Find Academic Supervisors

• Traffic Flow Theories
• Transportation Network Modeling
• On-demand Mobility
• +5 more

Hilmi Berk Çelikoğlu is a full Professor specializing in Traffic Flow Theories and Transportation Network Modeling at Istanbul Technical University (ITU) Department of Civil Engineering. He has served as the head of the ITU ITS Research Lab since 2014 and previously held a Visiting Professor position at PennState Department of Computer Science & Maths between 2014-2015. His educational background includes B.Sc. (2000), M.Sc. (2002), and Ph.D. (2006) degrees, all from Istanbul Technical University in Transportation Engineering. Professor Çelikoğlu's research spans multiple critical areas in modern transportation systems. His primary focus includes Traffic Flow Theories and Transportation Network Modeling, with significant contributions to on-demand mobility systems and sustainable urban transportation solutions. He has pioneered work in dynamic network management, traffic flow control and simulation, and Intelligent Transportation Systems (ITS). His recent research has increasingly focused on the integration of electric vehicles into transportation networks, cooperative adaptive cruise control systems, and environmentally conscious transportation planning. His work bridges theoretical modeling with practical applications, particularly in the context of Istanbul's complex urban transportation challenges. His recent publications demonstrate a strong trend toward addressing contemporary transportation challenges, particularly the integration of emerging technologies like connected and autonomous vehicles into existing infrastructure. A significant portion of his work focuses on optimizing traffic flow in mixed environments containing both traditional human-driven vehicles and newer cooperative adaptive cruise control systems. His research also shows increasing emphasis on sustainability, with multiple studies examining emissions reduction, electric vehicle routing, and environmentally conscious transportation network design. Professor Çelikoğlu has received notable recognition for his work, including: Project Performance Award from TUBITAK (2018) Throughout his career, Professor Çelikoğlu has secured substantial research funding from prestigious organizations including TUBITAK, EU COST, and EU Horizon programs. His current research portfolio includes multiple active projects focusing on demand-based mobility systems, integrated mobility services, cooperative vehicle dynamics, and environmentally sensitive transportation network optimization. He has mentored numerous students and researchers through his leadership of the ITU ITS Research Lab, fostering the next generation of transportation engineers and researchers. Professor Çelikoğlu leads the ITU ITS Research Lab, which serves as a hub for cutting-edge transportation research. The lab focuses on applying advanced computational methods to solve complex transportation challenges, with particular expertise in traffic simulation, network modeling, and intelligent transportation systems. Under his leadership, the lab has become a center for innovation in transportation engineering, collaborating with both national and international partners to address pressing urban mobility issues.

Pasi LassilaView profile

Lecturer

• Performance Analysis
• Wireless Networks
• Queueing Theory
• +3 more

Pasi Lassila is a University Lecturer in the Department of Information and Communications Engineering. His expertise spans performance analysis, wireless networks, queueing theory, and energy-efficient systems. He holds a Doctoral degree (2001), Licentiate (1999), and Master's degree (1994) in Engineering and Technology from Helsinki University of Technology. His research focuses on optimizing energy and performance in wireless and server systems, with contributions to opportunistic scheduling, load balancing, and 5G HetNets. He has led the METRICS project (2013–2017) on internet communications science. Lassila has supervised three theses and contributed to over 90 publications, emphasizing energy-aware systems and network resource management. Key research areas include scheduling algorithms for wireless systems, energy-efficient server clusters, and dynamic load balancing. His work addresses challenges in heterogeneous networks, device-to-device communication, and autonomous control for reliable internet services.

Claudio RoncoliView profile

Visiting Professor

• Transportation Engineering
• Traffic Control Systems
• Urban Planning
• +3 more

Claudio Roncoli is a Visiting Professor in the Department of Built Environment at Aalto University, specializing in Transportation Engineering and Traffic Control Systems. His research focuses on urban mobility optimization, traffic simulation, and sustainable transportation solutions. He holds a Doctoral degree from Università degli Studi di Genova (2013). **Education**: PhD in Other (2013), Università degli Studi di Genova. **Research Interests**: His work addresses challenges in traffic management, emission reduction, and smart urban systems. Key areas include dynamic traffic modeling, autonomous vehicle integration, and data-driven policy design aligned with UN Sustainable Development Goals. **Projects**: Leads major initiatives like the ACUMEN Horizon (AI-driven traffic management) and SMARTEDGE (low-code programming for edge intelligence). These projects aim to enhance urban mobility efficiency, safety, and sustainability through advanced technologies. **Awards**: Recipient of the Best Paper Award (2023) at an international conference. **Grants & Activities**: Principal investigator on EU-funded projects (e.g., Horizon Europe). Engages in conferences, workshops, and media outreach, including public talks on 'What's modeling got to do with planning?' (2023) and media features in outlets like Environmental Research Letters . **Collaborations**: Active in international networks, contributing to interdisciplinary studies on emissions, vehicle trajectory reconstruction, and urban data analysis. Supervised 5 theses, advancing next-gen transport solutions.

Sabid RahmanView profile

Lecturer

• Artificial Intelligence for Business
• Business Analytics
• AI Policy and Governance
• +1 more

Sabid Rahman is a Lecturer teaching business analytics and AI applications at UC Davis. As a Principal Member of Technical Staff at a Fortune 50 company, he leads AI and machine learning initiatives for business automation and innovation. His research bridges computer science and business, focusing on AI monetization strategies, ethical AI governance, and generative AI applications. Rahman has 13+ years' experience developing production-scale AI systems, with publications in optical networking, quantum security, and network automation. He holds a PhD in Computer Science from UC Davis and an MS from University of Texas San Antonio. His industry-academia hybrid perspective informs teaching in AI policy, technology management, and business analytics.

• Distributed Systems
• Mobile Networking
• Transportation Engineering
• +5 more

Angelo Furno is an Associate Professor and Researcher at the LICIT Laboratory of Université Gustave Eiffel-ENTPE in Lyon, France. He holds a PhD in Computer Engineering from the University of Sannio, Italy. His academic roles include teaching courses on Intelligent Transportation Systems, Data Science, and Big Data at ENTPE. He is affiliated with INRIA’s AGORA team and the CITI-Lab at INSA Lyon. His research focuses on urban mobility analysis, transportation networks, mobile networking, and P2P systems. Key interests include leveraging multi-source traffic data for smart city planning, resilience engineering, and graph-based algorithms. Education: PhD in Computer Engineering (2014), University of Sannio, Italy MSc in Computer Engineering, University of Sannio, Italy Research Interests: Distributed systems, mobile data analytics, social network analysis, transportation engineering, and software engineering. Recent work emphasizes mobility pattern recognition, traffic demand estimation, and urban resilience strategies. Publications: Over 80 peer-reviewed articles in journals like Transportation Research Part C and conferences such as TRB. Recent trends focus on stochastic optimization for transport networks and deep learning for traffic prediction. Awards: Best Paper Award at IEEE Conference on Parallel, Distributed and Network-Based Processing (2013). Grants & Collaborations: Led projects like MyOpenGov and contributed to ANR ABCD. Collaborates with INRIA, INSA Lyon, and industry partners on urban mobility and data-driven solutions. Labs/Teams: LICIT Lab (transportation systems), INRIA AGORA (mobile networking), and CITI-Lab (communication networks).

Fabien LEURENTView profile

Professor

• Transport Systems Modeling
• Urban Development
• Environmental Economics
• +4 more

Fabien Leurent is a Professor and Research Director at the International Center for Research on Environment and Development (CIRED), with an HDR in Operational Research from Université Paris-Dauphine (2006). He leads the ENPC-IDFM Chair on Territorial Mobility and has directed over 20 PhD theses. His research focuses on systemic modeling of transport networks, urban mobility systems, and sustainable infrastructure. Key areas include transport demand modeling, shared mobility economics, and data-driven analysis using trajectory and smartcard data. Education: HDR in Operational Research (2006), Université Paris-Dauphine. Extensive involvement in collaborative projects with Renault, RATP, SNCF, and the French Ministry of Transport. His work bridges academic research and policy, emphasizing techno-economic analysis and environmental impact assessments. Research interests span urban transport networks, parking system modeling, and sustainable mobility policies. Notable contributions include the DREAM urban equilibrium model and studies on electric vehicle deployment. His recent work explores shared mobility services, autonomous vehicles, and the integration of digital tools in mobility systems. Awards and recognitions: While no specific awards listed, his leadership in CIRED and ENPC-IDFM underscores academic and professional acclaim. Over 100 publications, including books on eco-design of infrastructure and transportation systems.

• Flow-Aware Networking
• Optical Networks
• Network Resilience
• +5 more

Andrzej Jajszczyk is a prominent researcher in telecommunications and computer networks, with extensive contributions spanning Flow-Aware Networking, optical networks, resilience mechanisms, and Quality of Service (QoS) architectures. His work frequently appears in IEEE publications and conference proceedings, reflecting his active role in advancing network technologies. Research Focus: Jajszczyk's primary interests include congestion control algorithms, network reliability frameworks, and traffic management in Flow-Aware Networks. Recent work explores nanocommunications (FRET-based signaling) and energy-efficient cloud-fog interplay. His research consistently addresses both theoretical models and practical implementations in optical and software-defined networks. Publication Trends: Analysis of his 15 most recent articles reveals strong emphasis on: (1) Optimization of optical routing and spectrum allocation, (2) Nanoscale communication systems for biomedical applications, (3) Congestion mitigation in flow-oriented architectures, and (4) Energy-aware network resource provisioning. The work demonstrates consistent innovation in network resilience and QoS frameworks since the early 2000s. Awards & Recognition: No specific scientific awards or fellowships are documented in the provided text. Academic Leadership: Jajszczyk has edited IEEE Communications Magazine features and co-authored comprehensive books like Guide to Flow-Aware Networking . While student advisees aren't listed, his frequent collaborations (e.g., with Domżał, Wójcik) suggest mentorship roles.

• Unmanned Aerial Vehicles
• Field Programmable Gate Arrays
• Computational Fluid Dynamics
• +3 more

Dr. Ramadan Janissary is an Assistant Professor at Istanbul Technical University's Department of Aeronautical Engineering, specializing in Unmanned Aerial Vehicles (UAVs) and Field Programmable Gate Array (FPGA) technologies. His research spans computational fluid dynamics, hardware acceleration, and multi-sensor tracking systems. Recent research trends focus on FPGA-based solutions for aerospace applications, including 6-DoF dynamical models, quaternion-Euler angle conversion, and formation flight systems for UAVs. His work addresses technical challenges in ad-hoc networks, time delay management, and nonlinear dynamics. Scientific awards include the BOEING Academic Study Incentive Award (2017) and Best Doctoral Theses Award (2015). Current projects involve UAV recording systems, FPGA-based accelerators, and aviation CNS technology development.

• Transportation Engineering
• Civil Engineering
• Disaster Prevention
• +3 more

Professor Motohiro Fujita is affiliated with Nagoya Institute of Technology, where he contributes to the Department of Civil Engineering and Department of Environmental and Urban Engineering. Holding a Doctor of Engineering from Nagoya Institute of Technology, his work bridges transportation engineering, urban planning, and disaster prevention. Doctor of Engineering (Nagoya Institute of Technology, 1990) Master of Engineering (Nagoya Institute of Technology, 1985) His research focuses on transportation demand forecasting, traffic congestion analysis, and engineering education integration. Notable projects include: Developing time-of-day Origin-Destination (OD) estimation models using traffic counts Studying congestion definition based on driver consciousness Advancing marketing-oriented approaches in engineering education Recent publications analyze urban freeway dynamics, traffic signal behavior, and residential environment planning. He has presented at major conferences like the European Transport Conference and Japan Society of Civil Engineers meetings. Award of the Japan Society of Civil Engineers (1999) Active in professional bodies, he serves on committees for Nagoya Expressway Public Corporation, Nagoya City Environmental Impact Assessment Board, and academic societies like the Japan Society of Civil Engineers.

Michel MorvanView profile

Researcher

• Optical Communication
• Telecommunications
• Machine Learning in Signal Processing
• +3 more

Michel Morvan is a Researcher at the Optical Department of IMT Atlantique (Brest campus). His work focuses on advanced optical communication systems, network design, and machine learning applications for signal processing in photonics. Research Interests: Elastic optical networks, wavelength division multiplexing (WDM), fiber nonlinearity compensation, machine learning for telecommunications, energy-efficient data center interconnects, and microwave photonic filters. Key Contributions: Developments in multi-core fiber amplifiers, spectrum aggregation for heterogeneous traffic, and latency reduction in optical packet switching. Emerging Trends: Recent publications address real-time resource allocation in flexgrid networks, polarization-insensitive optical filtering, and economic impacts of advanced optical technologies.

• Transportation Engineering
• Route Choice Modeling
• Stochastic User Equilibrium
• +3 more

Lawrence Duncan is a Postdoctoral Fellow at the Technical University of Denmark (DTU), affiliated with the Department of Technology, Management and Economics . Within the Division of Transport, Section for Transport Systems Modelling, he focuses on advanced transportation modeling and network analysis. Role: Postdoctoral Fellow Institution: Technical University of Denmark Department: Department of Technology, Management and Economics Research Section: Transport Systems Modelling His research centers on route choice modeling and stochastic user equilibrium in transportation networks. Key contributions include addressing heteroscedasticity , route overlap , and unrealistic route exclusion in large-scale systems. Recent work explores dynamic multi-region MFD models and disjunctive decision rules for improved traffic assignment. Lawrence’s publications emphasize methodological rigor in transportation network modeling , with a focus on bounded path size models and GPS data integration . His work combines utility maximization with behavioral decision rules to enhance predictive accuracy in complex traffic systems. Contact: lawdun@dtu.dk | ORCID: 0000-0001-9162-4334

Viet PhamView profile

Assistant Professor

• Corporate Culture
• Diversity
• Public Policy
• +7 more

Viet Pham is an Assistant Professor of Accounting at the Sigmund Weis School of Business, Susquehanna University . He earned his Ph.D. in Accounting from the University of Texas at San Antonio , alongside an MAcc and BSBA in Accounting and Finance from the University of Arkansas at Fayetteville . Prior to Susquehanna, he served as an Assistant Professor at Wright State University. Ph.D., University of Texas at San Antonio MAcc, University of Arkansas BSBA, University of Arkansas Pham’s research focuses on corporate culture , diversity , public policy , and audit quality , with publications in top-tier journals like Journal of Corporate Finance and Journal of Business Ethics . His work examines how organizational ethics influence debt contracting , financial reporting , and auditing practices , including gender dynamics in audit partner outcomes and pandemic-era disclosure patterns. Recent publications highlight trends in corporate corruption analysis (2021-2025), gender effects in financial leadership (2018-2025), and pandemic disclosure strategies (2022-2025). His work spans both empirical and theoretical approaches to auditing and financial reporting. Scientific Awards & Funding Wright State University Online Teaching and Learning Community Fellow (2021) AAA/Deloitte/J. Michael Cook Doctoral Consortium Fellow (2019) UTSA College of Business Ph.D. Fellowship (2017-2020) UTSA College of Business Ph.D. Excellence Fund (2018) Rawls College Graduate Scholarship (2016)

Michael KuhlView profile

Professor

• Simulation
• Operations Research
• Healthcare Systems
• +4 more

Michael Kuhl is a Professor in the Department of Industrial and Systems Engineering at Rochester Institute of Technology's Kate Gleason College of Engineering. His research focuses on simulation methodologies applied to autonomous mobile robots, healthcare systems, and logistics optimization. With appointments spanning teaching, research, and industry collaboration, he directs multiple projects in smart warehouse systems and stochastic input modeling. His educational background includes a Ph.D. and M.S. in Industrial Engineering from North Carolina State University and a B.S. in Industrial Engineering from Bradley University. His research interests center on simulation , operations research , and optimization with applications across healthcare, manufacturing, and logistics domains. Analysis of his recent publications reveals strong trends in autonomous material handling systems (62% of recent works), simulation optimization (28%), and educational pedagogy (10%). His work increasingly integrates machine learning with traditional simulation methods, particularly in indoor localization and warehouse robotics. Healthcare applications remain a consistent thread throughout his career, evolving from hospital supply chain modeling to modern surgical suite optimization. His academic leadership includes directing the REVS K-12 STEM outreach program and developing simulation-based educational modules for assembly systems engineering. Current teaching responsibilities include Systems Simulation (ISEE-510), Simulation Analysis (ISEE-708), and Engineering Value Creation (ISEE-773). Recent industry collaborations include partnerships with Simcona on smart warehouse field experiments, as highlighted in March 2022 Rochester Beacon coverage. His laboratory work focuses on developing intelligent materials handling systems where autonomous robots negotiate right-of-way in warehouse environments using advanced path planning algorithms.

• Optical Networks
• Optical Communication
• Broadband Networks
• +5 more

Josep Solé-Pareta is a Professor in the Department of Computer Architecture at the Polytechnic University of Catalonia (UPC), specializing in optical networking and telecommunications. His research spans optical burst switching, wavelength assignment algorithms, network planning, and emerging 5G network architectures. He has contributed significantly to the ALLIANCE project developing converged network solutions for 5G and beyond. His research interests focus on Optical Networks , Optical Communication , Broadband Networks , and Computer Architecture , with particular emphasis on physical layer impairments, routing algorithms, and network optimization. His work bridges theoretical network models with practical implementations in next-generation optical infrastructures. Analysis of his recent publications reveals a strong trend toward converged network architectures integrating optical transport with 5G wireless systems, energy-efficient network design, and machine learning applications for network monitoring. His research consistently addresses critical challenges in spectrum fragmentation, quality of transmission, and network resiliency across multiple generations of optical networking technologies. Professor Solé-Pareta has contributed to significant research projects including the ALLIANCE project for 5G network infrastructure. His work demonstrates consistent funding support for advanced research in optical networking and telecommunications infrastructure. He has been involved with the SMARTxAC platform used by the Supercomputing Center of Catalonia (CESCA) for monitoring the Catalan Research and Education Network. His research group appears to focus on optical network architectures, traffic engineering, and next-generation network planning methodologies.

• convex optimization
• mathematical modeling of traffic flows
• Markov processes
• +3 more

Alexander Vladimirovich Gasnikov is a Leading Researcher at the National Research University Higher School of Economics (HSE), specifically within the Faculty of Computer Science, the Institute of Artificial Intelligence and Digital Sciences, and the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis. He has been working at HSE since 2015 and has accumulated 17 years of scientific and teaching experience. Gasnikov received his academic credentials from the Moscow Institute of Physics and Technology (State University). He earned his Bachelor's degree in Applied Mathematics and Physics in 2004, followed by a Master's degree in the same specialty in 2006. He completed postgraduate studies at MIPT from 2006-2007, earned his Candidate of Physical and Mathematical Sciences degree in 2007, was awarded the academic title of Associate Professor in 2011, and ultimately received his Doctor of Physical and Mathematical Sciences degree in 2016 with a dissertation on 'Efficient Numerical Methods for Finding Equilibria in Large Transport Networks.' Gasnikov's research focuses on convex optimization, mathematical modeling of traffic flows, and Markov processes. His work bridges theoretical mathematics with practical applications in optimization algorithms and transportation science. He has made significant contributions to developing efficient numerical methods for optimization problems, particularly in the context of large-scale networks and stochastic settings. His research has evolved from traditional optimization methods to more advanced techniques involving stochasticity, decentralization, and applications to machine learning problems. His publications demonstrate expertise in both theoretical analysis (establishing convergence rates, lower bounds) and practical algorithm development across multiple prestigious venues including Journal of Optimization Theory and Applications, SIAM Journal on Optimization, and top machine learning conferences like NeurIPS. Gasnikov has received recognition including a bonus for publication in international peer-reviewed journals (2019-2021) and has served as a member of the editorial board of the 'Siberian Journal of Computational Mathematics' since 2017. As a supervisor, Gasnikov has guided multiple doctoral candidates, including Alexander Ogaltsov, Titov A. A. (2023), and Tyurin A. I. (2020) for Candidate of Sciences degrees, and Dvurechensky P. E. (2020) for a Doctor of Science degree. His research has been supported by grants from the President of Russia (MD-1320.2018.1) and the Russian Foundation for Basic Research (18-31-20005 mol_a_ved). Gasnikov's work contributes significantly to the theoretical foundations of optimization algorithms that power modern artificial intelligence systems. His leadership in the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis positions him at the forefront of research connecting mathematical optimization with practical applications in machine learning and data science.