Find Academic Supervisors

Nicholas VlachopoulosView profile

Professor

• Geotechnical Engineering
• Geomechanics
• Environmental Engineering
• +5 more

Nicholas Vlachopoulos is a Professor of Civil Engineering at the Royal Military College of Canada (RMC) with cross-appointments at Queen's University's Department of Geological Science and Geological Engineering and School of Environmental Studies. He holds a PhD (2009) from Queen's University and B/A.Sc/M.A.Sc degrees from RMC. His research focuses on geotechnical engineering, geomechanics, and environmental engineering, emphasizing physical testing, field observations, and analytical techniques to advance engineering practices. Key roles include Research Director of the GeoEngineering Centre, CEO of Geologos Inc., and Director of RMC's Green Team addressing environmental challenges in military facilities. Education: PhD in Geological/Geotechnical Engineering - Queen's University (2009) M.A.Sc in Civil Engineering - Royal Military College (1995) B.A.Sc in Civil Engineering - Royal Military College Research Interests: Geotechnical Engineering (rock mechanics, tunneling) Environmental remediation in defense facilities Structural health monitoring using fiber optics Rock bolt and ground support systems Military infrastructure resilience Professional Contributions: Founder of Geologos Inc., specializing in geotechnical solutions Recipient of DND Innovation Award for environmental solutions Teaching excellence awards (2018) Supervised award-winning graduate students (2017-2021) Lab/Team Leadership: RMC Green Team: Environmental engineering solutions for Canadian Forces bases GeoEngineering Centre: Interdisciplinary geotechnical research

• Resource Recovery
• Wastewater Treatment
• Microbial Ecology
• +3 more

Merve Atasoy is an External Researcher at Wageningen University & Research, holding a PhD from the Royal Institute of Technology (KTH), awarded in September 2020. Her research focuses on microbial-driven solutions for sustainable resource recovery, wastewater treatment, and circular economy transitions. She specializes in optimizing bioreactors for volatile fatty acid production and studying microbial responses to extreme conditions like low pH environments. Education: PhD in Environmental Biotechnology from Royal Institute of Technology (2017–2021). Awarded on 10 September 2020. Research Interests: Her work integrates microbial community dynamics, bioprocess engineering, and eco-friendly waste valorization strategies. Key areas include enhancing wastewater treatment efficiency, developing nature-based solutions for cities, and leveraging microbial consortia for targeted biochemical production. She explores both fundamental mechanisms (e.g., acid stress responses) and applied technologies (e.g., reactor design). Publications Trends: Recent work emphasizes low-pH microbial systems, circular economy frameworks, and SARS-CoV-2 wastewater surveillance. She has contributed to understanding microbial acid tolerance, optimizing anaerobic bioreactors, and designing sustainable wastewater resource recovery facilities. Collaborations: Active in international networks like the COST Action on acid-impacted microbiology and interdisciplinary teams addressing planetary health through microbial innovation.

William EiseleView profile

Researcher

• Transportation Planning
• Access Management
• Urban Development Impacts
• +4 more

William (Bill) Eisele serves as a Senior Research Engineer and Program Manager at Texas A&M University's Department of Landscape Architecture & Urban Planning. His work focuses on transportation systems, freight mobility, and urban development impacts. Eisele holds a Ph.D. (Civil Engineering, Texas A&M, 2001), M.S. (Civil Engineering, Michigan State, 1994), and B.S. (Civil Engineering, Michigan State, 1993). Research Interests: Dr. Eisele’s expertise spans Transportation planning and access management, Freight mobility optimization, Congestion monitoring, Transportation system performance measurement, Urban land development impacts, Sustainable infrastructure design. Recent Work Trends: His publications emphasize data-driven solutions for freight challenges, including truck parking behavior, cargo consolidation, and port fluidity. Recent studies apply machine learning to predict driver route choices and evaluate real-time mobility tools. He also explores historical trends in urban freight logistics to guide future innovations. Grants & Advising: While no specific grants or advisees are listed, his extensive publications reflect collaborative work with institutions like the Texas A&M Transportation Institute. He has contributed to statewide programs like Oregon’s operations performance measures and Maryland’s freight fluidity initiatives. Labs/Teams: His affiliations suggest involvement with interdisciplinary teams focusing on transportation systems, though specific lab names are not mentioned in the source text.

• Transportation and Logistics
• Supply Chain Management
• Operations Research
• +7 more

Prof. Keng Hock, Mark Goh is a Professor at the National University of Singapore (NUS) Business School, holding a joint appointment as Director (Industry Research) at The Logistics Institute-Asia Pacific (TLI-AP). He specializes in logistics, supply chain strategy, and operations research. He earned his PhD from the University of Adelaide on a fully funded scholarship and has held adjunct and visiting roles globally. His research focuses on supply chain risk management, healthcare logistics, and strategic decision-making, with over 400 publications in top journals. Notable contributions include work on multi-criteria supplier selection, supply chain resilience, and AI ethics in e-commerce. He has received the Supply Chain Educator Award and is recognized in global directories like *Who’s Who in Asia and the Pacific Nations*. Prof. Goh advises public and private sector organizations on logistics strategy and sits on industry committees such as the World Economic Forum’s Global Advisory Council on Logistics. His current projects emphasize syncretic value-driven logistics models and sustainable recycling frameworks. He leads collaborative research teams addressing global supply chain challenges through interdisciplinary approaches. His articles reflect cutting-edge advancements in AI-driven decision models, risk networks in construction, and data ownership strategies in digital platforms. These contributions underscore his role as a thought leader in logistics and operations research, blending academic rigor with real-world industry applications.

• Artificial Intelligence
• Uncertainty Theory
• Belief Functions
• +7 more

Professor Fabio Cuzzolin is a Professor of Artificial Intelligence at Oxford Brookes University, leading the Visual Artificial Intelligence Laboratory (VAIL). He holds roles in the Institute of Ethical AI and the Healthy Ageing and Care (HAC) network. His research focuses on uncertainty theory, belief functions, and their applications in AI, surgical robotics, healthcare, and autonomous driving. He has secured over £5.4M in external funding, including the H2020 Epistemic AI project. Education and Academic Background: While specific formal education details are not explicitly stated in the text, Professor Cuzzolin holds a PhD and has held academic positions across institutions in Italy, the US, and the UK. His teaching experience spans three countries, including roles as a Module Leader for undergraduate and postgraduate courses in Computer Vision, Machine Learning, and related fields. Research Interests: Professor Cuzzolin is a global leader in uncertainty theory, belief functions, and geometric approaches to probability. His work bridges AI with healthcare, robotics, and autonomous systems. Recent projects include the SARAS surgical robotics project, Epistemic AI, and continual learning frameworks. His lab, VAIL, is a leading group in action detection and neurosymbolic AI. Awards and Recognition: Awards include the IMechE Formula Student AI competitions (2021, 2020), W&B Best Library Award (2021), and the Next 10 Award (2012). His students and collaborators have also achieved notable recognitions, such as BMVC Best Reviewer Awards and dataset development accolades. Grants and Funding: Key funded projects include the H2020 Epistemic AI (£966k), SARAS (£4.3M), and the AIDA incubator (£1.25M). Current lab funding exceeds £3.2M, supporting nine active projects across Horizon 2020, Innovate UK, and industry partnerships. Labs and Collaborations: VAIL collaborates with top institutions (Oxford, Cambridge, Imperial College) and companies (Samsung, Huawei). Projects span autonomous driving datasets (ROAD), surgical AI, and continual learning libraries (Avalanche).

Menoka BalView profile

Teaching Professor

• Project Management
• Sustainability
• Construction Management
• +5 more

Menoka Bal is a Teaching Fellow in the Department of Operations and Service Management at Aston Business School, part of the College of Business and Social Sciences at Aston University. Previously, she held roles including Assistant Professor, Lecturer in Engineering Management at Coventry University, and a PhD researcher at Liverpool John Moores University. Her academic qualifications include a BSc in Mechanical Engineering, an MSc in Engineering Management, and a PhD in Project Management. Her research focuses on sustainable development through integrative project management approaches, particularly in construction and IT sectors. Key interests include stakeholder engagement, risk mitigation, AI applications in project management, and lean management methodologies. She has published extensively on topics like project success measurement, waste management in construction, and leadership styles in manufacturing. Notable achievements include the Best Paper Award at the 2020 BAM Conference. Bal’s work emphasizes practical solutions for improving project performance through sustainable practices and technology integration. She has collaborated on projects addressing waste management in Lebanon’s construction sector and stakeholder dynamics in urban development. External Roles: External Examiner at the University of Bolton and Blackpool and Flyde College. Professional Certifications: PRINCE2 Practitioner, AgilePM Practitioner, Senior Fellow of the Higher Education Academy. Her publications span journals like Sustainability and conferences such as the British Academy of Management, showcasing a focus on bridging theoretical research with real-world project challenges.

Erdinç AltuğView profile

Professor

• Unmanned Aerial Vehicles (UAVs)
• Quadcopter Design
• Flight Control Systems
• +5 more

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 ShokriView profile

Professor

• Digital Supply Chain
• Operational Excellence (OPEX)
• Lean Six Sigma
• +3 more

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'.

• 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.