Multimodal Transit Operations Professors and Supervisors | ApplySharif

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Christian KirchesView profile

Professor

Technical University of BraunschweigGermany

Christian Kirches is a full professor at the Institute for Mathematical Optimization within the Carl-Friedrich-Gauß-Fakultät (Faculty of Mathematics, Technische Universität Braunschweig). His research focuses on nonlinear optimization , mixed-integer optimal control , and robust optimization for dynamic systems. He was awarded the Klaus-Tschira prize (2011) for public science communication and the Hengstberger prize (2014) for junior researchers, and received an ERC Consolidator Grant (2022) for his work on optimization under uncertainty. Alumni of Heidelberg University (Diploma, Doctorate, Habilitation) Former resident associate at Argonne National Laboratory and postdoctoral appointee at the University of Chicago Leader of a junior research group (2013–2017) at Heidelberg University His recent publications highlight advancements in mixed-integer nonlinear programming , real-time control systems , and optimization for sustainable energy and transportation . He collaborates with researchers on projects like wind farm control, hydrogen aviation networks, and chromatography process optimization. His methodological work on sum-up rounding , trust-region algorithms , and combinatorial integral approximation has been published in journals such as SIAM Journal on Optimization, Mathematical Programming, and IEEE Control Systems Letters. Kirches also serves as area coordinator for Optimization Online and was associate editor for OR Spectrum (2022–2024). Scientific Awards: Klaus-Tschira Prize (2011) Hengstberger Prize (2014) ERC Consolidator Grant (2022) He is an elected member of the COIN-OR initiative and contributes to open-source optimization software. His lab at TU Braunschweig develops algorithms for dynamic systems under uncertainty, with applications in energy management, autonomous traffic, and industrial processes.

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R. Bruce WallaceView profile

Adjunct Professor

Carleton UniversityCanada

R. Bruce Wallace is an Adjunct Professor at Carleton University's Faculty of Engineering and Design and an Adjunct Research Professor affiliated with Bruyère Health Research Institute. He serves as Executive Director of the AGEWELL National Innovation Hub (SAM3), focusing on sensors and analytics for aging in place. His expertise spans signal processing, data analytics, and healthcare technology. Dr. Wallace holds a Ph.D. from Carleton University, an M.Eng. from Carleton, and a B.E.Sc. from the University of Western Ontario, alongside a P.Eng. license and Senior Member status in IEEE. His research focuses on innovative smart home technologies to support aging populations, including sensor-based monitoring systems, cognitive health assessment, and assistive vehicle technologies. Key projects include the SAM3 initiative, which integrates multi-disciplinary teams to develop solutions for independent living. He co-authored the book *Supportive Smart Homes: Their Role in Aging in Place* and holds 24 patents in telecommunications and healthcare systems. Dr. Wallace’s work emphasizes collaboration with industry, clinical partners, and end-users to bridge technology development and real-world applications. His speaking engagements span academic, industry, and public audiences, advocating for age-friendly technology adoption. His research has been published in journals like IEEE Transactions on Instrumentation and Measurement, with a focus on sensor technologies, health monitoring, and driver safety for older adults. Current affiliations include leadership roles at SAM3, Bruyère Research, and Carleton’s ARISE Lab, where he oversees projects such as the SAM3 Smart Apartment and Virage Simulator. His contributions address ethical, legal, and policy challenges in smart home technologies, ensuring user-centered design and accessibility.

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Avinash UnnikrishnanView profile

Professor

University of Alabama at BirminghamUnited States

Avinash Unnikrishnan is a Professor and Chair in the Department of Civil, Construction, and Environmental Engineering at the University of Alabama at Birmingham (UAB). He holds a B.Tech. from the Indian Institute of Technology Madras, an M.S. from Vanderbilt University, and a Ph.D. from the University of Texas, all in civil engineering fields. His research focuses on optimizing urban mobility networks, resilient infrastructure systems, and the intersection of transportation with public health and pedagogy. He has contributed to studies on EV charging equity, disaster-related pathogen assessments, and drone-integrated logistics systems. Unnikrishnan's work spans transportation policy, infrastructure resilience under extreme events, and sustainable urban systems. His recent research includes analyses of post-pandemic shopping behavior in New Delhi, risk-based asset management for bridges, and the impact of truck platooning on bridge loading. He has also explored the implications of home deliveries during and post-COVID-19 lockdowns, emphasizing equity and environmental justice. He has advised several research projects funded by state and federal agencies, including studies on speed zoning methodologies, freight flow prediction using weigh-in-motion data, and motor carrier safety in Oregon. His expertise in interdisciplinary methods has led to innovations in transportation modeling, logistics optimization, and infrastructure durability assessment. Labs/Teams: While specific lab names aren’t mentioned, his research involves collaborations with state transportation departments (e.g., ODOT) and interdisciplinary teams focusing on urban systems, environmental health, and infrastructure resilience.

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Jason P. HuntView profile

Professor

University of UtahUnited States

Jason P. Hunt, MD, MS, FACS, serves as Professor and Chair of the Department of Otolaryngology-Head and Neck Surgery at the University of Utah, with adjunct appointments in Neurosurgery. He joined the institution in 2006 and has been instrumental in departmental development, including its transition to a standalone entity. His clinical base is at Huntsman Cancer Institute, where he holds leadership roles including Clinical Director of Head and Neck Surgical Oncology and Medical Director of Operating Rooms. Dr. Hunt specializes in surgical oncology, tumor reconstruction, and thyroid/parathyroid neoplasms. Education Dr. Hunt earned foundational training in polymer science (BS/MS, Georgia Tech) before pursuing medicine: MD: University of Alabama at Birmingham General Surgery Internship: Louisiana State University Otolaryngology Residency: Louisiana State University Fellowship: Head & Neck Oncologic Surgery/Microvascular Reconstruction, Vanderbilt University Research Focus His work spans surgical innovation, cancer biology, and clinical guideline development. Key areas include: Thyroid/parathyroid carcinoma pathophysiology and treatment optimization Microvascular reconstruction techniques for head/neck defects Radiation-induced tissue damage mechanisms Quality-of-life outcomes in cancer survivors Familial cancer patterns and genetic risk factors Publication Trends Dr. Hunt's recent articles (2018–2025) demonstrate a shift toward multidisciplinary approaches: earlier works focused on surgical techniques and genetic epidemiology, while recent publications emphasize guideline development (e.g., NCCN thyroid standards), precision oncology (mutation-based therapies), and pandemic-related survivorship challenges. This reflects integration of molecular biology, patient-centered outcomes, and population health perspectives. Awards & Honors Fellow, American College of Surgeons (FACS) Clinical & Academic Leadership He oversees the Head and Neck Cancers Disease Center and mentors surgical trainees. Institutional initiatives under his direction include: Expansion of theranostics programs Proton therapy center development Clinical trials in radioligand therapy

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Marin MarinovView profile

Lecturer

Aston UniversityUnited Kingdom

Marin Marinov is a Lecturer at the School of Engineering and Applied Science, Aston University (since 2019). Prior to this, he held roles as Senior Research Associate (2017–2019) and Research Associate (2009–2017) at Newcastle University's NewRail research centre, focusing on rail freight logistics and systems design. He holds a PhD in 'Analysis and Evaluation of Formation Yard Performances' from Newcastle University (2007). Research Interests: Urban Rail Systems, Freight Transport, Simulation Modeling, Rail Education, Sustainability Teaching: Simulation Modelling, Transport Logistics, Rail Freight, Systems Design, Queueing Theory Funding: Led the ASTONRail project (€450k EU Erasmus+ grant, 2020–2023), developing rail education standards across Europe. He coordinates RailUniNet (international rail academic network) and the ASTONRail strategic partnership, collaborating with institutions like SAPIENZA, KTH, and the International Union of Railways (UIC). His work emphasizes bridging rail education with industry needs, including AI integration and sustainable transport solutions. Awards: EU Erasmus+ grant for ASTONRail initiative. Editorial Roles: Sustainable Rail Transport (Springer), Urban Rail Transit (Springer).

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Irfan KhanView profile

Assistant Professor

Texas A&M University at GalvestonUnited States

Irfan Khan is an Assistant Professor at Texas A&M University's Department of Marine Engineering Technology, with a joint appointment in Electrical and Computer Engineering. His research focuses on cybersecurity for critical infrastructure, smart grid resiliency, and electric vehicle systems. He earned his Ph.D. (2018) and M.S. (2017) from Carnegie Mellon University, an M.S. in Electrical Power Engineering from the University of Greenwich (2011), and a B.S. from the University of Engineering & Technology Lahore (2009). He leads the Clean And Resilient Energy Systems (CARES) lab and has received awards including the William Paul Ricker Distinguished Faculty Award (2023) and Gulf Research Program Fellowship (2021). His publications address adversarial network defense, EV battery optimization, and renewable integration. William Paul Ricker Distinguished Faculty Award (2023) Data Science Career Initiation Fellow (2022) Gulf Research Program Fellowship (2021)

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Etu Egbe-etuView profile

Assistant Professor

San José State UniversityUnited States

Dr. Etu is an Assistant Professor of Business Analytics at San José State University (SJSU) , part of the Department of Marketing and Business Analytics within the Lucas College and Graduate School of Business . He holds a Ph.D. in Industrial Engineering (Wayne State University, 2021), an M.S. in Industrial Engineering (2018), and a B.Eng. in Civil Engineering from Covenant University, Nigeria (2016). His research focuses on developing use-inspired machine learning models to address challenges in healthcare, manufacturing, and transportation. Key areas include health informatics , customer feedback analytics , simulation modeling , and lean systems development . He has received the IEOM Annual Conference Best Paper Award (2020) for work in healthcare systems. Dr. Etu teaches courses such as Statistical Analysis (BUS2 194A), Data Visualization & Exploration (BUS2 195B), and Data Visualization & Management (BUS 235E). His research spans pandemic impacts on healthcare operations, Fintech adoption dynamics, and public transit usage patterns among older adults, leveraging predictive modeling and machine learning techniques.

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Austen LamacraftView profile

Professor

University of CambridgeUnited Kingdom

Prof Austen Lamacraft is a Professor at the University of Cambridge's Cavendish Laboratory, affiliated with the Theory of Condensed Matter group in the Department of Physics. His research focuses on quantum phase transitions, magnetism in atomic gases, ultracold atoms, and nonequilibrium phenomena in quantum systems. He has contributed to understanding dynamics of impurities in one-dimensional quantum liquids, integrable systems, and the interplay between magnetism and superfluidity. His work bridges theoretical physics with cold atom experiments, exploring topics like quantum hydrodynamics, spin-orbit coupled Bose gases, and quantum noise correlations. He has also developed methods for analyzing many-body quantum systems using reinforcement learning and machine learning techniques. Research interests include: quantum phase transitions, ultracold atomic physics, integrable systems, and non-equilibrium dynamics. His studies often involve exact analytical solutions and numerical methods to model complex quantum phenomena. Key contributions include theoretical predictions of dynamical magnetism in atomic gases, analysis of impurity motion in quantum fluids, and exploration of operator spreading in noisy spin systems. His recent work addresses quantum measurement-induced phase transitions and stochastic processes in dual-unitary circuits. Lamacraft has published extensively on quantum dynamics, entropy production, and interdisciplinary applications of statistical mechanics. He collaborates with experimental groups to guide cold atom experiments and has developed tools for multimodal data integration in physics research.

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Francesco CormanView profile

Associate Professor

ETH ZurichSwitzerland

Francesco Corman is an Associate Professor at the Department of Civil, Environmental and Geomatic Engineering at ETH Zürich, where he also serves as the Head of the Institute for Transport Planning and Systems (IVT). His academic career spans from his doctoral studies at Delft University of Technology to his current position at one of Europe's leading technical universities. He has established himself as a leading researcher in transport systems with a focus on railway operations and optimization. His educational background includes: Doctoral Degree (Ph.D.) from Delft University of Technology (2007-2010) Master's Degree in Management & Automation Engineering from Roma TRE University, Italy (2004-2006) Bachelor's Degree in Computer Science Engineering from Roma TRE University, Italy (2001-2004) Professor Corman's research focuses on analytics, optimization and control in transport systems, with particular emphasis on public transport, railway networks, and logistics systems. His work bridges the gap between theoretical optimization models and practical applications in real-world transportation networks. He has developed innovative approaches to railway traffic management, public transport operations, and freight logistics that address contemporary challenges in transportation systems. His recent publications demonstrate a strong trend toward data-driven approaches in transportation, with increasing integration of machine learning techniques, particularly deep learning and Bayesian networks, into traditional transportation optimization problems. There's also a growing emphasis on sustainability considerations in transportation systems, as evidenced by research on environmental impacts of railway infrastructure. His scientific contributions include: Development of advanced models for railway traffic management and optimization Innovative approaches to public transport disruption analysis and recovery Integration of on-board monitoring data for railway infrastructure management Probabilistic modeling of transportation operations under uncertainty Professor Corman leads several significant research projects including ESTRA (Efficient Safe Train Dynamics), LeRaBe (Learning railways for better schedules), NCCR (Dynamic stochastic learning of train dynamics as enabler to highly automated train operation), RaDiCa (Modeling the Impact of Digitalization on Railway Capacity), and UrbanEcho (Envisioning tomorrow - A digital twin technology for sustainable urban planning in data poor regions). He teaches multiple courses at ETH Zürich including Public Transport Design and Operations, Public Transport and Railways, Logistics and Freight Transportation, and contributes to doctoral seminars on Data Science and Machine Learning in Civil Engineering. His teaching reflects his research expertise, bridging theoretical concepts with practical applications in transportation systems.

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Simone Lamont-BlackView profile

Senior Lecturer

University of EdinburghUnited Kingdom

Dr Simone Lamont-Black is a Senior Lecturer in International Trade Law at the University of Edinburgh's School of Law, affiliated with the Edinburgh Centre for Commercial Law. She holds a Doctorate from Augsburg University (summa cum laude) and practiced law in Germany before moving to the UK in 2010. Her teaching focuses on international commercial law, including transport law, arbitration, and dispute resolution methods. She established the Edinburgh Willem Vis International Commercial Arbitration Moot Team and the Edinburgh Vis Pre-Moot, fostering legal advocacy skills. Her research interests span international transport law (carriage by sea, land, air, and multimodal systems), freight forwarding, and food supply chain regulation. Notable outputs include contributions to Gloag and Henderson: The Law of Scotland and co-authored works like Goods in Transit and Current Issues in Freight Forwarding . She has held visiting positions at institutions such as the National University of Singapore and Murdoch University. Her work emphasizes legal harmonization in transport and food supply chains, with recent articles addressing CMR regulations, freight forwarder liability, and post-Brexit passenger rights. She is a Senior Fellow of the Higher Education Academy and an Academic Fellow at the Centre for Maritime Law (NUS).

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Magnus WiktorssonView profile

Professor

KTH Royal Institute of TechnologySweden

Magnus Wiktorsson is a Professor at KTH Royal Institute of Technology's Department of Sustainable Production Development within the Digital Futures Faculty. His work focuses on smart production logistics, sustainability, and digital transformation in manufacturing systems. He explores applications of machine learning, IoT, blockchain, and digital twins to enhance supply chain visibility, optimize production processes, and achieve circular economy goals. His research integrates technical and socio-technical perspectives, addressing challenges in human-robot collaboration, data-driven decision-making, and Industry 4.0/5.0 transitions. Key themes include material efficiency, real-time data utilization, and participatory modeling in urban and industrial logistics. Recent work emphasizes frameworks for adaptive scheduling, explainable AI in logistics, and blockchain-based collaboration models. Wiktorsson collaborates with industry partners to validate frameworks through case studies, pilot projects, and simulation-based methodologies. His contributions span academic publications and contributions to strategic innovation programs like Produktion2030, focusing on sustainability and resilience in manufacturing systems.

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Juan Rivera-LetelierView profile

Professor

University of RochesterUnited States

Juan Rivera-Letelier is a Professor of Mathematics at the University of Rochester's School of Arts & Sciences. He holds a Doctorat en Mathématiques Pures (equivalent to a PhD) from Université de Paris Sud, obtained in 2000. His research focuses on dynamical systems, number theory, and ergodic theory, with particular emphasis on non-Archimedean dynamics, statistical properties of maps, and applications to arithmetic geometry. He has authored numerous influential papers on topics such as Fatou components, Gibbs states, and p-adic distributions of algebraic points. His recent work explores phase transitions in intermittent maps, sensitive dependence in geometric Gibbs states, and equidistribution of CM points in toric varieties. He has contributed to foundational results in ultrametric dynamics, including studies on wildly ramified power series and residue fixed point indices. Rivera-Letelier’s research bridges complex dynamics, real analysis, and number theory, often employing techniques from thermodynamic formalism and non-uniform hyperbolicity. His work has implications for understanding the interplay between arithmetic structures and dynamical systems, with applications to Diophantine geometry and statistical mechanics.

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Pascal Van HentenryckView profile

Adjunct Professor

Georgia Institute of TechnologyUnited States

Pascal Van Hentenryck is an Adjunct Professor at the School of Computational Science and Engineering, Georgia Institute of Technology. His research focuses on integrating optimization techniques with artificial intelligence, particularly in power systems, transportation networks, and constraint programming. He leads projects on trustworthy optimization learning, grid reliability, and AI-driven solutions for public transit systems like MARTA REACH in Atlanta. Key areas include optimal power flow, machine learning proxies for large-scale optimization, and stochastic decision-making in renewable energy systems. Van Hentenryck's work spans academic and industrial collaborations, including the ARPA-E Grid Optimization Competition and the design of on-demand multimodal transit systems. He emphasizes practical applications of optimization algorithms in real-world scenarios such as supply chain management, rider behavior modeling, and fair policy design. His contributions to constraint programming education and MOOC development highlight his commitment to advancing computational methods in academia. Recent projects include developing frameworks for privacy-preserving convex optimization and analyzing the impact of equity considerations on adversarial vulnerability in AI systems. He explores topics like neural network verification, battery storage integration in grids, and scalable solutions for large-scale scheduling problems using column generation and reinforcement learning.

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Yu LiuView profile

Researcher

Aalto UniversityFinland

Yu Liu is a Doctoral Researcher at Aalto University's Department of Mathematics and Systems Analysis, within the School of Science. Their research focuses on Optimization, Transportation Systems, and Operations Research, with contributions to interdisciplinary fields like Quantum Optomechanics and Gravitational Physics. They are affiliated with the Operations Research and Systems Analysis group, and their work bridges mathematical modeling with engineering and physical sciences. Research interests include developing optimization algorithms for complex systems, analyzing traffic flow dynamics, and advancing quantum technologies through optomechanical systems. Recent studies explore adaptive sampling methods for surrogate models and lane-changing strategies for congestion mitigation in mixed traffic environments. Publications highlight trends in both applied and theoretical domains: from practical transportation solutions to fundamental quantum phenomena like gravitational entanglement and noise-canceling microwave systems. Their work emphasizes cross-disciplinary approaches, combining computational methods with experimental physics. No awards or grants are explicitly mentioned in the provided information. Yu Liu's advising record is not listed, though their role as a doctoral researcher suggests active engagement in academic research teams. They contribute to Aalto University's efforts in systems analysis and quantum technology through collaborations in the mentioned research groups.

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Yu JiangView profile

Associate Professor

Technical University of DenmarkDenmark

Yu Jiang is an Associate Professor in the Department of Transportation Systems Modelling at the Technical University of Denmark (DTU), within the Department of Technology, Management and Economics. He is actively engaged in research and supervision, with a strong focus on transportation science and systems optimization. He is accepting PhD students and maintains an active research profile with numerous ongoing projects and publications. Education: PhD, The University of Hong Kong (2010–2014) His research interests include static and dynamic transit/traffic assignment, network design, infrastructure resilience and vulnerability, multi-objective optimization, and metaheuristics. These areas are central to improving urban mobility, public transport efficiency, and sustainable transportation systems. His work contributes to UN Sustainable Development Goals related to sustainable cities and responsible consumption. Recent publications (2025) reflect a strong trend in applying advanced optimization and machine learning techniques to urban transportation challenges, including traffic signal control, last-mile delivery, intermodal travel behaviour, and demand prediction across shared mobility systems. The research spans both theoretical modelling and practical case studies. Scientific Awards: No scientific awards listed in the provided text. Advising and Grants: Yu Jiang is the main supervisor for several PhD projects, including 'Development of an integrated optimisation model for operating urban transit system (SmoothTrip)', 'Crowdsourced Delivery as an Activity for Sustainable Cities', and 'Network Optimisation for Connected, Cooperative and Automated Mobility'. He is also a co-investigator in the NEMESYS project funded by the European Commission, focusing on dynamic pricing and tradable credits for emissions management. His academic activities include organizing conferences, presenting at international events, serving as a journal editor, and conducting peer reviews. Labs and Research Teams: He is part of the research network at DTU's Department of Technology, Management and Economics, collaborating on projects related to urban transit optimization, shared mobility, and sustainable freight. His work involves close collaboration with researchers from institutions such as Oxford University, NUS, and HKU, as well as international partners in ongoing research initiatives.

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