Costanza Argiroffi is a researcher at the University of Palermo within the Department of Physics and Chemistry - Emilio Segrè. Her office hours are scheduled for multiple programs including Physics, Natural and Environmental Sciences, and Optics and Optometry. Stellar Evolution (Physics) Instrumentation for Optics and Astronomy (Optics and Optometry) Accretion processes in young stars Her research focuses on high-energy astrophysical phenomena, particularly X-ray and UV emission from young stellar objects , magnetohydrodynamic modeling of accretion shocks , and multi-wavelength diagnostics of stellar activity . Publications span topics from stellar flares to laboratory astrophysics and accretion dynamics . Costanza Argiroffi's recent publications demonstrate strong expertise in: X-ray astronomy (XMM-Newton, Chandra, NuSTAR) Magnetohydrodynamic simulations Young stellar object variability Accretion processes in classical T Tauri stars Binary star magnetospheres Planetary atmosphere irradiation She has advised multiple theses and participated in research projects involving international collaborations with X-ray observatories.
Belen Martin-Barragan is a Reader in Management Science at the University of Edinburgh Business School , with a focus on the Department of Management Science and Business Economics . Her research bridges Machine Learning and Mathematical Programming , emphasizing Explainable Artificial Intelligence (XAI) and applications in Operational Research , including classification , clustering , inventory management , and routing optimization . Her work includes developing interpretable machine learning models for credit scoring, healthcare data, and sustainable logistics. She has led EPSRC-funded projects on Optimisation Models for Interpretable Analytics and contributed to journals like European Journal of Operational Research , Risk Analysis , and Computers and Operations Research . Key methodologies involve Mixed-Integer Linear Programming , Support Vector Machines , and stochastic dynamic programming . Her research fingerprint spans Machine Learning (97%), Mathematical Programming (75%), and Optimization Algorithms (20%). She has been a Research Champion and Deputy Director of Research (Ethics and Integrity) at the Business School, with affiliations to the Credit Research Centre and Edinburgh Strategic Resilience Initiative .
Prof. Dr. Bryan T. Adey is a full Professor at the Swiss Federal Institute of Technology in Zurich (ETHZ) within the Department of Civil, Environmental and Geomatic Engineering . He directs the Institute for Construction and Infrastructure Management and leads the Masters Spatial Planning and Infrastructure Systems program. His research focuses on improving infrastructure management through process standardization, automation, and optimization for systems like road networks, rail networks, and water distribution networks. Specializes in infrastructure resilience and post-disaster recovery Active participant in European research projects (e.g., Destination Rail, Foresee) Editorial Board member of Journal of Infrastructure Asset Management and Journal of Infrastructure Systems His recent publications emphasize: Ensemble learning for water pipe failure prediction Simulation-based optimization for flood recovery Resilience quantification frameworks Cost-benefit analysis for urban mobility transitions He contributes to global infrastructure standards through: Leadership in VSS committee 4.3 Consultancy for major infrastructure owners Active reviewing for 20+ international journals
Robert M. Curry is an Assistant Professor in the Department of Industrial Engineering at the University of Arkansas (since August 2023). Previously, he served as an Assistant Professor in the Mathematics Department at the United States Naval Academy (2018-2023). His work focuses on large-scale network optimization with applications in defense logistics , sensor networks , and cyber-physical systems . Education Ph.D. in Industrial Engineering (Clemson University, 2018) M.S. in Industrial & Systems Engineering (University of Florida, 2014) B.S. in Industrial Engineering (University of Arkansas, 2013) Curry's research develops mixed-integer programming models and heuristic algorithms for solving complex network optimization problems in contested environments. His applications span military strategy , energy infrastructure , telecom networks , and healthcare logistics . Publications appear in journals like IISE Transactions , Networks , and Naval Research Logistics . Grants include funding from the Office of Naval Research for projects such as "Coordinated Navy and Marine Corps Strategy in the South China Sea" ($220,771.53) and "Dynamic Minimum-cost Flow Problems" ($40,000).
Myra B. Cohen is a Professor and the Lanh and Oanh Nguyen Chair in Software Engineering within the Department of Computer Science at Iowa State University's College of Engineering. She previously served as a Susan J. Rosowski Professor at the University of Nebraska-Lincoln and leads the LaVA-OPs Laboratory for Variability-Aware Assurance and Testing of Organic Programs. Her research spans software testing of highly-configurable systems, search-based software engineering, combinatorial design applications, and synergies between software engineering and synthetic biology. She investigates assurance techniques for self-adaptive systems through bio-inspired algorithms and examines software testing representations of natural processes like chemical reaction networks. Her 15 most recent publications demonstrate strong focus on cyber-physical systems (particularly drone safety), biological computing, and configuration-aware testing. These works reveal interdisciplinary trends combining software engineering with synthetic biology, emphasizing real-world applications in autonomous systems and computational biology. NSF CAREER Award AFOSR Young Investigator Award ACM Distinguished Scientist Best Student Paper Award at SPLC 2019 ACM Distinguished Paper Award at ASE 2020 Best Paper Award at GI@ICSE 2021 Professor Cohen advises PhD students Salil Purandare, Md Obaidul Kabir, and Michael Gerten, with research focusing on cyber-physical systems and biological software applications. She leads multiple significant projects including the DOE-funded Dependable, Explainable, Reusable, AI-Driven Computational Biology initiative and blockchain fault tolerance research. Her LaVA-OPs laboratory develops assurance techniques for highly-configurable and self-adaptive programs through bio-inspired algorithms.
Dr. David Willems serves as a Lecturer at the University of Koblenz, holding dual appointments within the Faculty of Mathematics and Natural Sciences: specifically at the Mathematical Institute and the Physics Department. He maintains a significant external affiliation with the Institute for Preventive Medicine of the German Armed Forces, where he is associated with Department A5 (Medical-Technical Ergonomics and Systems Informatics) in Koblenz. His research program centers on advanced optimization theory with three core pillars: Combinatorial Optimization : Developing algorithmic solutions for discrete decision problems Network Flow Problems : Analyzing optimal resource distribution across complex networks Multi-Criteria Optimization : Creating approximation frameworks and representative systems for multi-objective decision scenarios Current research initiatives include proj-multikosi, proj-tmoco, and proj-mmdf, which integrate theoretical optimization with practical applications in medical-technical systems and military preventive medicine. His work bridges mathematical theory with real-world systems informatics challenges.
Ameer Tamoor Khan serves as a Postdoctoral Researcher (Research Fellow) in the Section for Crop Sciences within the Department of Plant and Environmental Sciences at the University of Copenhagen's Faculty of Science. Based at the Taastrup campus (Højbakkegård Allé 13, 2630 Taastrup), his work bridges agricultural science and computational intelligence with direct contact via atk@plen.ku.dk and +4535327865. His research centers on AI-driven solutions for agricultural challenges, specializing in computer vision applications for precision farming. Key focus areas include pest and weed detection using YOLO architectures (v8/v11), leaf phenotyping analysis, neural network-based supply chain optimization, and evolutionary computation for model-free systems. This interdisciplinary work integrates deep learning, operational research, and agricultural engineering to enhance food security and farming efficiency through real-time computational approaches. Analysis of his 2025 publications reveals a dominant trend in applying computer vision to agricultural robotics, particularly in multi-crop monitoring systems. His work consistently connects neural dynamics with practical farming applications, spanning from cotton weed management to portfolio risk optimization, demonstrating cross-domain versatility in computational intelligence. No scientific awards were documented in the source material. Information regarding student supervision or research grant acquisition was not provided in the available records. While specific laboratory affiliations weren't detailed, his research output indicates active collaboration within computational agriculture networks, particularly with co-authors Jensen and Mirjalili across multiple institutions.
Sergio Segura is a Full Professor of Software Engineering at the University of Seville (Spain), where he leads the research line on Software Engineering within the SCORE Unit of Excellence. He is a member of the Applied Software Engineering research group and affiliated with the SCORE Lab at the I3US Institute. His research focuses on applied and tool-oriented software engineering, with particular emphasis on improving software quality and developers' productivity through automation. He actively collaborates with industry through research contracts and technical training initiatives. Segura's research interests include software testing, AI-driven software engineering, trustworthy AI, and software engineering education. His recent work shows a strong trend toward testing RESTful APIs, safety and fairness testing of large language models, and mutation testing in practice. His publications demonstrate a consistent focus on practical, tool-oriented solutions to real-world software engineering challenges. Docentia Teaching Accreditation - Excellence Mention (2025) Best Application Paper Award at AITest 2022 His student Alberto Martín won the SCIE/BBVA National Young Researcher Award 2023 Segura has supervised numerous PhD students, many of whom have achieved significant recognition including First and Second Place Winners in ACM SRC Grand Finals. He leads the TRUST4AI project focused on trustable AI-driven internet search and maintains close collaboration with industry partners such as Schneider Electric through industrial PhD programs.
Xavier Devroey is an Assistant Professor of Software Engineering at the University of Namur in Belgium. He co-leads the SNAIL Team with Benoît Vanderose, focusing on innovative approaches to software testing and automation. His work bridges academic research with practical applications in the software engineering community. His educational background includes a Ph.D. and Master's in Computer Science from the University of Namur, plus a Bachelor's in Analyst Programming from Haute Ecole de Bruxelles, Belgium. This comprehensive academic training informs his research and teaching approach. Devroey's research interests center on Software Testing , with particular emphasis on Search-Based Software Engineering and Software Variability . His specific focus areas include: Search-Based Testing and Fuzzing Model-Based Testing Mutation Testing Variability Modeling Software Product Line Testing Test suite augmentation DevOps integration These interests reflect his commitment to advancing automated approaches for test case design, generation, selection, and prioritization. His recent publication portfolio (2019-2025) demonstrates consistent contributions to software testing research, with particular focus on crash reproduction, API testing, and innovative approaches to test automation. The articles reveal a strong emphasis on practical applications of search-based techniques across various testing domains. Devroey maintains active engagement with the academic community through conference participation, having served on program committees for major software engineering conferences including ASE, ICSE, ISSTA, and ICST across multiple years (2019-2025). He also contributes to educational aspects of software engineering, with publications examining testing education approaches and tools for programming exercise assessment. His personal website (xdevroey.be) and GitHub profile demonstrate his commitment to open academic practices and community engagement.
Ansgar Zerfass is Professor and Chair in Strategic Communication at the Institute of Communication and Media Studies at the University of Leipzig, Germany, and Professor in Communication and Leadership at BI Norwegian Business School in Oslo, Norway. With a distinguished career spanning academic and professional communication fields, he has established himself as a leading scholar in strategic communication, corporate communication, and public relations. His work bridges theory and practice through extensive research collaborations and leadership roles in major international communication studies. Dr. Zerfass earned his Dipl.-Kfm. (equivalent to MBA) in Business Administration from the University of Erlangen-Nuremberg in 1990, followed by a Dr. rer. pol. (PhD) in Business Administration summa cum laude in 1995. He completed his Habilitation (second doctorate) in Communication Science at the same university in 2005. His academic journey includes significant industry experience, having worked for 10 years in corporate communications and political consulting, including an executive position at MFG Baden-Württemberg. Zerfass's research focuses on strategic communication, corporate communication, digital transformation, communication evaluation, and communication management. His work examines how organizations can optimize their communication functions to create value, navigate digital transformation, and maintain ethical standards in an increasingly complex media environment. He has pioneered research on communication business models, communication maturity, and the role of communication in agile organizations. His extensive publication record reveals a consistent focus on bridging theory and practice in communication management. His recent work explores the impact of digitalization and AI on communication departments, stress resilience among communication professionals, and the evolving business models for communication functions. His research demonstrates increasing attention to digital transformation challenges while maintaining core interests in communication evaluation, strategic alignment, and organizational integration of communication functions. Multiple Top Paper Awards at EUPRERA Annual Conferences (2012-2016) Koichi Yamamura International Strategic Communication Award (2014, 2016) Pathfinder Award from the Institute for Public Relations (2014) Impact Award from the Journal of Communication Management (2016) Albert-Oeckl-Prize from the German Public Relations Society (1995) PhD Award from the University of Erlangen-Nuremberg (1995) As Editor of the International Journal of Strategic Communication and director of the European Communication Monitor (a 15+ year study spanning 40+ countries), Zerfass has significantly shaped communication research methodology and practice. He serves as Academic Advisor for the Corporate Communication Cluster Vienna and Plank Scholar at the Plank Center for Leadership in Public Relations. His leadership extends to founding the Academic Society for Corporate Management and Communication, which connects over 35 global companies with academic institutions for knowledge transfer and research funding. Zerfass leads several major research initiatives including the European Communication Monitor (since 2007), the Asia-Pacific Communication Monitor, and the multi-year research program Value Creating Communication. His work with these initiatives has established longitudinal datasets that track global trends in strategic communication practices, providing invaluable insights into the evolution of the field.
Gustavo Carvajal serves as an International Expert Partner at Lansberg Gersick Advisors (LGA) and holds a professorial position in the executive-education program "Governance & Continuity in Family Business" at Universidad ICESI in Cali, Colombia. With extensive experience spanning over 30 years in family enterprises across Latin America, he specializes in complex corporate governance matters and board development for family businesses. His academic background includes a BA in Economics and Political Science from Adelphi University and an MBA from Babson College, supplemented by executive courses at Stanford, Harvard, and Northwestern Universities. This strong educational foundation supports his practical work with family enterprises throughout the region. Carvajal's research and professional interests center on developing effective governance structures for multi-generational family businesses. His expertise includes designing Family Governance Systems, establishing Family Councils, and creating successful Family Offices that balance family dynamics with business objectives. He has developed frameworks for board effectiveness specifically tailored to the unique challenges of family-controlled enterprises. As an active practitioner, Carvajal frequently speaks at prominent organizations including FBN, Owners Council, IDB-Invest, and TEC Monterrey. His insights bridge academic theory with real-world application in family business contexts across Latin America. His professional leadership extends beyond academia to significant board roles. He currently serves on the Board of Directors of CARVAJAL S.A. (where he previously served as Chairman for six years), chairs the CARVAJAL Foundation, and sits on the boards of ICESI University and BOLIVAR Group in Colombia. Carvajal's international experience includes serving as Ambassador of Colombia to France and UNESCO in Paris, where he played a pivotal role in Colombia's accession process to the OECD. He also served concurrently as Ambassador to Monaco and Algeria, bringing global perspective to his work with family enterprises. Partner at Lansberg Gersick Advisors (LGA) Professor, Executive Education Program, Universidad ICESI Board Director, CARVAJAL S.A. Chairman, CARVAJAL Foundation Board Member, ICESI University Former Ambassador of Colombia to France, UNESCO, Monaco, and Algeria
Debasis Ganguly is a Lecturer in Data Science at the School of Computing Science, University of Glasgow. His research focuses on information retrieval, natural language processing, and machine learning, with particular emphasis on query performance prediction, in-context learning, and legal IR systems. He actively contributes to workshops such as SIGIR and ECIR. Research interests include AI methodology extraction, query variant analysis, and privacy-aware machine learning. He has organized workshops like JCDL 2024 and LLMIT at CIKM 2023. Key publications span topics like retrieval-augmented generation with mixed data, query-specific pooling strategies, and legal data annotation systems.
Allel Hadjali is a Full Professor in Computer Science specializing in Data Engineering at ISAE-ENSMA (École Nationale Supérieure de Mécanique et d'Aérotechnique) in Poitiers, France. He is affiliated with the Laboratory LIAS (Laboratoire d'Ingénierie des Applications de la Connaissance et des Systèmes) at ISAE-ENSMA. His academic career includes progression from Associate Professor to his current Full Professor position, with extensive teaching experience across multiple computer science domains. Professor Hadjali's research falls within the data science domain, with particular focus on Exploitation, Extraction, and Recommendation (E2R). His work applies Computational Intelligence and Soft Computing techniques to massive data exploitation and analysis, including flexible querying approaches (Skyline, Gradual, and Bipolar queries), modeling and querying uncertain/incomplete data, cooperative answering techniques, and data reduction through linguistic summaries. He also conducts research in recommendation systems (learning-based and group recommendation) and extraction techniques (mining gradual patterns), along with related interests in data quality, intelligent systems, and crowdsourced data management. His publication record demonstrates consistent contributions to top-tier journals and conferences, with recent work focusing on skyline query processing, uncertain data management, RDF knowledge bases, and explainable AI. His research shows a clear trajectory from foundational work in fuzzy logic and uncertain databases toward more applied research in semantic web technologies and machine learning explainability. Professor Hadjali serves on the editorial boards of several prestigious journals including the Journal of Smart Environments and Green Computing, Sensors Journal, and the Universal Journal of Aeronautics and Aerospace Research. He has also organized special issues on topics such as uncertainty in cloud computing and managing uncertain data. At ISAE-ENSMA, Professor Hadjali teaches courses including Formal aspects of software engineering, Language interpretations and compilation, Programming languages, and Data management and exploitation. Previously as an Associate Professor, he taught courses on object modeling, distributed algorithms, operating systems, and advanced databases focusing on preferences and uncertainty. He leads the Data Engineering team within the Laboratory LIAS, which focuses on developing computational intelligence approaches for modern data challenges. His current projects include work on data quality (QDoSSI project funded by CNRS Mastodons 2016-2018) and research actions in GDR MADICS 2018 related to scientific data quality.
Janardhan Rao (Jana) Doppa is an Associate Professor in the School of Electrical Engineering and Computer Science (EECS) at Washington State University (WSU). He holds the Huie-Rogers Endowed Chair in Computer Science and the Berry Distinguished Professorship in Engineering. His research focuses on artificial intelligence, machine learning, and data-driven science, with applications in structured prediction, Bayesian optimization, and sustainable computing. He chairs the EECS Graduate Studies program and has received awards such as the NSF CAREER Award (2019) and the Voiland College Anjan Bose Outstanding Researcher Award (2024). Education: Ph.D., Computer Science, Oregon State University (2014) M.Tech., Computer Science, Indian Institute of Technology Kanpur (2006) Research Interests: Dr. Doppa's work spans AI-driven adaptive experiment design, sequential decision-making under uncertainty, robust machine learning, and applications in agriculture, health informatics, and electronic design automation. He leads the NSF-USDA AI Institute for Agricultural Decision Support and explores AI methods for nanoporous materials design and sustainable computing. Awards: NSF CAREER Award (2019) Voiland College Anjan Bose Outstanding Researcher Award (2024) Best Paper Awards at multiple conferences (e.g., ACM/IEEE Embedded Systems Week 2023) Outstanding Junior Faculty in Research (2020) and Reid Miller Teaching Excellence (2018) Advising & Grants: He advises a dynamic group of PhD and MS students, many of whom have won awards. His grants include NSF-CAREER and USDA AI Institute funding. He teaches courses like Machine Learning and Structured Prediction at WSU. Labs/Teams: His research group collaborates with industry and academia, advancing AI for engineering and scientific domains through interdisciplinary projects.
Andrew Hutchinson is a Researcher at the School of Electrical and Electronic Engineering, University of Sheffield, specializing in energy storage systems and grid resilience. His work focuses on optimizing power systems to reduce carbon emissions, enhance renewable energy integration, and improve grid stability through advanced storage technologies like flywheels and batteries. He holds a Research Associate position and has contributed to over 20 peer-reviewed articles since 2020. Research Interests: Energy Storage System Design & Control Grid Decarbonization Strategies Renewable Energy Integration Challenges Frequency Response Services Techno-Economic Analysis Grid Resilience Assessment Recent Work Trends: His articles emphasize hybrid storage systems, flywheel applications for ancillary services, and economic feasibility studies for energy storage deployment. He explores how storage technologies can mitigate export limitations in wind and solar sites while enhancing grid resilience against climate change impacts. Advising & Grants: No formal advisee records or grant details provided in the text. Labs/Teams: Affiliated with the School's energy storage research groups, collaborating on projects funded by UK energy networks and academic partnerships.
