Find Academic Supervisors

• Biomedical Engineering
• Nanomedicine
• Tissue Engineering
• +3 more

Dr. Ye Zhang is a Research Fellow at the University of Technology Sydney (UTS), School of Biomedical Engineering. She holds a PhD from Macquarie University (2023) and is affiliated with the Kolling Institute of Sydney University and the Woolcock Institute of Macquarie University. Her multidisciplinary expertise spans computational fluid dynamics, microfluidics, biofabrication, and nanomedicine development. She leads projects in translatable nanomedicine technologies for joint diseases and has developed an innovative biosensor through the NSW Defence Innovation Network internship. Dr. Zhang also holds a Project Management Professional certification and has mentored numerous postgraduate and honors students. Education: PhD in Biomedical Engineering (Macquarie University, 2019-2023); Master’s and Bachelor’s degrees not explicitly stated but inferred from career progression. Research Interests: Focus on biofilm characterization, drug delivery systems (e.g., 3D-printed throat models), microfluidic platforms for biofilm studies, and biomimetic scaffolds for tissue engineering. Her work bridges engineering and medicine to address chronic diseases like osteoarthritis and cardiovascular conditions. Recent Research Trends: Her publications emphasize biofilm dynamics, in vitro models for drug transport, and nanomedicine applications. Key innovations include real-time biofilm monitoring systems and inhalable liposomal drug formulations. Honors: NSW Defence Innovation Network PhD Candidate Internship award (2023). Active collaborations with international teams and governmental/industrial partners. Advising & Grants: Experienced in mentoring students and managing projects, including the UTS Strategic Research Accelerator Program. Her work integrates project management expertise with interdisciplinary research. Labs & Affiliations: Member of the UTS SRA Program, Kolling Institute (USYD), and Woolcock Institute (MQ). Global collaborations include partnerships with Canadian and international institutions.

Fenghui RenView profile

Senior Lecturer

• Multi-Agent Systems
• Reinforcement Learning
• Machine Learning
• +3 more

Fenghui Ren is a Senior Lecturer at the University of Wollongong's School of Computing and Information Technology. Previously, he served as a Lecturer there from 2022 to 2024. He holds a Ph.D. in Computer Science from the University of Wollongong. His research focuses on multi-agent systems, reinforcement learning, and their applications in distributed environments, emergency response, and social network analysis. Ren has secured significant funding, including grants from the Connectivity Innovation Network and the Baosteel-Australia Joint Research and Development Centre. He has been recognized with the Australian Research Council Discovery Early Career Researcher Award (DECRA) in 2014. His work addresses challenges in decentralized resource allocation, resilient telecommunication systems, and smart grid optimization. Ren’s research integrates techniques like hierarchical reinforcement learning, agent-based modeling, and adversarial training to solve complex real-world problems. He actively contributes to conferences and journals, including IEEE Transactions on Cybernetics. Current supervision includes projects on AI-driven financial document extraction, TikTok video propagation prediction, and depression detection through speech analysis. Ren’s funding projects include developing multi-agent systems for telecommunication resilience and BDI agent frameworks for steel industry logistics. His work emphasizes scalability, adaptability, and real-world impact in domains like emergency management and distributed computing. He is a member of the IEEE and has reviewed for multiple prestigious journals.

• Structural Engineering
• Blast Engineering
• Impact Mechanics
• +6 more

Professor Alex Remennikov is a structural engineering academic at the University of Wollongong (UOW), affiliated with the School of Civil, Mining and Environmental Engineering. He holds a PhD from the National University of Construction and Architecture, Kyiv (1994), followed by a postdoctoral fellowship at the University of Canterbury, NZ. Since joining UOW in 2001, he has focused on structural analysis under extreme loads, blast/impact mitigation, and infrastructure protection against terrorism. His research spans experimental and numerical methods, with notable contributions to coal mine safety, hydrogen explosion hazards, and timber-steel composites. Education: PhD, National University of Construction and Architecture, Kyiv, Ukraine (1994) Postdoctoral Fellowship, University of Canterbury, NZ (Civil Engineering, Seismic Analysis) Key Research Themes: Blast and impact-resistant structures Protective infrastructure design Coal mine explosion safety Hydrogen explosion dynamics Advanced composites and hybrid materials His recent work emphasizes hydrogen explosion modeling, timber-steel hybrid systems, and blast hazard mapping for underground coal mines. He leads projects funded by ARC and industry, including the ARC Training Centre for Innovative Composites. Prof. Remennikov is a member of the Centre for Infrastructure Protection and Mine Safety (CIPMS) at UOW.

Mauricio Di LorenzoView profile

Research Fellow

• Hydrogen Production
• Carbon Capture and Storage
• Multiphase Flow Modeling
• +7 more

Dr. Mauricio Di Lorenzo is a Research Fellow at Curtin University, affiliated with the School of Electrical Engineering, Computing and Mathematical Sciences (EECMS) and the Faculty of Science and Engineering. He holds a cross-appointment in the Office of the Provost and works across Curtin's Perth, Dubai, Malaysia, Mauritius, and Singapore campuses. His career spans over 20 years in R&D roles at CSIRO Energy (2007–2020) and PDVSA-Intevep (1991–2002), with expertise in multiphase flow, hydrate management, and energy storage technologies. His research focuses on large-scale hydrogen production and storage, carbon capture/utilization, and multiphase flowloop design. Notable contributions include developing methodologies for hydrate formation/deposition modeling in gas-dominant pipelines and advancing surfactant-based solutions for enhanced oil recovery. He has led projects for the Future Energy Exports CRC and collaborated internationally on flow assurance challenges. Di Lorenzo's work integrates experimental rigor with computational modeling, emphasizing data quality and interdisciplinary problem-solving. He has co-authored over 20 peer-reviewed publications since 1990, spanning topics from semiconductor physics (1990s) to modern energy systems (2020s). His teaching experience includes lecturing in physics at Venezuelan universities and co-supervising student theses. He maintains active partnerships with global research institutions and industry stakeholders, driving innovation in sustainable energy technologies while advocating for laboratory safety and mentorship programs.

• Geophysics
• Mineral Physics
• X-ray Crystallography
• +4 more

Prof. Dan Shim is a Professor in the School of Earth and Space Exploration at Arizona State University (ASU), located in Tempe. He holds a PhD in Geosciences from Princeton University (2001) and previously served at the University of California, Berkeley (Miller Research Fellow, 2001–2003), MIT (Assistant/Associate Professor, 2003–2012), before joining ASU in 2012. His research focuses on planetary materials under extreme conditions, using techniques like laser-heated diamond-anvil cells and synchrotron/XFEL analysis to study high-pressure/temperature behavior of minerals, liquids, and alloys relevant to Earth and exoplanet interiors. Education: PhD in Geosciences, Princeton University (2001) M.S. Geological Sciences, Seoul National University (1994) B.S. Geological Sciences, Seoul National University (1992) Research interests include: Planetary core-mantle interactions Hydrogen and volatile behavior in planetary interiors High-pressure phase transitions in silicates, oxides, and metals X-ray crystallography and spectroscopy of planetary materials Experimental facilities like ASU’s FORCE (Facility for Open Research in a Compressed Environment) Recent work explores exoplanet compositions, ULVZ origins, and hydrogen storage mechanisms in planetary cores. Key contributions include the development of the FORCE facility, which enables large-scale multi-anvil press experiments for simulating deep planetary conditions. His group uses novel techniques like vibrational electron energy loss spectroscopy to detect hydrogen at sub-nanometer scales.

Mohammad MarufuzzamanView profile

Associate Professor

• Supply Chain Optimization
• Renewable Energy Systems
• Stochastic Programming
• +7 more

Mohammad Marufuzzaman is an Associate Professor and Department Head in the Department of Industrial & Systems Engineering at Mississippi State University (MSU), holding the Charles R. Stephenson Endowed Professorship. He joined the faculty in 2014 as a Visiting Assistant Professor before advancing to his current role. His research focuses on supply chain optimization with applications in renewable energy, stochastic programming, decomposition methods, and risk management. Dr. Marufuzzaman holds a Ph.D. in Industrial & Systems Engineering from MSU (2014), an MASc in Industrial Systems Engineering from the University of Regina, Canada (2010), and a B.Sc. in Industrial & Production Engineering from Shah Jalal University of Science & Technology, Bangladesh (2006). His work bridges theoretical optimization techniques with practical applications in energy systems, disaster logistics, and sustainable infrastructure. His research interests span renewable energy supply chains, large-scale network design, and resilience engineering. Notable contributions include predictive models for wood chip moisture content using machine vision, disaster response frameworks for hurricane-impacted regions, and optimization models for electric vehicle infrastructure. His publications appear in leading journals such as Transportation Science and Computers & Operations Research . Dr. Marufuzzaman is a member of INFORMS and IIE. His recent work emphasizes interdisciplinary solutions for complex systems, including military base modernization, marine debris management, and IoT-enabled energy systems. He has developed novel algorithms for stochastic optimization problems and contributed to policy-relevant research on biomass energy utilization in rural regions.

Michael SchreckenbergView profile

Professor

• Transportation Engineering
• Traffic Simulation
• Statistical Physics
• +3 more

Professor Michael Schreckenberg is a faculty member at the University of Duisburg-Essen, holding the first German professorship in Physics of Transport and Traffic since 1997. His research focuses on large-scale transportation systems modeling, simulation, and optimization, particularly road traffic dynamics and human behavior impacts. He leads projects like autobahn.NRW and RuhrPilot , which integrate real-time traffic data into simulations for forecasting and network analysis. His work extends to pedestrian dynamics and evacuation modeling, including applications for passenger ships. Education: Earned a PhD in statistical physics from the University of Cologne (1985) after studying theoretical physics there. Joined the University of Duisburg-Essen in 1994. Research Interests: Traffic flow modeling (e.g., Nagel-Schreckenberg cellular automata), human factors in ITS, synchronized traffic patterns, and evacuation simulations. Recent studies address automated vehicles, mixed traffic systems, and spatiotemporal traffic correlations. Key Projects: Online traffic forecasting in North Rhine-Westphalia Analysis of driver reactions to traffic information Crowd behavior during emergencies Labs & Tools: Founded the Physics of Transport and Traffic department at UDE, develops simulation tools like CAMAT for airport ground traffic and FAST for pedestrian evacuation.

Marc OlanoView profile

Associate Professor

• Computer Graphics
• Real-Time Systems
• Game Development
• +5 more

Dr. Marc Olano is an Associate Professor of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He specializes in real-time 3D graphics, non-graphics applications of graphics hardware, and game development. As director of UMBC’s Game Development Track and 3D photogrammetric scanning facility, he focuses on advancing interactive technologies and environmental monitoring systems like Ecosynth. His research collaborations include work with gaming companies such as Firaxis, Epic Games, and Activision, as well as contributions to virtual reality (VR) applications in healthcare and scientific visualization. Dr. Olano holds a Ph.D. in Computer Science from the University of North Carolina and a B.S. in Electrical Engineering from the University of Illinois. Education: Ph.D., Computer Science, UNC (1998); B.S., Electrical Engineering, UIUC (1990). Research Interests: Computer graphics, GPU acceleration, VR, game development, and ecological 3D scanning. Key Roles: Director of Game Development Track, Editor-in-Chief of the Journal of Computer Graphics Techniques. Olano’s work bridges academia and industry, emphasizing practical applications like texture compression for games, VR-based rehabilitation systems, and UAV-driven environmental analysis. His research often leverages GPU computing to solve real-world problems, from optimizing rendering algorithms to enabling large-scale ecological data collection through Ecosynth. Publications span VR systems, subsurface scattering techniques, and GPU algorithms, reflecting his commitment to advancing interactive and computational graphics. His teaching and mentorship in the Game Development Track prepare students for roles in game design, while his lab facilities provide hands-on experience with cutting-edge technologies.

Felipe Aros-VeraView profile

Associate Professor

• Humanitarian Logistics
• Operations Research
• Transportation and Urban Logistics
• +3 more

Felipe Aros-Vera is an Associate Professor and Graduate Chair in the Department of Industrial and Systems Engineering at Ohio University's Russ College of Engineering and Technology. He holds a Ph.D. in Transportation Engineering from Rensselaer Polytechnic Institute and degrees from Pontificia Universidad Católica de Chile. His research focuses on humanitarian logistics, operations research, and transportation systems, particularly in disaster response, critical infrastructure resilience, and combating human trafficking through supply chain modeling. He advises the Global Engineering Projects (GEP) student organization, which collaborates with Ghana's Offinso-Maase village on engineering initiatives like solar water pumps and electrical systems analysis. Aros-Vera co-chairs the Transportation Research Board's Humanitarian Relief Subcommittee (AMR20(1)) and participates in the College of Humanitarian Operations and Crisis Management (POMS) and INFORMS' Location Analysis Section. His work spans academic publications in journals like European Journal of Operational Research and Transportation Research, emphasizing practical applications such as optimizing post-disaster distribution networks, microgrid placement for disaster resilience, and crowd management during large events. His research portfolio includes studies on pandemic logistics for maternal-child care during crises, infrastructure interdependency modeling, and urban freight sustainability programs. He has led projects analyzing Hurricane Maria's impact on Puerto Rico's infrastructure and developed frameworks for disrupting illicit networks using operations research techniques. Aros-Vera's interdisciplinary approach bridges theoretical models with real-world humanitarian challenges, fostering partnerships between academia, government, and communities.

Andrew GraettingerView profile

Professor

• Community Resilience
• GIS Technology
• Disaster Management
• +3 more

Andrew Graettinger serves as Associate Dean for Research at the University of Wisconsin-Milwaukee's College of Engineering & Applied Science, advancing the institution's R1 research status through interdisciplinary initiatives. Previously, he held professorial roles at the University of Alabama, directing graduate programs in Civil, Construction and Environmental Engineering. His work focuses on applying GIS technology to address civil engineering challenges, with $7.5M+ in funded research. Education: PhD in Civil Engineering, Northwestern University (1998) MS in Civil Engineering, University of Wisconsin-Milwaukee (1994) BA in Geography, University of Wisconsin-Milwaukee (1989) Research emphases include community resilience post-extreme events, geotechnical sustainability, and 3D printing applications. His work bridges geospatial data analysis with infrastructure challenges, including disaster recovery frameworks and transportation system optimizations. Recent projects address flood resilience modeling, tornado impact assessment, and WisDOT data governance initiatives. Grants and collaborations focus on large-scale data integration (e.g., LiDAR, machine learning) and disaster preparedness. His interdisciplinary approach combines engineering, environmental science, and policy to enhance regional resilience and innovation.

David PisingerView profile

Professor

• Operations Research
• Management Science
• Network Design
• +3 more

David Pisinger is a Professor at the Department of Technology, Management and Economics, Technical University of Denmark (DTU). His research focuses on Operations Research, Management Science, and Optimization, with significant contributions to maritime transportation, offshore wind farm design, and stochastic optimization. He leads the DECIDE project (ERC-2022-ADG), exploring machine learning for decision-making under uncertainty. His research interests include network design, vehicle routing, energy systems modeling, and combinatorial optimization. Notable recent work addresses challenges in multi-parallel-aisle warehouses, tramp ship routing, and immunization strategies for epidemic outbreaks. Research Trends in Articles: Recent publications emphasize maritime logistics, renewable energy optimization (offshore wind farms), and stochastic programming applications. His work bridges theoretical optimization and real-world problems in transportation, energy, and telecommunication networks. Awards: ERC-2022-ADG Grant (2023) Finalist - EURO Excellence in Practice Award (2021, 2018) Best Student Paper Award (ICORES 2017) Advising & Grants: Supervises PhD students in stochastic optimization, energy systems, and maritime logistics. PI of projects like DECIDE (2024–2029), SUSTAINABULK (2022–2025), and others. Teams/Labs: DECIDE Project Team (machine learning for decision-making under uncertainty). Collaborations on offshore wind farm optimization, energy system modeling, and maritime logistics.

Jajnabalkya GuhathakurtaView profile

Researcher

• Computational Imaging
• Materials Science
• Structural Engineering
• +3 more

Jajnabalkya Guhathakurta is a Researcher at the Institute of Computer Architecture and Computer Engineering within Faculty 05 of the University of Stuttgart. His work focuses on advanced materials science, computational imaging, and structural analysis. He specializes in composite materials, computed tomography (CT), and the mechanical behavior of advanced composites under various conditions. His research interests include fiber-reinforced concrete systems, interpenetrated composites, and the application of CT imaging for non-destructive evaluation of materials. He has contributed to studies on steel fiber orientation effects, Li-ion cell expansion phenomena, and data-driven material characterization. His work integrates computational methods with experimental analysis, particularly in high-resolution imaging and dynamic material response modeling. Key areas of exploration include the potato effect in Li-ion cells, bubble dynamics in chemical flows, and the optimization of composite material properties through advanced fabrication techniques. His publications span interdisciplinary fields, combining mechanical engineering, materials science, and computational methodologies.

Alina VereshchakaView profile

Assistant Professor

• Optimal control in complex systems
• Social behavior modeling
• Deep reinforcement learning
• +5 more

Alina Vereshchaka is an Assistant Professor of Teaching in the Department of Computer Science and Engineering at the University at Buffalo. She holds a PhD in Computer Science from the same institution (2021). Her research focuses on optimal control in complex systems, including social behavior modeling, deep reinforcement learning, multi-agent systems, adversarial machine learning, transportation dynamics, and large-scale social system dynamics. She leads projects involving epidemic modeling, smart city infrastructure optimization, and disinformation detection. Education: PhD in Computer Science, University at Buffalo, 2021 Her work bridges theoretical machine learning advancements with real-world applications in public health, transportation, and crisis management. Key research themes include: Optimizing epidemic intervention strategies using reinforcement learning Urban traffic prediction through vehicle trajectory analysis Automated disinformation detection systems Multi-agent resource allocation during disasters Dr. Vereshchaka's recent publications (2018-2024) emphasize data-driven decision-making frameworks across transportation networks, healthcare systems, and social media platforms. Though no specific grants or awards are listed, her work reflects interdisciplinary collaboration with engineering and public health domains. She currently advises no listed students and maintains an active research website and dblp profile for further details.

Andreas StavridisView profile

Associate Professor

• Structural Engineering
• Earthquake Engineering
• Bridge Engineering
• +5 more

Andreas Stavridis is an Associate Professor at the University at Buffalo, State University of New York , with a joint appointment as Professor at the University of Patras . His work focuses on structural and earthquake engineering, particularly masonry-infilled RC frames, seismic isolation systems, and post-earthquake damage assessment. Academic Background: PhD and MS in Structural Engineering from UC San Diego, Diploma in Civil Engineering from National Technical University of Athens Research Leadership: Director of the Structural Engineering and Earthquake Simulation Laboratory Dr. Stavridis specializes in nonlinear structural analysis, large-scale testing, and finite element modeling. His research addresses seismic vulnerability of non-ductile RC frames, innovative retrofit schemes (e.g., sliding subpanels, PVC-based isolation systems), and masonry-concrete interaction mechanisms. He has led field investigations of earthquake-damaged buildings in Nepal (2015 Gorkha earthquake) and Mexico (2017 Puebla-Morelos earthquake), integrating ambient vibration data with point cloud measurements for damage quantification. Current projects include developing simplified modeling frameworks for masonry infills, advancing surrogate statistical models for seismic risk assessment, and optimizing low-cost seismic solutions for developing countries. His work bridges experimental validation with computational modeling, appearing in 99+ peer-reviewed publications and collaborations with international teams across the US, Greece, and Nepal. Key Research Themes: Seismic Performance of Infilled RC Frames Nonlinear Dynamic Modeling Hybrid Retrofit Techniques Post-Disaster Structural Assessment Low-Cost Base Isolation Systems Bayesian Model Updating

Akshat KUMARView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Multiagent Systems
• +4 more

Akshat Kumar is an Associate Professor (Research Track) in the School of Information Systems at Singapore Management University (SMU). He holds a PhD in Computer Science from the University of Massachusetts Amherst (2013) and was previously a Research Scientist at IBM Research India. Research Focus : His work lies at the intersection of AI, Machine Learning, and Multiagent Systems, with applications in urban mobility optimization (e.g., autonomous vehicles, maritime traffic management), decision-making under uncertainty, and computational sustainability. He leads the Representation, Learning, and Reasoning (RLR) Lab, which develops algorithms for large-scale multiagent coordination using reinforcement learning and probabilistic inference. Awards & Grants : Recipient of the Lee Kong Chian Fellowship (2020-22), Best Paper Awards at AAAI (2017) and ICAPS (2014), and featured in IEEE’s 'AI’s Ten to Watch' (2018). Principal Investigator (PI) of Singapore MOE Tier-2 grants totaling S$1.1M for projects like 'Data Driven Collective Decision Making For Urban System Optimization' (2019–2021). Education & Teaching : Taught courses on computational thinking, artificial intelligence, and spreadsheet modeling. Advises PhD students and research engineers on topics like reinforcement learning, maritime traffic simulation, and cloud security policy design. Impact : His research addresses challenges in urban systems, such as optimizing autonomous taxi fleets, reducing maritime congestion, and improving smart grid management. Collaborations include Fujitsu-SMU Urban Computing Lab and Singapore port authorities.