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Amory MartinView profile

Adjunct Professor

• Earthquake Engineering
• Structural Optimization
• Topology Optimization
• +5 more

Dr. Amory Martin is an Adjunct Professor at New York University's Tandon School of Engineering and a Senior Engineer at Exponent's New York office. His expertise spans Earthquake Engineering , Structural Optimization , and Multi-Hazard Risk Analysis , with a focus on seismic-resistant design, structural failure investigation, and climate change adaptation. Ph.D., Civil and Environmental Engineering, Stanford University (2020) M.S., Civil and Environmental Engineering, Stanford University (2016) B.S., Civil Engineering, Johns Hopkins University (2014) B.S., Mathematics, Johns Hopkins University (2014) Dr. Martin's research involves dynamic analysis of complex structures , topology optimization algorithms , and nonlinear seismic response modeling . His work integrates high-performance computing and data-driven techniques to enhance structural resilience. His recent publications focus on earthquake-induced bridge damage , seismic isolation systems , and socio-economic impacts of disasters . These emphasize nonlinear dynamics , multi-hazard coordination , and virtual reconnaissance . National Science Foundation Graduate Research Fellowship Stanford School of Engineering Fellowship Johns Hopkins Civil Engineering Award Tau Beta Pi Engineering Honor Society Dr. Martin has led projects on high-rise building analysis , garage collapse investigations , and seismic design of highway bridges . He served as a consultant for the World Bank on pandemic economic impacts and is actively involved in code compliance and expert report writing .

Eduardo DavalosView profile

Assistant Professor

• Large Language Models
• Human-Computer Interaction
• Artificial Intelligence for Education
• +7 more

Eduardo Davalos is an Assistant Professor in the Computer Science department at Trinity University in San Antonio, Texas. His work focuses on the intersection of AI in Education (AIED), Human-Computer Interaction (HCI), and Large Language Models (LLMs), with the aim of developing technologies that enhance learning experiences while reducing teacher workload through privacy-preserving, browser-native approaches. Dr. Davalos received his academic training at: B.S. in Electrical Engineering from St. Mary's University M.S. in Electrical Engineering from St. Mary's University Ph.D. in Computer Science from Vanderbilt University His research centers on developing technologies that translate into scalable learning solutions, with particular emphasis on browser-based sensing and modeling. Dr. Davalos is currently developing RedForest, a next-generation e-learning platform that combines AI, gamification, online collaboration, and domain-specific activities to enhance learning while providing AI-assisted lesson planning. His work bridges computer science, cognitive science, and educational psychology, with applications across multiple domains including literacy, nursing education, computer science education, and physics. He has developed WebEyeTrack, a head-pose-aware, deep-learning gaze estimation framework for browsers that runs entirely on-device. Analysis of Dr. Davalos's publications reveals a clear trajectory from foundational technology development (like WebEyeTrack) to sophisticated educational applications using LLMs for data analysis. His work consistently emphasizes practical, teacher-friendly tools that can be deployed in real classrooms without compromising student privacy. The research spans multiple educational contexts and demonstrates strong interdisciplinary collaboration, particularly with experts in cognitive science, psychology, and domain-specific education fields. Dr. Davalos leads the RedForest Lab, which focuses on creating learning technologies that benefit both students and teachers. His research has been supported by grants from the Institute of Education Sciences, U.S. Department of Education (Grants R305A150199 and R305A210347 to Vanderbilt University), indicating recognition of the importance and potential impact of his work in educational technology.

Michela BarbotView profile

Research Professor

• Legal History
• Economic History
• Institutional Theory
• +12 more

Michela Barbot is a Research Professor at CNRS and ENS Paris-Saclay, serving as Director of the Research Unit IDHE.S (Institutions et Dynamiques Historiques de l'Economie et de la Société). She holds advanced degrees from Bocconi University (Milan) and Sciences Po Paris, with a distinguished career spanning prestigious institutions including CNRS, ENS Paris-Saclay, Sciences Po Paris, and Bocconi University. Her educational background includes: M.A. in Economics (DES: Economic and Social Disciplines) - Bocconi University, Milan PhD in Social and Economic History - Bocconi University, Milan HDR (Habilitée à diriger des recherches) - Sciences Po Paris Law School Professor Barbot's research program examines the historical and comparative dimensions of legal and economic institutions from the 16th to 21st centuries. Her work integrates theoretical frameworks from Law in Action, Old and New Institutionalisms, Law and Economics, and Historical Comparative Sociology with empirical investigations of property rights systems, market regulation, and urban development. She has developed innovative approaches to understanding how legal frameworks shape economic behavior and social organization across different historical contexts and geographical scales. Analysis of her recent publications reveals a consistent scholarly trajectory focused on the interplay between legal institutions and economic practices. Her work demonstrates how historical analysis of valuation systems, property rights, and market regulation can inform contemporary debates about economic justice, sustainable development, and the governance of cultural heritage. Barbot's research often bridges theoretical frameworks from institutional economics with detailed historical case studies, creating valuable interdisciplinary connections between legal history, economic history, and urban studies. Among her notable recognitions: Fellow of the Canada Research Chair in Transsystemic Property Law and Sustainable Communities European Research Based Universities Chair of Excellence Research in Paris Fellowship Multiple fellowships from Ecole Française de Rome and International Institute F. Datini As an educator, Professor Barbot has supervised PhD students including Huiying Li (co-supervised with Pr. Zhao Yeqin) and Pierre-Adrien Ladant (co-supervised with Pr. A. Caracausi). Her research has been supported by numerous grants from the Italian Ministry of Education, Gobierno de Navarra (Spain), and other international funding bodies. She has coordinated the Economic History Summer School since 2013 and currently serves as Principal Investigator for WP1 of the PEPR VDBI-ANR Project TRACES, which focuses on transforming heritage through multi-scale systemic approaches. Professor Barbot leads several significant research initiatives including the PEPS seminar (Propriété, environnement, patrimoine et société) at ENS Paris-Saclay and participates in international collaborations such as the ANR project EXPERTS on building expertise in Paris (1690-1790). Her scholarly leadership extends to editorial roles with journals including Quaderni Storici and Ædificare, where she serves on international editorial boards.

Theresia Veronika RampiselaView profile

Researcher

• Algorithmic Fairness
• Recommender Systems
• Information Retrieval
• +3 more

Theresia Veronika Rampisela is a PhD student and Guest Researcher in the Department of Computer Science at the University of Copenhagen's Faculty of Science, specializing in Machine Learning. She actively contributes to the Algorithms, Data, and Democracy (ADD) project (https://algorithms.dk/), which investigates the societal implications of algorithmic decision-making systems. Her academic background includes a Master's degree in Computer Science from the University of Indonesia, providing foundational expertise in computational methods and data analysis. This education has enabled her transition from early work in information retrieval to specialized research in algorithmic fairness. Rampisela's research program critically examines fairness evaluation in machine learning applications, with particular focus on recommender systems. She investigates both group and individual fairness metrics, exploring their practical implementation challenges and limitations. Her work addresses the fundamental tension between recommendation relevance and equitable treatment of diverse user populations. Earlier research included academic expert finding using semantic techniques and medical applications involving schizophrenia classification with SVMs. Analysis of her publication trajectory reveals progressive sophistication in algorithmic fairness research. Starting with foundational work on expert finding systems, she has advanced to developing novel frameworks like Pareto optimization for balancing competing objectives in recommendation algorithms. Her publications in top venues including ACM Transactions on Recommender Systems and the ACM SIGIR Conference demonstrate growing recognition in this critical field. Mensa International Scholarship (2024) Rampisela collaborates extensively with Maria Maistro, Tuukka Ruotsalo, and Christina Lioma through the ADD project. Her research has significant practical implications for technology companies developing recommendation systems and policymakers regulating algorithmic fairness. She maintains an active scholarly profile documented through her ORCID (https://orcid.org/0000-0003-1233-7690) and demonstrates growing influence with mentions across academic social platforms.

Liqian ChenView profile

Professor

• Program analysis
• Program verification
• Abstract interpretation
• +3 more

Liqian Chen is a Full Professor and PhD Supervisor in the College of Computer Science and Technology at the National University of Defense Technology (NUDT) in Changsha, China. With a prolific research career spanning over a decade, Professor Chen has established himself as a leading expert in program analysis, verification, and automated program repair. His work bridges theoretical foundations with practical applications, particularly in the areas of abstract interpretation and numerical program analysis. Professor Chen's primary research interests include: Program analysis and verification Abstract interpretation Automated program repair Floating-point analysis Neural network verification His research focuses on developing rigorous theoretical frameworks for program analysis while ensuring practical applicability to real-world software systems. A significant portion of his work addresses the challenges of numerical accuracy in software, particularly in floating-point computations, and has extended these techniques to the emerging domain of neural network verification. Analysis of Professor Chen's recent publications reveals several key trends in his research trajectory. His work has evolved from foundational abstract interpretation techniques to address increasingly complex software systems, including neural networks. There's a clear progression from theoretical developments in abstract domains to practical applications in software verification and repair. His recent work demonstrates a growing emphasis on the intersection of traditional program analysis with machine learning systems, particularly in verifying neural network behavior and addressing numerical instability in AI systems. Professor Chen has received notable recognition for his contributions to the field: ACM SIGSOFT Distinguished Paper Award (ISSTA 2024) Best Paper Award (APSEC 2017) Best Paper Award Nomination (EMSOFT 2015) As an academic advisor, Professor Chen supervises numerous PhD and Master's students working on cutting-edge research in program analysis and verification. His team has developed several influential tools including AutoRNP (for automatically detecting and repairing floating-point errors), Software Apron (a library for numerical abstract domains), and F-IKOS (a static analyzer for Fortran programs). Professor Chen has secured substantial research funding to support his work, though specific grant details are not provided in the available information. He actively serves the research community through program committee roles for major conferences including ASE, SAS, and VMCAI, and as a guest editor for journals such as Automated Software Engineering Journal and Journal of Systems Architecture. Professor Chen leads a vibrant research group focused on high-confidence software technologies. His team, comprising PhD students, Master's students, and research engineers, collaborates closely on projects spanning from theoretical foundations of program analysis to practical tool development. The group maintains strong connections with both academic institutions and industry partners, facilitating the transfer of research innovations to real-world applications. Their work is characterized by rigorous theoretical underpinnings combined with practical validation on real software systems.

Yasser KhanView profile

Assistant Professor

• Flexible and Stretchable Electronics
• Wearable Medical Devices
• Bioelectronics
• +7 more

Yasser Khan is an Assistant Professor of Electrical and Computer Engineering at the University of Southern California's Ming Hsieh Department. He leads the Khan Lab, which focuses on sensor systems for precision health and psychiatry. His lab is part of the USC Institute for Technology and Medical Systems (ITEMS), a joint Keck-Viterbi initiative with presence in both the USC Viterbi School of Engineering and Keck School of Medicine of USC. Dr. Khan received his B.S. and M.S. in Electrical Engineering from the University of Texas at Dallas and King Abdullah University of Science and Technology, respectively. He completed his Ph.D. in Electrical Engineering and Computer Sciences at UC Berkeley in 2018, followed by postdoctoral research in Stanford University's Department of Chemical Engineering. As an expert in flexible and stretchable electronics, Khan's research focuses on additive manufacturing and hardware AI to produce skin-like wearables, implantables, and ingestibles for precision health and psychiatry. His lab's core expertise spans biophotonic devices, bioelectronic interfaces, biochemical sensors, flexible hybrid electronics, and hardware-enabled AI systems that enable near- and in-sensor data classification. His publication record shows a progression from fundamental flexible electronics research to increasingly sophisticated medical applications, with recent work focusing on ingestible electronics, AI-enabled sensing, and precision health applications. His work has been published in top journals including Nature Electronics, PNAS, Nature Communications, and Advanced Materials. 2025 USC Viterbi Junior Faculty Research Award 2025 AFOSR Young Investigator Award 2024 Packard Fellowship 2024 Zumberge Award Elevated to IEEE Senior Member (2024) Best Paper Award at IEEE BioCAS Professor Khan actively mentors students in his lab and has secured significant funding from NIH, AFOSR, Packard Foundation, and other agencies for projects developing multimodal AI and sensing technology for mental health, ingestible electronics, and precision psychiatry applications. His lab collaborates with institutions including Binghamton University, i3 Electronics, Lockheed Martin, and American Semiconductor on flexible hybrid electronics projects. The Khan Lab at USC is dedicated to making medical devices accessible to everyone through innovations in flexible and stretchable electronics. The lab's vision encompasses developing skin-like wearables that seamlessly measure vital signs, ingestible electronics for gastrointestinal monitoring, and implantable devices for precision psychiatry applications.

Alexander ZhiponovView profile

Assistant Professor

• Bridge Engineering
• Condition Assessment of Bridges
• Composite Materials in Bridge Design
• +5 more

Alexander Zhiponov serves as Chief Assistant Professor at the University of Architecture, Civil Engineering and Geodesy (UACEG) in Sofia, Bulgaria, within the Faculty of Transport Engineering's Department of Roads and Transport Facilities. His office (Cabinet B12) is located on the 3rd floor between Building A and Building B, with contact email ajiponov_fte@uacg.bg. He holds a Doctorate in Structural Engineering (Bridges, 2019) and Master's in Transportation Engineering (2012) from UACEG, with language proficiency in English (C1), French (B2), and Danish (A1). His educational qualifications include: 2019: Doctor of Engineering in Structural Engineering (Bridges) 2012: Master of Engineering in Transportation Engineering Zhiponov's research centers on practical bridge engineering challenges , specializing in condition assessment of aging infrastructure, composite material applications, and structural modeling. His expertise spans steel-concrete composite bridges , drone-based photogrammetry for arch bridge documentation , and retrofitting solutions for historic crossings like the Danube bridge at Ruse-Giurgiu. He actively employs Finite Element Analysis and BIM methodologies while addressing Bulgaria's specific infrastructure needs, particularly in Sofia's transport network. Analysis of his 15 publications (2018-2025) reveals consistent focus on real-world bridge rehabilitation , with 60% addressing Bulgarian infrastructure and 30% incorporating international case studies (notably Denmark's geotechnical solutions). Key trends include innovative inspection techniques for 50+ year-old structures, lifecycle extension through modern materials, and multi-criteria analysis for major crossings like the proposed third Danube bridge. No scientific awards or fellowships were documented in available sources. He actively supervises student research and provides consulting services, with collaborations primarily involving Lazar Georgiev and Vasil Nikolov on projects spanning structural analysis, tunnel assessment, and composite bridge design. His work demonstrates strong integration with UACEG's educational mission through thesis supervision and specialized coursework in transportation structures. Zhiponov utilizes UACEG's accredited laboratories for structural testing and material analysis, particularly for bridge component evaluation. His research increasingly incorporates drone technology and advanced modeling to address Sofia's aging infrastructure challenges while contributing to national bridge management protocols.

Sarah RachutView profile

Researcher

• Digital Law
• E-Government
• Data Protection
• +7 more

Dr. Sarah Rachut is a Scientific Associate at the Technical University of Munich (TUM), working at the Chair of Digital Law and Security under Prof. Dr. Dirk Heckmann. She serves as Managing Director of the TUM Center for Digital Public Services research institute and is affiliated with the TUM School of Social Sciences and Technology in the Department of Governance. Her work bridges legal scholarship with practical digital governance solutions, focusing on fundamental constitutional issues in digital contexts. Dr. Rachut studied law with a European and international focus at the University of Passau and completed her legal traineeship at the Higher Regional Court of Munich. She earned her doctorate with a dissertation titled "Realization of Fundamental Rights in Digital Contexts," which received the Science Prize of the Society for Data Protection and Data Security in November 2024. She is also a member of the German Society for Law and Informatics (DGRI) and an associate member of the eSports Law Research Center at the University of Augsburg. Her research centers on e-government, e-health, and e-education law, with particular emphasis on how constitutional rights can be realized in digital environments. Dr. Rachut challenges the misconception that law hinders digitalization, arguing instead that legal frameworks enable balanced technological advancement that respects fundamental rights. She advocates for moving from application-based administration toward proactive government services that automatically recognize citizens' legitimate claims without requiring burdensome documentation. Dr. Rachut's extensive publication record demonstrates deep expertise in AI regulation, digital administrative procedures, and electronic examination systems. Her work uniquely combines theoretical legal scholarship with practical implementation experience, as evidenced by her pivotal role in developing Bavaria's Fernprüfungserprobungsverordnung (BayFEV) during the pandemic, which became a national model for legally secure remote examinations. Young Leader in Gov Tech Award by Handelsblatt and Possible (2024) Science Prize of the Society for Data Protection and Data Security (2024) Second place in Young Scientist of the Year award (2025) Talent in BayFiD program (Bavaria's Women in Digital Professions) (2020) Scholarship holder at Graduate School of Bavarian Research Institute for Digital Transformation (2022) As Managing Director of the TUM Center for Digital Public Services, Dr. Rachut mentors students and leads research initiatives focused on digital transformation in government. She has successfully guided student teams to multiple awards in the "Digital Future Challenge" competition. Her leadership extends to shaping policy through expert opinions for legislative bodies including the German Bundestag and various state parliaments, where she has advised on the Bavarian Digital Law and other key digital governance frameworks. Dr. Rachut plays a key role in the TUM Center for Digital Public Services, which serves as an interdisciplinary hub for digital government research. She also serves as spokesperson for the "E-Government Law" working group of the National E-Government Competence Center (NEGZ) and co-edits the journal "Ordnung der Wissenschaft" since October 2024.

• Environmental Economics
• Natural Resource Economics
• Land Use Economics
• +6 more

Mette Termansen is a Professor in the Department of Food and Resource Economics at the University of Copenhagen, specializing in spatially explicit economic analysis of land use decision-making, ecosystem service valuation, and environmental policy design. Her current leadership of the H2020 EFFECT project focuses on optimizing voluntary environmental schemes for farming systems across Europe. Her academic credentials include: 2005: YCAP York Certificate of Academic Practices (MA Level), University of York 2001: DPhil in Environmental Economics and Environmental Management, University of York 1996: MSc in Environmental Economics, University of York 1994: MSc in Forest Science, Royal Veterinary and Agricultural University, Copenhagen Termansen's research centers on quantifying trade-offs between agricultural production and environmental objectives, with emphasis on biodiversity conservation, climate adaptation, water quality, and recreational values. She develops spatially explicit models to evaluate policy impacts, particularly investigating how alternative contract designs influence farmer participation and environmental outcomes in agri-environmental schemes. Her interdisciplinary approach integrates ecological data with economic behavior to inform evidence-based environmental governance. Analysis of her 2024-2025 publications reveals consistent methodological focus on integrated environmental-economic modeling, scenario analysis, and policy pathway evaluation. Key thematic clusters include spatial optimization of land use for multiple environmental goals, behavioral insights in agricultural decision-making, and valuation frameworks incorporating diverse societal values of nature. Her work predominantly addresses European agricultural contexts with strong policy relevance for nitrogen regulation, biodiversity protection, and climate mitigation. Termansen teaches BSc and MSc modules in Environmental and Natural Resource Economics while leading externally funded research initiatives. Her primary active grant is the Horizon 2020 EFFECT project, with additional collaborations conducted through contractual agreements with the Danish Ministry of Environment and Food. She maintains partnerships with agricultural producers, marine sectors, and environmental NGOs, primarily serving in advisory capacities within research consortia where the University of Copenhagen acts as the contracting entity.

Chris J SeegerView profile

Professor

• Landscape Architecture
• Geographic Information Systems (GIS)
• Community Planning
• +4 more

Chris J Seeger is a Professor and Landscape Architecture Extension Specialist at Iowa State University's Department of Landscape Architecture within the College of Design. His work focuses on leveraging Geographic Information Systems (GIS), participatory design, and community engagement to enhance urban walkability and infrastructure planning. He specializes in methodologies like Facilitated-Volunteered Geographic Information (F-VGI), integrating citizen input with spatial data for community-driven solutions. Key projects include the I-WALK initiative, which assesses walkability in Iowa communities through data collection and participatory mapping. His research spans over two decades, with early contributions to web-based GIS tools (e.g., VaSS Builder) and historical environmental documentation. He has collaborated with schools, municipalities, and nonprofits to produce over 50 community reports analyzing infrastructure, transportation, and public health. Seeger’s expertise bridges technology and practice, emphasizing low-tech/high-tech integration for accessible urban planning. His work often addresses challenges in rural-urban contrasts, sustainable design, and technology adoption in underserved areas.

Claudio LuchinatView profile

Professor

• Structural Biology
• Metabolomics
• NMR Methods
• +4 more

Claudio Luchinat is a Full Professor of Chemistry at the University of Florence, affiliated with the Department of Chemistry and the Magnetic Resonance Center (CERM). He co-founded CERM and currently leads the Interuniversity Consortium on Magnetic Resonance of Metalloproteins (CIRMMP). His research focuses on structural biology, paramagnetic NMR methodologies, and metabolomics. Notable contributions include integrating structural techniques (X-ray/NMR) for biomolecular accuracy, advancing Dynamic Nuclear Polarization (DNP) theory, and pioneering NMR-based metabolomics for disease biomarker discovery. Luchinat’s work spans metalloprotein studies, relaxometry applications, and MRI contrast agent development. He has been a key figure in metabolomics, publishing influential studies on Parkinson’s disease, cardiovascular risk, and cancer. His research bridges theoretical and applied domains, with global collaborations and invitations to international conferences as a keynote speaker. He holds roles as director of CERM and CIRMMP, and is recognized as a leading expert in structural and metabolic NMR. His lab develops novel statistical methods for metabolomics data analysis, emphasizing preanalytical standardization in multicenter studies.

Valerio AcocellaView profile

Associate Professor

• Volcano-tectonics
• Caldera dynamics
• Volcano deformation
• +7 more

Valerio Acocella is a Professor at the Department of Science, University of Roma Tre, Italy. His academic career includes a Ph.D. in Earth Sciences from the University of Siena (1995-1999) and post-doctoral research on volcano-tectonics since 2001. He has held permanent research positions since 2006 and was promoted to Professor in June 2016. Acocella's research focuses on volcano-tectonics , caldera dynamics , volcano deformation , and dike propagation . He utilizes field studies, analogue/numerical modeling, and InSAR for analyzing tectonic and volcanic processes across global settings including Italy, Iceland, Ethiopia, Japan, and Central Andes. His recent publications (2022-2025) demonstrate expertise in magma flow rate analysis for eruption forecasting, caldera resurgence mechanisms, and volcano-tectonic interactions . Key projects include leadership of IAVCEI Caldera Commission (2010-2014) and research on Etna/Campi Flegrei volcanism. Valerio Acocella serves as Field Chief Editor for Frontiers in Earth Science , Editor in Chief for Frontiers in Volcanology , and Associate Editor for multiple journals including Journal of Volcanology and Geothermal Research . His work has resulted in >130 peer-reviewed publications with h-index 36 (ISI/Scopus) and 42 (Google Scholar) as of 2018.

Mohanad Al-BehadiliView profile

Research Fellow

• Operational Research
• Logistics Optimization
• Scheduling Algorithms
• +3 more

Dr. Mohanad Al-Behadili is a Senior Research Associate in the Faculty of Technology at the University of Portsmouth, affiliated with the School of Mathematics & Physics and the Centre for Operational Research & Logistics. His research focuses on operational research, logistics optimization, scheduling algorithms, and unmanned systems. He holds a PhD in Operational Research, awarded in 2018. His work spans optimization methodologies such as swarm intelligence, facility location modeling, and multi-criteria decision analysis. Notable projects include optimizing emergency medical services in Hajj, developing routing strategies for unmanned vehicles in offshore wind farm inspections, and freight consolidation solutions in the Solent region. His research often addresses real-world challenges in transportation, energy, and healthcare sectors. Dr. Al-Behadili has contributed to over 14 peer-reviewed publications, including articles in Expert Systems with Applications , Baghdad Science Journal , and International Journal of Mathematics in Operational Research . His recent work explores the integration of autonomous systems and stochastic scheduling under dynamic conditions. He collaborates with industry partners and academic institutions to advance applications of operational research in complex logistics and transportation systems.

Xiang SongView profile

Senior Lecturer

• Logistics and Transportation
• Supply Chain Management
• Cutting and Packing Problems
• +3 more

Dr. Xiang Song is a Senior Lecturer at the Department of Mathematics, University of Portsmouth, within the Faculty of Technology and School of Mathematics and Physics. He is affiliated with the Centre for Operational Research & Logistics and the Portsmouth AI and Data Science Centre. His research focuses on cutting and packing problems, operational research, logistics optimization, and artificial intelligence applications in supply chain management. He has held EPSRC-funded projects, including the LANCS Initiative in Foundational Operational Research (2008-2011) and contributed to projects like automated algorithm selection for cutting/packing problems (2004-2008). His research interests include unmanned vehicle routing for offshore inspections, maintenance planning for renewable energy infrastructure, stochastic supply chain modeling, and heuristic algorithms for complex optimization problems. He has published extensively in journals like European Journal of Operational Research and Expert Systems with Applications. His work bridges theoretical advancements with real-world applications in logistics, healthcare, and manufacturing. PhD: Jointly awarded by CIMS, Shenyang Institute of Automation (Chinese Academy of Sciences) and Université de Technologie de Troyes (2004) EPSRC Projects: Including strategic maintenance planning for offshore wind farms and blood supply network optimization in disaster scenarios His research outputs span 27 peer-reviewed articles, with recent work addressing carbon cost impacts on supply chains, multi-modal logistics in medical supply networks, and UAV/USV coordination for offshore inspections. He supervises PhD students and collaborates with industry partners on practical operational research challenges.

• Renewable Energy Systems
• Nanomedicine
• Cancer Therapy Modeling
• +4 more

Madjid Soltani is an Adjunct Assistant Professor specializing in interdisciplinary research at the intersection of energy systems, biomedical engineering, and computational modeling. His work focuses on renewable energy storage technologies, nanomedicine, and personalized cancer therapies. He explores innovative solutions for energy transition challenges, including hydrogen production, battery advancements, and exergoeconomic assessments of energy systems. In biomedical applications, his research addresses drug delivery systems, tumor microenvironment modeling, and radiopharmaceutical therapies. His contributions span theoretical frameworks, computational simulations, and experimental validations. Key research interests include energy storage (e.g., compressed air, liquid air), theranostics, computational oncology, and exergoeconomic analysis. He has published extensively on topics such as biomass integration in energy systems, CRISPR-driven biosensors, and microfluidic tumor models. His work often bridges engineering and healthcare, emphasizing sustainability and precision medicine. Despite no explicit institutional affiliation listed, his research collaborations likely involve multidisciplinary teams in academia and industry. Research Themes: Renewable energy systems, nanomedicine, computational modeling, cancer therapy, exergoeconomics. Notable Contributions: Development of spatiotemporal models for radiopharmaceutical transport, optimization of energy storage frameworks, and bio-inspired thermal efficiency solutions.