operations
• +3 more

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.

Ding Ze YangView profile

Lecturer

• Industrial AI
• Deep Learning
• Data-Driven Modeling
• +4 more

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.

Felix SchmidView profile

Professor

• Railway Engineering
• Transportation Systems
• Civil Engineering
• +3 more

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.

• Statistics
• High-Dimensional Data Analysis
• Statistical Genetics
• +7 more

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. BlackhurstView profile

Adjunct Professor

• Supply Chain Risk Management
• Supply Chain Disruption Management
• Supplier Assessment and Selection
• +6 more

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.

• Algorithms and Complexity
• Parameterized Algorithms
• Approximation Algorithms
• +7 more

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 JagodaView profile

Professor

• Supply Chain Management
• Project Teams
• Cross-organizational Management
• +5 more

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.

Iain MacgillView profile

Associate Professor

• Renewable Energy Integration
• Electricity Market Design
• Distributed Energy Systems
• +4 more

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.

Kristin KnipferView profile

Research Fellow

• Leadership Development
• Organizational Learning
• Team Dynamics
• +5 more

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.

• Robotics
• Human-Robot Interaction (HRI)
• Artificial Intelligence
• +3 more

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.

Christoph SchmidtView profile

Senior Lecturer

• Supply Chain Management
• Digital Technologies
• Blockchain
• +3 more

Christoph Schmidt is a Senior Lecturer in the Department of Management Information, Decisions & Operations at the University of Bath. His research focuses on the intersection of operations and information systems, particularly digital technology adoption in business and supply chains. Expertise in blockchain and additive manufacturing Contributions to UN Sustainable Development Goals (SDGs) Employs empirical methods with secondary and textual data Key research areas include supply chain risk management, data privacy, and digitalisation. His work often addresses humanitarian aid logistics and pandemic-related disruptions. Current research explores the physical-digital interface in blockchain applications and public reactions to supply chain glitches. Collaborations span multiple institutions and industries.

John GroutView profile

Professor

• Quality Management
• Mistake-Proofing
• Lean Manufacturing
• +5 more

John Grout is the David C. Garrett Jr. Professor of Business Administration and Chair of the Technology, Entrepreneurship, and Data Analytics Department at Berry College, within the Campbell School of Business. He previously served as dean of the school and returned to full-time faculty in 2016, continuing his leadership in academic innovation. His research focuses on quality management, particularly mistake-proofing (poka-yoke), lean manufacturing, and the impact of user innovation on supply chains. He has made significant contributions to healthcare process improvement, with publications guiding error reduction in clinical settings. The recent articles reflect a strong trend in applying operational excellence to healthcare systems, integrating concepts from manufacturing into medical process design. His work emphasizes designing systems that prevent errors through structural and procedural safeguards, supported by economic and behavioral models. Scientific Awards: Shingo Prize for Excellence in Manufacturing (2004) for 'The Human Side of Mistake-Proofing' John Grout has advised various organizational improvement initiatives and led the development of Berry College’s Creative Technologies program and the HackBerry Lab makerspace. His grants include work supported by the Agency for Healthcare Research and Quality (AHRQ), resulting in influential publications on healthcare process safety. He has also consulted widely with firms to improve operational reliability. He is actively involved in academic leadership, curriculum development, and cross-disciplinary innovation, particularly in integrating technology and entrepreneurship into undergraduate education.

Eren İnciView profile

Professor

• Urban Economics
• Transportation Economics
• Economics of Parking
• +3 more

Eren İnci is a Professor of Economics at the Faculty of Arts and Social Sciences, Sabanci University. His research focuses on Urban Economics and Transportation Economics , particularly the economics of parking, traffic congestion, and urban sustainability. He holds a PhD (2007), MA (2004), and BA in Management Engineering (2002) from Boston College and Istanbul Technical University. Education PhD (Economics), Boston College, 2007 MA (Economics), Boston College, 2004 BSc (Management Engineering), Istanbul Technical University, 2002 Research Interests center on urban transport systems, parking policies, retail leasing, and their environmental impacts. His work bridges economic theory with real-world policy challenges, including sustainable city planning and market design for shared resources. Scientific Awards include: TUBITAK Incentive Award (2018) Outstanding Young Scientist Award (TUBA-GEBIP) (2014) Young Scientist Award (BAGEP) (2014) Best Overall Paper Prize (International Transportation Economics Association) (2016) FASS Teaching Award (2011) Professional Roles include Vice Dean (2017–2024), Executive Committee Member of the International Transportation Economics Association (2016–present), and Research Member at the Smart Mobility and Logistics Lab (2018–present). He has held visiting positions at MIT, University of California, Riverside, and ZEW.