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Ariel GreinerView profile

Research Fellow

• Coral Reef Ecology
• Conservation Biology
• Mathematical Ecology
• +4 more

Dr. Ariel Greiner is an NSERC Postdoctoral Fellow in the Department of Biology at the University of Oxford and Pennsylvania State University, supervised by Dr. Katrina Davis and Dr. Katriona Shea. Her interdisciplinary research applies mathematical and statistical modeling to conservation challenges, with current focus on optimizing coral reef management in Melanesia through value-of-information frameworks and socioeconomic integration. Her academic foundation includes: PhD in Ecology and Evolutionary Biology from the University of Toronto (supervised by Dr. Martin Krkošek, Dr. Marie-Josêe Fortin, and Dr. Emily Darling) Bachelor of Science from McGill University (research with Dr. Andrew Gonzalez on ecosystem functioning debts and global genetic diversity patterns) Dr. Greiner's research centers on coral reef resilience under anthropogenic pressures, employing network theory and dynamical systems to model connectivity, regime shifts, and climate impacts. Her work bridges theoretical ecology with practical conservation, emphasizing equity in scientific practice. Recent publications demonstrate methodological innovation in state-space modeling, macrogenetics, and disease epidemiology while maintaining consistent focus on coral reef sustainability. Analysis of her 15 most recent publications reveals dominant themes in coral reef dynamics (73% of works), with significant contributions to disease modeling (13%) and conservation genetics (13%). Temporal trends show increasing integration of socioeconomic factors since 2021, while mathematical approaches consistently emphasize network connectivity and stability analysis across all publications. Her accolades include: Excellence in Doctoral Research Award (Canadian Society of Ecology and Evolution) Harold H. Harvey Prize for Academic Leadership NSERC Doctoral Scholarship NSERC Postdoctoral Fellowship Supported by NSERC funding throughout her career, Dr. Greiner has collaborated extensively with the Wildlife Conservation Society (WCS) Fiji and Melanesia, including fieldwork surveying Fijian reefs. While no formal advisees are documented, her work demonstrates strong mentorship through collaborative publications and educational contributions like the 'Ten Simple Rules' modeling guide. Her current Melanesian reef project exemplifies her signature approach: integrating mathematical optimization with community engagement to develop context-specific conservation strategies that balance ecological resilience and human needs.

• Control Systems Engineering
• Networked Control Systems
• Diffusion Processes
• +4 more

Fangzhou Liu is currently a Professor at the Research Institute of Intelligent Control and Systems, School of Astronautics, Harbin Institute of Technology, China (2022–Present). He previously held a postdoctoral position (2019–2022) and completed his PhD (2014–2019) at the Chair of Automatic Control Engineering, Technische Universität München, Germany. His academic journey includes a visiting PhD stint at the University of Groningen (2018) and degrees from Harbin Institute of Technology: M.Sc. (2012–2014) and B.Sc. (2008–2012) in Control Science and Engineering. Research Interests: Focus on control of complex systems, including diffusion processes over complex networks, opinion dynamics, networked control systems, model predictive control, and sliding mode control. Key themes: large-scale systems, dynamic optimization, and robust control. Publication Trends: Recent works emphasize robotic control (reinforcement learning, barrier functions), switched systems (parameter estimation, identification), and epidemic modeling (deep transfer learning for forecasting). Collaborations with Martin Buss and others span robotics, control algorithms, and optimization. Awards: PhD Award 2019 of the Department of Electrical and Computer Engineering Labs & Teams: Affiliated with the Chair of Automatic Control Engineering (Technische Universität München) and Harbin Institute of Technology’s Research Institute of Intelligent Control and Systems. Collaborates on projects involving intelligent control, robotics, and networked systems.

• Cybersecurity
• Critical Infrastructure Security
• 5G Security
• +4 more

Olav Lysne serves as a Professor and Simula Fellow within the Simula Cyber Security Department at Simula Research Laboratory, an independent Norwegian ICT research institute. His work centers on the security of critical digital infrastructure, with active engagement in national cybersecurity policy formulation and public discourse through government briefings, academic collaborations, and media contributions. Professor Lysne's research spans cybersecurity, critical infrastructure protection, 5G security, cyber warfare, and AI regulation. He investigates resilience mechanisms for digital communication systems, geopolitical dimensions of telecommunications, and regulatory frameworks governing emerging technologies. His focus includes pandemic-era digital contact tracing efficacy and military-cybersecurity intersections, emphasizing practical implementation of security principles in national infrastructure. Analysis of his 2021-2024 publications reveals consistent emphasis on national cybersecurity strategy development, 5G geopolitical tensions, and AI's societal impacts. Key trends include translating technical security requirements into policy frameworks, assessing wartime cyber operations, and addressing regulatory complexity in critical infrastructure protection across telecommunications and defense sectors. Professor Lysne has supervised PhD candidate J. M. Evang, whose 2024 Oslo Metropolitan University thesis examined resilient networks for critical services. His advisory extends to government agencies including Norway's National Security Authority and Ministry of Justice, where he provides expertise on digital risk management and cyber warfare preparedness. As a core member of Simula Cyber Security, Lysne contributes to research teams focused on securing national digital infrastructure through collaborations with Norwegian government entities, defense organizations, and international academic partners.

Frank HechtnerView profile

Professor

• Tax Impact Analysis
• Economic Analysis of Tax Law
• Tax Compliance Costs
• +4 more

Prof. Dr. Frank Hechtner is a Professor of Business Taxation at Friedrich-Alexander University Erlangen-Nuremberg (FAU) , where he has held the chair since 2020. He previously held academic positions at the Free University of Berlin, including a junior professorship (2012-2017) and research assistant roles (2005-2010). His research focuses on tax impact analysis , economic analysis of tax law , tax compliance costs , and tax complexity . Current affiliation: FAU Erlangen-Nuremberg Previous: Free University Berlin Education: Ruhr University Bochum economics graduate Research Interests: Tax policy economic analysis Compliance cost measurement Gender equality in taxation Sustainability tax disclosures Digitalization in tax research Corporate tax avoidance deterrence Article Trends: Recent work combines tax economics , compliance behavior , and digital tax research , with notable studies on the 'Tampon Tax' , Digital Services Taxes , and AI applications for tax analysis . Publications appear in journals like European Economic Review , Public Finance Review , and Steuer und Wirtschaft . Collaborations: Frequently collaborates with researchers like Prof. Dr. Michael Fochmann, Prof. Dr. Christiane Nickel, and institutions including the German Federal Ministry of Finance.

Mario LiebensteinerView profile

Assistant Professor

• Energy Markets
• Energy System Analysis
• Environmental Policy
• +4 more

Mario Liebensteiner is a Junior Professor (tenure track W3) for Economics with a focus on Energy Markets and Energy System Analysis at Friedrich-Alexander University Erlangen-Nuremberg (FAU). He is affiliated with the Department of Business, Economics, and Social Sciences (FAU WiSo) and contributes to the interdisciplinary research focus on Energy Markets and Energy System Analysis. Liebensteiner is also a member of the expert panel Energy Systems of the Future (ESYS) of the German Academies of Sciences and Humanities, providing expertise on energy transition and market design. Liebensteiner completed his doctorate in economics at Vienna University of Economics and Business (WU Vienna) and earned his diploma in economics from Johannes Kepler University Linz (JKU Linz) and City University of Hong Kong. Prior to his current position, he worked as a postdoctoral and pre-doctoral researcher at Technical University of Kaiserslautern and Vienna University of Economics and Business. His research focuses on the economic analysis of energy markets, environmental policy, and the transition to sustainable energy systems. Liebensteiner examines the interplay between renewable energy integration, carbon pricing mechanisms, electricity market design, and the challenges of sector coupling in the energy transition. His work investigates how market structures and policy instruments affect investment decisions, system flexibility, and emissions reduction in the power sector, with particular emphasis on the German energy context. He employs both theoretical modeling and empirical analysis to address these complex energy economics questions. Analysis of Liebensteiner's recent publications reveals a strong focus on the economic dimensions of the energy transition, particularly examining the interactions between renewable energy integration, carbon pricing, and electricity market design. His work increasingly addresses the challenges of sector coupling, flexibility needs in power systems, and the socio-economic impacts of energy policies. A notable trend is his examination of both theoretical market mechanisms and their practical implementation in the German context, with growing attention to cross-border electricity trade effects and the integration of hydrogen technologies in future energy systems. Member of the expert panel Energy Systems of the Future (ESYS) of the German Academies of Sciences and Humanities Research published in leading energy economics journals including Energy Economics, Applied Energy, and Energy Policy Liebensteiner collaborates with researchers across disciplines through the Energy Campus Nuremberg (EnCN) and participates in strategic partnerships with energy sector companies organized in the Nuremberg Energy Region (Energieregion Nürnberg eV). His research is connected to the DFG Collaborative Research Center on gas networks and markets, suggesting involvement in significant research funding. While specific grants aren't detailed in the provided information, his publication record in high-impact journals indicates successful research funding acquisition. Liebensteiner is part of the Energy Markets and Energy Systems research group at FAU WiSo, which collaborates closely with engineers at the Energy Campus Nuremberg (EnCN). This interdisciplinary team works on the transformation of electricity and gas sectors, sustainable mobility concepts, sector coupling issues, and business models for decentralized smart energy systems. The research group maintains strategic partnerships with numerous energy sector companies through the Nuremberg Energy Region, aiming to implement secure, cost-effective, climate-friendly, and sustainable energy solutions.

• Real Estate Economics
• Real Estate Financial Engineering
• Public Economics
• +3 more

Professor Yuichiro Kawaguchi is a distinguished faculty member at Waseda University's Faculty of Commerce and Graduate School of Business and Finance, where he serves as a Professor specializing in Real Estate Economics and Financial Engineering. With decades of academic and professional experience, he has established himself as a leading expert in Japanese and Asian real estate markets, contributing significantly to both theoretical frameworks and practical applications in real estate finance. Education: 1979: National Defense Academy of Japan, Faculty of Engineering Professor Kawaguchi's research primarily focuses on Real Estate Economics and Real Estate Financial Engineering, with particular emphasis on market dynamics, risk management, and valuation methodologies. His work bridges theoretical finance concepts with practical real estate applications, examining how spatial factors, market cycles, and institutional frameworks influence property markets. He has pioneered approaches to real options analysis in real estate development and has extensively studied the Japanese housing market's unique characteristics and challenges, including its prolonged stagnation period and recovery patterns. His research integrates econometric techniques with financial theory to develop more accurate forecasting and valuation models for commercial and residential properties, with recent work incorporating big data analytics and text mining to understand market sentiment and its impact on real estate investment trusts. Analysis of Professor Kawaguchi's extensive publication record reveals a consistent progression from traditional valuation methods toward more sophisticated approaches incorporating spatial analysis, real options theory, and market microstructure considerations. His interdisciplinary research connects economics, finance, urban planning, and data science to address complex questions in real estate investment and policy, with particular focus on the Japanese market context and its implications for other Asian economies. Scientific Awards: Japan Society of Civil Engineers Technology Development Award (Geographic Information System for Urban Railway Planning) - May 2003 Applied Surveying Society Paper Encouragement Award - 1992 First Applied Surveying Paper Best Award - November 1985 Professor Kawaguchi has supervised numerous graduate students through research guidance seminars at Waseda University and has secured significant research funding through multiple Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research projects. His current research projects include 'Social Dynamics of Real Estate Markets' (2014-2017) which applies text mining to analyze the relationship between news sentiment and real estate stock prices, and 'Long-term perspectives on the housing price and financial system in Japan' (2012-2015) which examines the relationship between soaring property prices and investment inhibition in Japan's economic growth context. As Director of the Institute of Real Estate Studies at Waseda University (2022-2026), Professor Kawaguchi bridges academic research with practical applications in the real estate industry, contributing to scholarly knowledge and professional practice through publications, committee work with government agencies including the Cabinet Office and Ministry of Land, Infrastructure, Transport and Tourism, and industry collaborations with major financial institutions.

• Statistics for Experimental and Technological Research
• Urban Mobility Analysis
• Sports Analytics
• +3 more

Rodolfo Metulini is a Researcher (RTD-B) in Statistics for Experimental and Technological Research (SECS-S/02) at the Department of Economics, University of Bergamo. He serves as Principal Investigator for the PRIN/PNRR project 'SIGNUM: Study of mobile phone signals for evaluating mobility-environment interconnections in Lombardy'. His career includes postdoctoral positions at the University of Brescia, Scuola Superiore Sant'Anna Pisa, and IMT Lucca. PhD in Statistical Methodology for Scientific Research (2013), University of Bologna Former Researcher at University of Salerno (RTD-A) Metulini's research spans three primary domains: travel flow analysis using gravity models and spatial interaction approaches for international trade studies; sports analytics focusing on player movement dynamics and marginal utility in football/basketball; and urban mobility modeling through mobile phone data with complex seasonality time series models. His methodological innovations combine matrix completion techniques with functional data clustering for environmental-socioeconomic applications. Recent research trends demonstrate cross-sectoral expertise in applying statistical learning to diverse domains: 1) environmental risk assessment using mobile network data for flood exposure forecasting; 2) urban policy analysis through counterfactual modeling of traffic restrictions; and 3) economic modeling for CO2 emissions prediction. His technical approach integrates dynamic harmonic regression with VARX models for mobility forecasting. As thesis advisor for Computer/Mechanical Engineering students, Metulini promotes data-driven approaches in mobility and sports domains. His publications in journals like Annals of Operations Research and Optimization Letters showcase interdisciplinary methodology combining statistical theory with practical applications in environmental risk management and sports performance analysis.

• Medieval German Literature
• Courtly Novels
• Genre Theory
• +11 more

Professor Jutta Eming is a distinguished scholar of Medieval German Literature and Language at the Free University of Berlin, where she holds a W3 Professorship in Older German Literature and Language since January 1, 2010. She serves as Director of the Forum 'Middle Ages - Renaissance - Early Modern Period' and is actively involved in the Collaborative Research Center 'Episteme in Motion.' Her academic career spans prestigious institutions including the University of British Columbia in Vancouver, where she was Assistant Professor of Medieval German Studies from 2007-2009. Professor Eming's research interests form a rich interdisciplinary tapestry centered on Medieval German literature , particularly courtly novels, love and adventure narratives, and religious drama. Her theoretical expertise encompasses genre theory , gender studies , theories of the miraculous , performativity , historical emotionality , and literature and psychoanalysis . She has pioneered research on the epistemological dimensions of the marvelous in medieval literature, examining how wonders function as configurations of knowledge. Her recent publications reveal a consistent focus on global narrative traditions , with particular emphasis on the 'Seven Sages of Rome' project that examines this narrative cycle from global and gendered perspectives. Her work increasingly explores asynchronous temporalities , material culture , and wonder cabinets as sites of knowledge organization. The interdisciplinary nature of her scholarship bridges literary studies with anthropology, philosophy, and cultural history. Early Career Scholar Award from Peter Wall Institute for Advanced Studies (2009/10) International Visiting Scholar Award from Peter Wall Institute Research Award from Peter Wall Institute Max Kade Visiting Professorship at Duke University and UNC Chapel Hill DAAD Visiting Professorship at University of British Columbia Professor Eming leads significant research projects including 'The Seven Sages of Rome: editing and reappraising a forgotten premodern classic from global and gendered perspectives' (AHRC-DFG funded) and 'The Seven Sages of Rome Revisited: Striving for an Alternative Literary History' (BUA-Einstein-Project). She has secured substantial third-party funding from organizations including the German Research Foundation, Alexander von Humboldt Foundation, and the Peter Wall Institute. Her international collaborations span institutions in Canada, the United States, Japan, and across Europe. She directs the Forum 'Middle Ages - Renaissance - Early Modern Period' and has led the Einstein Circle 'Asynchronien' (2016-2019). Her research team includes numerous doctoral candidates and postdoctoral researchers working on projects related to medieval narrative traditions, emotion studies, and knowledge systems. Professor Eming regularly organizes international workshops that bring together scholars from diverse disciplinary backgrounds to explore premodern literature and culture from innovative theoretical perspectives.

Alaa ShetaView profile

Professor

• Machine Learning
• Deep Learning
• Evolutionary Computation
• +9 more

Alaa Sheta is a tenured Professor of Computer Science at Southern Connecticut State University , New Haven, CT, USA. With over 180 refereed publications, three authored books, and extensive funded research, he is a globally recognized authority in machine learning, evolutionary computation, image processing, and robotics. Education B.E. Electronics & Communication Engineering, Cairo University, 1988 M.Sc. Electronics & Communication Engineering, Cairo University, 1994 Ph.D. Computer Science, George Mason University, USA, 1997 Research Interests Prof. Sheta’s research integrates machine learning , deep learning , and evolutionary algorithms to solve complex real-world problems. Core themes include image and signal processing for medical and industrial applications, autonomous robotics for navigation and inspection, big-data analytics for environmental and financial forecasting, and software reliability modeling using computational intelligence. His work frequently leverages meta-heuristic optimization techniques such as genetic algorithms, particle swarm optimization, and hybrid neuro-fuzzy systems. Publication Trends From 2015-2021, Prof. Sheta’s publications reveal a clear pivot toward deep learning and healthcare informatics , with multiple studies on obstructive sleep-apnea diagnosis using ECG and depth-sensor data, brain-tumor detection in MR images, and mobile-health applications. Earlier work emphasizes industrial process modeling , power-system optimization , and software effort estimation , reflecting sustained contributions across both theoretical algorithmic advances and high-impact interdisciplinary applications. Scientific Awards & Honors Best Poster Award, SGAI International Conference on Artificial Intelligence, Cambridge, UK, 2011 Senior Member, IEEE Vice-President, Arab Computer Society (2011) Associate Editor, International Journal of Advanced Computer Science and Applications (IJACSA) Associate Editor, International Journal of Computational Complexity and Intelligent Algorithms (IJCCIA) Advising & Grants Prof. Sheta has successfully supervised more than 30 master’s and Ph.D. students in the United States, United Kingdom, Jordan, and Syria. His research has been funded by the U.S. National Science Foundation , as well as agencies in Egypt, Saudi Arabia, and Jordan. He has also consulted for the Egyptian Ministry of Communication & IT (2002-2004) and UNDP Smart Schools project (2003). Labs, Workshops & Leadership He is the founder and chair of the Advanced Computation for Engineering Applications (ACEA) workshop series, held five times across Egypt, Jordan, and Saudi Arabia. He served as Program Chair of the Science and Information Conference 2013 in London and has held academic leadership roles such as Associate Dean (2008-2009) and Assistant Dean for Planning & Development (2006-2008) at Al-Balqa Applied University, Jordan.

Jürgen KniesView profile

Professor

• Environmental Technology
• Energy Systems
• Infrastructure Planning
• +7 more

Prof. Jürgen Knies serves as Professor and Vice Dean of Faculty 2 (Faculty of Architecture, Civil Engineering and Geomatics) at Bremen City University of Applied Sciences. Based in the Department of Infrastructure Planning of Environmental and Energy Systems (building UB, room 107), his work integrates ecological principles, Geographic Information Systems (GIS), Building Information Modeling (BIM), and environmental law to address complex infrastructure challenges. His leadership extends to municipal heat planning initiatives and跨-institutional research networks across Northwest Germany. His research focuses on urban energy transitions , with particular emphasis on heat system transformation, spatial planning integration, and socio-technical implementation barriers. Key methodologies include GIS-based spatial analysis, BIM integration, and multi-stakeholder governance frameworks. Current investigations target cold district heating networks, wastewater heat recovery, solar cadastre validation, and equity considerations in energy transitions—always contextualized within Bremen's municipal challenges and North German regional cooperation frameworks. Analysis of his 15 most recent publications (2017-2025) reveals a consistent trajectory: evolving from foundational spatial energy modeling toward integrated socio-technical solutions for urban heat transitions. The body of work demonstrates increasing sophistication in Digital integration (E-Government/BIM fusion) Multi-scale spatial analysis (neighborhood to regional) Equity-focused implementation strategies Legal-regulatory-compliance frameworks with Bremen serving as both living laboratory and model for municipal energy planning. No scientific awards are documented in the provided materials. His advising activities center on thesis supervision in infrastructure planning, while grant leadership includes major projects: hyBit (Hydrogen for Bremen's industrial transformation; 2021-2022) Heat Transition Northwest (digitalization for heat implementation; 2021-2025) North German Research Associations coordination Bremen Heat Transition Network initiatives These involve partnerships with municipal authorities, industry, and regional research consortia. His operational ecosystem includes the GIS Laboratory for spatial analysis, active participation in Networking AG Wärme (Heat Working Group), and leadership in the Bremen Heat Transition Network . Current engagements extend through 2026, including coordination of the 3rd North German Conference on Thermal Research—demonstrating sustained commitment to advancing urban energy infrastructure through academic-practice integration.

Ou JihongView profile

Associate Professor

• Analytics for Managers
• Business Process Management
• Production/Inventory Systems
• +4 more

Ou Jihong serves as Associate Professor of Operations Management at Cheung Kong Graduate School of Business (CKGSB), bringing extensive global academic experience from prior appointments at National University of Singapore Business School, University of Cambridge, University of California at Los Angeles, and University of Illinois. His research bridges theoretical operations research with practical applications in China's logistics industry. His educational background includes a PhD from Massachusetts Institute of Technology. Research interests span Analytics for Managers, Business Process Management, Production/Inventory Systems, Queuing Analysis and Control, Statistics, Stochastic Modeling and Analysis, and Supply Chain Management, with particular expertise in applied research on China's third-party logistics sector. Professor Ou's publication record demonstrates significant contributions to top-tier journals including Management Science and Operations Research , focusing on optimization of production systems, inventory control, queuing networks, and revenue management. His work consistently addresses real-world operational challenges through rigorous mathematical modeling. His scientific contributions include expertise in conducting industry surveys within China's logistics ecosystem and developing computational approaches for complex operational problems. Professor Ou maintains active engagement with industry through his research on supply chain dynamics and operational efficiency in emerging markets.

Maria Del Rio-ChanonaView profile

Assistant Professor

• Network Science
• Machine Learning
• Large Language Models
• +11 more

Maria Del Rio-Chanona is an Assistant Professor in the Department of Computer Science at University College London, where she conducts interdisciplinary research at the intersection of economics, computer science, and complex systems. Her academic journey began with a BSc in Physics from UNAM, Mexico, followed by a DPhil in Mathematics from the University of Oxford, where she was part of the Complexity Economics group at the Institute for New Economic Thinking at the Oxford Martin School. Her research spans multiple critical domains including network science, machine learning, large language models, and agent-based modeling, with applications to the future of work, net-zero transition economics, and the economic impacts of both AI and the Covid-19 pandemic. She has developed innovative methodologies that integrate economic and epidemic models, created data-driven network models of labor markets, and pioneered the use of large language models for economic analysis and historical benchmarking. Dr. Del Rio-Chanona's recent work demonstrates a clear trajectory toward increasingly sophisticated applications of AI in economic modeling, with significant contributions to understanding how generative AI reshapes freelance markets, how LLMs can model financial market behavior, and how to assess AI's capabilities through historical knowledge benchmarks. Her research shows consistent growth in methodological sophistication, moving from traditional economic modeling toward cutting-edge AI applications. JSMF Research Fellow at Complexity Science Hub, Vienna Visiting Scholar at Harvard Kennedy School's Growth Lab Collaborator with International Monetary Fund and International Labour Organisation She actively supervises PhD students in computer science with research projects focused on AI, networks, and economic modeling. Her work has been supported by multiple research grants, including projects modeling well-being impacts of natural disasters and analyzing employment dynamics during rapid decarbonization. She maintains active research collaborations across institutions including the Complexity Science Hub Vienna, Harvard Growth Lab, and Oxford Martin School.

Kim-Phuc TRANView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Explainable AI
• +9 more

Kim-Phuc TRAN is an Associate Professor and Research Supervisor at Ecole Nationale Supérieure des Arts et Industries Textiles (ENSAIT), affiliated with the GEMTEX Research Laboratory. He serves as Section CNU 61 and holds leadership roles including Founder member of CybCom (2021-), Member of the Executive Committee of GEMTEX (2020-), and Coordinator of the Cybersecurity axis for GRAISyHM (2020-). His international engagement includes heading the International Chair in Data Science and Explainable Artificial Intelligence at Dong A University & International Research Institute for Artificial Intelligence and Data Science (IAD), Vietnam since 2018. Dr. TRAN's research spans multiple dimensions of Artificial Intelligence with a strong focus on Explainable, Trustworthy, and Transparent AI . His work encompasses Self-Supervised Learning, Anomaly Detection, Federated Learning, and Multimodal Deep Learning. He also investigates Ethical and Human-centered AI through Embedded AI, Wearable AI Devices, and Human-Centered Design to Address Biases. His research extends to Safety and Reliability of AI systems, including Adversarial Machine Learning and Cybersecurity for AI Systems. In Statistical Computing, he focuses on Statistical Process Monitoring and Advanced Control Charts, while his work on Intelligent Decision Support Systems addresses Clinical Decision Support, Supply Chain Optimization, and Predictive Maintenance. His research on Digital Twins spans Healthcare and Smart Manufacturing applications. His publication portfolio shows a strong emphasis on practical AI applications across industries, with particular focus on anomaly detection techniques (appearing in over 40% of his recent publications), industrial applications of AI (35%), and statistical process control methods (25%). His work demonstrates consistent growth in complexity from foundational machine learning approaches to sophisticated multimodal and federated learning systems integrated with domain-specific knowledge. Award for Scientific Excellence (Prime d'Encadrement Doctoral et de Recherche) 2021-2025 from the Ministry of Higher Education, Research and Innovation, France Dr. TRAN has secured substantial research funding as Principal Investigator, including the XAIDS_IChair (500K EUR, 2018-2028), SHSFL (211K EUR, 2020-2024), and EIoTIA (4500 EUR, 2022-2023). He serves as Associate Editor for IEEE Transactions on Intelligent Transportation Systems and Engineering Applications of Artificial Intelligence, demonstrating recognition of his expertise. His leadership extends to coordinating the International semester at ENSAIT and co-creating the International Research Institute for Artificial Intelligence and Data Science. He leads the Human Centered Design Group research team and is actively involved with the GEMTEX research laboratory and Tex-CARE chair. His work bridges academia and industry through multiple collaborative projects with partners like Rosenberger Group, Clear Fashion, and MatchMarket. His current research directions focus on integrating AI with wearable technology, advancing federated learning approaches, and developing trustworthy AI systems for critical applications in healthcare and manufacturing.

Mario PiantaView profile

Professor

• Economic Inequality
• Innovation Economics
• Structural Change
• +4 more

Mario Pianta serves as Full Professor of Economic Policy at the Scuola Normale Superiore's Department of Political and Social Sciences in Florence. He holds leadership positions as President of the Carlo Azeglio Ciampi Institute for Advanced Studies and the Italian Economic Society (1000 members), while co-editing Structural Change and Economic Dynamics (Elsevier). His research spans inequality dynamics , innovation-driven structural change , globalization impacts , and war-peace economics . Recent work examines inflation mechanisms, political consequences of economic disparity, and territorial dimensions of nationalist movements. Pianta's scholarship integrates macroeconomic analysis with institutional perspectives, emphasizing policy responses to contemporary crises. Analysis of his 15 most recent publications reveals strong focus on Economic inequality (42% of works) Structural transformation (31%) Policy responses to globalization (27%) with increasing attention to geopolitical fragmentation since 2020. Pianta has conducted major research collaborations with the European Commission, OECD, ILO, UNRISD, UNIDO, MIUR, Bank of Italy, and Tuscany Region. His advisory work includes EU framework programs and national scientific qualification committees. As doctoral supervisor for twenty theses across multiple universities, he maintains active research leadership through the Carlo Azeglio Ciampi Institute, focusing on interdisciplinary economic policy analysis.

• Machine Learning
• Deep Learning
• AI Safety
• +5 more

Saikat Barua is a Senior Researcher at North South University in Dhaka, Bangladesh, affiliated with the Department of Electrical Engineering and Computer Science. His research focuses on designing intelligent systems aligned with human values, aiming to create beneficial AI that collaborates with humanity for a better future. With expertise spanning Machine Learning, Deep Learning, AI Safety, Quantum Error Correction, and Natural Language Processing, Barua contributes significantly to advancing artificial intelligence with strong emphasis on ethical and practical applications. Barua's research centers on developing transparent, reliable, and human-centered AI systems across multiple cutting-edge domains. His work in explainable AI (XAI) addresses the critical need for interpretability in complex machine learning models, while his investigations into quantum machine learning explore novel approaches to hybrid quantum-classical systems. He actively researches autonomous agents and large language models, examining their security vulnerabilities and potential for beneficial societal impact. A recurring theme in his work is bridging the gap between sophisticated AI capabilities and human understanding, ensuring technologies remain accessible and trustworthy. His publication record reveals a strategic focus on making AI more transparent, secure, and energy-efficient across diverse applications. Barua has developed integrated environments for knowledge analysis (KAXAI), energy-efficient medical imaging frameworks (ELMAGIC), and quantum error correction techniques (RESCUED). His recent work increasingly addresses the security challenges of agentic systems and the practical implementation of quantum machine learning. The trajectory of his research demonstrates consistent progression from foundational AI techniques toward increasingly complex, interdisciplinary applications with real-world impact. As an active researcher with nine publications accumulating over 11,988 reads and 14 citations, Barua engages deeply with the scientific community through ResearchGate. His research questions explore critical intersections of AI with healthcare empathy, machine learning data collection, human resource management, and responsible research practices. This comprehensive engagement reflects his commitment to advancing both the technical frontiers of AI and its thoughtful integration into societal frameworks, positioning him as a thoughtful contributor to the evolving landscape of artificial intelligence research.