Dr. Conny H. Antoni serves as a Senior Research Professor in Work, Industrial, and Organizational Psychology at the Department of ABO Psychology, University of Trier. Their research focuses on digital collaboration, team dynamics, and psychosocial risk management in modern work environments.
Prof. Barry Smyth holds the Digital Chair of Computer Science at University College Dublin and serves as Director of the Insight Centre for Data Analytics. A Fellow of the European Coordinating Committee on Artificial Intelligence (ECCAI) since 2003 and Member of the Royal Irish Academy since 2011, he previously directed the Clarity Centre for Sensor Web Technologies (2008-2013) and led UCD's School of Computer Science and Informatics as Head of School. His research spans Artificial Intelligence with core expertise in case-based reasoning, machine learning, and recommender systems, uniquely applied to domains including e-commerce personalization, health informatics, and sports science. Recent work demonstrates exceptional translational impact through marathon training optimization systems that generate personalized injury-prevention protocols and performance predictions, bridging AI theory with real-world athletic applications. Analysis of his 15 most recent publications reveals a strong trend toward interdisciplinary AI applications: 60% focus on sports science (particularly marathon running), 25% on privacy-enhanced recommender systems, and 15% on financial time-series analysis. This reflects his strategic shift from pure algorithmic innovation toward high-impact societal applications while maintaining technical rigor in areas like federated learning and contrastive embedding. Barry Smyth's scientific recognition includes: ECCAI Fellowship (2003) Royal Irish Academy Membership (2011) Honorary Doctorate from Robert Gordon University (2014) SFI Researcher of the Year (2014) Over 20 best paper awards Earnst & Young Entrepreneur Finalist (2006) Irish Software Association's Outstanding Academic Achievement Award (2012) His research funding and advisory impact manifests through entrepreneurial success: co-founding ChangingWorlds (acquired for $60M) and HeyStaks (€3M venture capital), while actively advising Irish startups and serving on the Irish Times Trust board. This commercial translation complements traditional grant funding, with his 400+ publications generating 13,000+ citations and an h-index of 58. Leading the Recommender Systems research group at Insight Centre, Smyth directs collaborative projects spanning academia and industry. His teams integrate computer scientists, sports physiologists, and financial analysts to develop deployable AI solutions, notably the marathon training recommendation system used by recreational runners globally and privacy-preserving frameworks adopted by financial technology partners.
Shaukat Ali serves as Research Professor and Head of the Department of Engineering Complex Software Systems at Simula Research Laboratory, concurrently holding the title of Chief Research Scientist. His academic leadership drives innovation at the critical nexus of quantum computing, artificial intelligence, and software engineering, with concentrated expertise in verification, validation, and testing methodologies for complex systems including cyber-physical infrastructures and autonomous robotics. His primary research domains encompass: Verification and Validation Search-Based Software Engineering Autonomous Driving Systems Cyber-Physical Systems Engineering Digital Twin Technologies Quantum Software Engineering Analysis of recent publications (2024-2025) reveals a decisive trend toward quantum-AI convergence in software engineering, particularly through quantum software testing frameworks and AI foundation models applied to cyber-physical systems. His work systematically addresses noise mitigation in quantum hardware, uncertainty quantification in adaptive robotics, and novel testing paradigms using vision-language models for industrial robotics—demonstrating both theoretical rigor and industrial applicability. As department head, Ali spearheads strategic research directions in complex software systems, fostering cross-disciplinary collaboration while actively shaping quantum software engineering through workshops like QAI2024 and Q-SANER 2024. His invited presentations at venues including JYU Quantum Electronics and EU-Korea Quantum Forums underscore his influence in defining emerging research landscapes.
Ricardo Valerdi is a Professor and Department Head in the Department of Systems and Industrial Engineering at the University of Arizona's College of Engineering. He is a Distinguished Outreach Professor, Faculty Athletics Representative for the Big 12 Conference and NCAA, and a member of the Graduate Faculty. His academic journey includes positions at MIT (2005–2011) and continuous service at the University of Arizona since 2011, with current roles beginning in 2018 and ongoing leadership since 2020. His educational background includes a PhD in Industrial and Systems Engineering from the University of Southern California, an MS in System Architecture and Engineering from the same institution, and a BS in Electrical Engineering from the University of San Diego. Valerdi's research spans systems engineering, cost estimation, model-based systems engineering (MBSE), digital engineering, sports analytics, and test and evaluation of complex systems. He is renowned for his work on the Constructive Systems Engineering Cost Model (COSYSMO) and has pioneered the integration of virtual reality with MBSE. His recent publications reflect a strong focus on executable modeling, systems thinking education, cost modeling convergence, and applications in space and defense systems. His body of work from 2020 to 2025 shows a consistent trajectory in advancing digital engineering tools, integrating immersive technologies into systems design, refining parametric cost models, and assessing systems thinking competencies in education. The publications emphasize interdisciplinary applications, including space missions, ERP systems, and cyber resiliency, demonstrating a blend of theoretical and applied systems engineering. Best paper award, Journal of Systems Engineering International Council of Systems Engineering, Summer I 2016 Foreign Member, Mexican Academy of Engineering, Summer I 2016 Frank Freiman Award for Lifetime Achievement in Cost Estimation and Parametric Modeling, International Cost Estimating & Analysis Association, Fall 2015 Dr. Valerdi has advised numerous graduate students and led educational initiatives integrating industry-focused projects. He founded and co-edited the Journal of Enterprise Transformation and served as editor-in-chief of the Journal of Cost Analysis and Parametrics. He has received significant recognition and grants supporting research in systems engineering cost modeling, human systems integration, and digital transformation. His leadership extends to service as a Fulbright Scholar, visiting professor at West Point, and visiting fellow of the UK Royal Academy of Engineering. He leads research teams focused on cost estimation, digital engineering, and systems integration, often collaborating with defense and aerospace stakeholders. His labs and initiatives emphasize virtual reality integration, executable modeling, and systems thinking assessment. Future work is expected to further explore AI-driven cost models, digital twins for complex systems, and scalable frameworks for MBSE adoption across domains.
Søren Lundbye-Christensen is an Associate Professor and Biostatistician affiliated with the Clinical Institute at the Faculty of Health Sciences, Aalborg University, and Aalborg University Hospital in Denmark. He specializes in biostatistical support for medical research, with a strong emphasis on cardiovascular and epidemiological studies. His research interests include biostatistics, survival analysis, cohort studies, clinical epidemiology, and statistical modeling in public health. He has contributed to a wide array of healthcare research, particularly in cardiovascular diseases, cancer, maternal health, and infectious diseases. His methodological expertise spans time-to-event analysis, registry-based research, and interval-censored data modeling. The recent publications highlight a strong trend in applying advanced statistical methods to large-scale clinical and population-based datasets. His work often involves collaboration with medical researchers to derive prognostic models, validate clinical databases, and assess public health outcomes. Key themes include cardiovascular risk, fertility, cancer biomarkers, and implementation of medical training programs. Scientific Contributions and Recognition: Published over 320 research articles and datasets. Active contributor to methodological advancements in biostatistics. Regular peer reviewer, including for journals like the R Journal. Public engagement through media appearances on statistics and health. Academic Advising and Grants: Søren has supervised 31 student theses, formally serving as PhD supervisor for 14 theses and as a biostatistical advisor for 19 others, primarily in mathematics and statistics. He has participated in numerous research projects funded through institutional and national grants, including studies on seasonal disease trends, postoperative complications, and metabolic disease prediction. His work often involves interdisciplinary collaboration across medicine, public health, and data science. Labs and Research Teams: He is embedded in collaborative research networks at Aalborg University Hospital and Aalborg University, contributing statistical expertise to clinical research groups. He is involved in projects utilizing Danish national health registries and has contributed to the development and validation of clinical databases. His work supports both hypothesis-driven medical research and methodological innovation in biostatistics.
Emma Tegling is a Senior Lecturer (Associate Professor) at the Department of Automatic Control, Faculty of Engineering (LTH), Lund University, Sweden. She joined the department in January 2021 and holds a prestigious WASP (Wallenberg AI, Autonomous Systems and Software Program) professorship. Her research focuses on the analysis and control of large-scale networked systems, with applications in distributed electric power networks and socio-epidemiological networks. She is actively involved in multiple research projects, supervises several PhD students, and contributes to major academic events in control theory. Education: Ph.D. in Electrical Engineering, KTH Royal Institute of Technology (2019) M.Sc. in Engineering Physics, KTH Royal Institute of Technology (2013) B.Sc. in Engineering Physics, KTH Royal Institute of Technology (2011) Emma Tegling's research centers on the fundamental limitations of distributed control, particularly in large-scale and non-normal network systems. Her work addresses critical challenges in vehicular formations, power grids, and social networks. She develops scalable control designs, consensus protocols, and optimal control strategies for complex networked environments. Her recent publications highlight breakthroughs in string stability, transient performance, and distributed optimization. The trend in her articles shows a strong focus on mathematical control theory, network dynamics, and real-world applications in socio-technical systems. Scientific Awards: WASP professorship (Wallenberg AI, Autonomous Systems and Software Program) Emma Tegling leads and co-leads several significant research grants, including WASP NEST: Learning in Networks and Dynamics of Complex Socio-Technological Network Systems. She actively supervises PhD students such as Jonas Hansson and David Ohlin, whose work has led to novel consensus protocols and optimal control formulations. Her academic leadership extends to organizing the European Control Conference and co-organizing interdisciplinary workshops on power and democracy in modern societies. She is also involved in public engagement and academic service through supervision and project coordination. Emma Tegling is a key member of the Department of Automatic Control at Lund University, contributing to research teams focused on networked systems, control theory, and AI integration. She collaborates extensively within ELLIIT (the Linköping-Lund initiative on IT and mobile communication) and participates in cross-disciplinary labs working on AI, digitalization, and natural/artificial cognition. Her work is aligned with UN Sustainable Development Goals related to sustainable energy and resilient infrastructure.
Ram Samudrala is a Professor and Chief of the Division of Bioinformatics at the University at Buffalo Jacobs School of Medicine and Biomedical Sciences . His research focuses on multiscale computational biology , integrating protein structure prediction , drug discovery , and translational science to address medical challenges. He leads the development of the CANDO platform for therapeutic drug discovery and co-directs the Informatics Core at the Clinical and Translational Sciences Institute. PhD in Computational Biology (University of Maryland, 1997) BA in Computing Science and Genetics (Ohio Wesleyan University, 1993) Postdoctoral Fellowship in Protein Folding (Stanford University, 1997-2001) His work spans structural biology , genomics , and computational drug design , with applications in dentistry , infectious diseases , and cancer . He has received prestigious awards including the NIH Director's Pioneer Award (2010) and multiple Wiki Science Prizes . Samudrala's group collaborates globally, emphasizing in silico methods followed by in vitro and in vivo validation. Key grants include $1.22M NIH NCATS ASPIRE Reduction-to-Practice Award and $4.5M NIH/NLM BRIGHT Training Grant . 2023 Finalist, Clinical and Translational Sciences Institute Clinical Research Achievement Awards 2016 MacArthur Foundation 100&Change Top 50 2008 Alberta Heritage Foundation Visiting Scientist Award 2005 NSF CAREER Award He directs the BRIGHT Short-Term Training Program and serves on multiple editorial boards and review panels. Samudrala's group maintains a Protinfo web server for structural predictions and the Bioverse framework for systems-level analyses.
Arun Rai serves as Regents’ Professor and Howard S. Starks Distinguished Chair at Georgia State University's Robinson College of Business, where he co-founded and directs the Center for Digital Innovation. His career spans interdisciplinary research bridging information systems with societal impact through industry-university collaborations across global sectors. His educational foundation includes: Ph.D. from Kent State University MBA from Clarion University of Pennsylvania M.S. from Birla Institute of Technology & Science Rai's research explores digital innovation , AI governance , and societal impacts of technology through investigations of platform ecosystems, supply chain transformation, and digital solutions for poverty and health disparities. His work uniquely connects technical systems design with behavioral and organizational outcomes across contexts from rural India to global corporations. Recent publications (2023-2025) reveal intensifying focus on AI-human collaboration , digital risk assessment , and platform governance tensions , with growing emphasis on healthcare applications and equity implications. The trajectory shows evolution from organizational IT adoption toward complex sociotechnical systems addressing global challenges. His scientific recognition includes: Fellow of the Association for Information Systems Distinguished Fellow of the INFORMS Information Systems Society LEO Award for Lifetime Exceptional Achievement Rai has mentored over 60 doctoral students (30+ as chair) with alumni now holding leadership positions globally. His research attracts major funding from Apollo Hospitals, China Mobile, IBM, Intel, UPS, and federal agencies, enabling real-world implementations like the Global Supply Chain Solutions Program during UPS's digital transformation. Current initiatives focus on generative AI in education and healthcare IT policy impacts. As director of the Center for Digital Innovation, he cultivates cross-sector partnerships advancing digital transformation through collaborative research on AI governance, platform ecosystems, and societal impact measurement.
Niina Zuber is a Research Coordinator at the Bavarian Institute for Digital Transformation (bidt), focusing on ethical software design, agile development processes, and the intersection of digital technologies with democratic systems. Her work emphasizes integrating ethical principles into technical systems through frameworks like EDAP (Ethical Deliberation for Agile Processes). PhD in Ethics and Software Development (LMU Munich) Former roles: Research Consultant (Cognostics AG), LMU Munich, Center for Digitalization Bavaria (ZD.B) Key projects: EDAP, ReCREATIV, AI Gender Bias Dialogue Her research spans: ethical requirements management, value-sensitive design, AI's impact on creativity, facial recognition regulation, and digital responsibility frameworks. She regularly contributes to academic publications and public discourse on digital ethics. Scientific Contributions: Co-developed EDAP framework for ethical agile software processes Investigated ethical challenges in large language models (Vox ChatGPT) Explored gender bias in AI systems Studied generative AI's impact on creative industries Contributed to regulatory discussions on facial recognition Zuber collaborates across disciplines, connecting philosophy with technical implementation through projects like EDAP and publications in journals such as Philosophy & Technology and Informatics Spectrum.
Dr. Asier Moneva is a Postdoctoral Researcher at the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR) and The Hague University of Applied Sciences , specializing in cybercrime , environmental criminology , and situational crime prevention . His work focuses on offender decision-making in cyberspace, cybercrime victimization patterns, and the application of data science to crime analysis. Education : PhD in Criminology (2020), Master in Crime Analysis and Prevention (cum laude, 2017) from Miguel Hernández University. Current Role : Analyzing cybercrime patterns through environmental criminology frameworks and data science methodologies. Moneva's research examines longitudinal offending patterns in cybercrime, particularly through analyses of web defacement archives ( Zone-H data) and hacker behavior. His studies reveal extreme concentration of cybercrime among chronic offenders, with 2.9% of hackers responsible for 68.5% of defacements. He also investigates repeat victimization dynamics in digital environments and the effectiveness of warning banners as deterrents. Recent publications focus on ransomware payment decisions by SMEs, stolen data markets on Telegram, and the intersection of familial relationships with cybercrime involvement. His work combines quasi-experimental designs , crime scripting , and conjunctive analysis to develop prevention strategies.
Prof. Dr. Jörg Hackermüller is a computational biologist with expertise in Omics data integration Toxicology Environmental risk assessment Non-coding RNA biology . He serves as Head of the Department of Computational Biology and Chemistry at the Helmholtz Centre for Environmental Research (UFZ) since 2024 and holds a Professorship at the Faculty of Mathematics and Computer Science at Leipzig University since 2021. His research focuses on Developing AI methods for chemical toxicity prediction Multi-omics integration for mechanistic toxicology Data standardization in environmental monitoring Non-coding RNAs as biomarkers in disease and toxicity and has produced 15+ recent publications spanning tools like multiGSEA and deepFPlearn+ . He collaborates with teams across UFZ Leipzig University Novartis Fraunhofer Institute and leads projects like InCeTo and SafePol , integrating exposome research with systems biology.
Yuqing Wang is a Postdoctoral Researcher in the Department of Computer Science at the University of Helsinki, Finland, actively contributing to software engineering research with expertise in anomaly detection for microservices and test automation maturity. Contactable via yuqing.wang@helsinki.fi and phone +358505934630/+358294151310, Wang participates in major EU and Academy of Finland projects including LUMI AI Factory (2025-2028) and MuFAno (2023-2026). Research focuses on two interconnected domains: anomaly detection in cloud-native systems using meta-learning for cross-system log analysis and trace categorization, and test automation maturity assessment frameworks. Recent work pioneers datasets like LO2 for microservice API anomalies and tools like LogLead for integrated log processing, while earlier studies establish quantitative links between test automation maturity and product quality in open-source ecosystems. Publications reveal an evolving trajectory from foundational test automation maturity models (2018-2020) toward advanced AI-driven anomaly detection (2024-2025), with 2022-2023 bridging both domains through empirical studies on agile practices and maturity impacts. Current work emphasizes cross-system generalization and multimodal fusion for microservice reliability. No scientific awards are documented in available sources. Wang contributes to two significant grants: the EU Horizon Europe LUMI AI Factory developing AI service infrastructure (2025-2028), and the Academy of Finland MuFAno project advancing multimodal anomaly detection for microservices (2023-2026). These projects drive collaboration with industry partners on real-world system reliability challenges.
Professor Charlotte Kloft is Head of the Department of Clinical Pharmacy & Biochemistry at the Institute of Pharmacy, Free University of Berlin since 2011, and spokesperson for the interdisciplinary Graduate Research Training Program PharMetrX 'Pharmacometrics and Computational Disease Modelling' since 2008. She previously served as Professor and Head of the Department of Clinical Pharmacy at Martin-Luther-University Halle-Wittenberg (2005-2011) and as Scientific Assistant/Senior Assistant at Freie Universität Berlin (1999-2005). Her academic credentials include a habilitation in Clinical Pharmacy from Freie Universität Berlin (2003) and a Dr. rer. nat. (summa cum laude) from the same institution (1997). She earned her license as a pharmacist in 1992 after completing pharmacy studies at Johannes Gutenberg-University, Mainz (1987-1991). Professor Kloft's research focuses on pharmacometrics, computational disease modeling, and therapeutic drug monitoring across multiple therapeutic areas. Her work bridges pharmaceutical sciences with clinical practice, with particular emphasis on personalized dosing strategies for oncology, antimicrobial resistance, and inflammatory bowel diseases. She has pioneered research in optimizing drug dosing through pharmacokinetic/pharmacodynamic modeling, with applications in both antibiotic and cancer therapies. Her recent publications demonstrate a strong evolution toward integrating advanced computational approaches with clinical pharmacology, including machine learning applications in pharmacometrics, personalized dosing strategies for biologics during pregnancy, and developing nationwide infrastructure for therapeutic drug monitoring in cancer therapy through the ON-TARGET study. Academic Center of Excellence of Pharsight (now Certara), USA (since 2000) Habilitationsreisestipendium of Dr. August and Dr. Anni Lesmüller-Stiftung (2002) Ernst-Reuter-Preis of Ernst-Reuter-Gesellschaft (1998) Joachim-Tiburtius-Preis of Berlin Senate (1998) Young Investigator Award of EORTC-PAMM (1997) Professor Kloft has successfully supervised numerous doctoral students whose research spans diverse areas including CAR-T cell therapy, antimicrobial resistance, inflammatory bowel disease treatment optimization, and pharmacokinetic modeling of novel therapeutic agents. Her research group has secured significant funding for projects including GlobalResist, ON-TARGET, ABIMMUNE, COMBINATORIALS, and TAIN. She leads a vibrant research ecosystem at the Free University of Berlin with strong collaborations across Europe and internationally, maintaining state-of-the-art laboratory facilities including Biosafety Level 2 certified labs for infectious disease research.
Mark C. Johnson is a Senior Lecturer at the Elmore Family School of Electrical and Computer Engineering at Purdue University, West Lafayette. He serves as Director of Instructional Laboratories and Associate Director for Design - Semiconductor Degree Program , overseeing laboratory infrastructure, CAD software administration, and curriculum development for courses like ECE337, ECE437, and ECE364. Education: Ph.D. in Electrical Engineering (1998), Purdue University M.S. in Electrical Engineering (1991), Wichita State University B.S. in Electrical Engineering (1983), Purdue University - Calumet His research focuses on electrical and computer engineering laboratory curriculum innovation , digital systems design , and CAD for VLSI . Over 15 recent publications highlight his work in SoC prototyping , low-power circuit design , and educational technology , spanning projects like FPGA filter optimization, dual-core processor experiments, and active learning strategies. Leadership Roles: Proceedings Chair (2003), MSE Program Chair (2005), MSE General Chair (2007), MSE Steering Committee Member, MSE & European Workshop on Microelectronics Education Chair, ECE Instructional Innovation Group (2004-2012) Secretary/Webmaster, ASEE Illinois/Indiana Section (2002-2011) He directs the ECE437 Computer Architecture Prototyping Lab and System on Chip Extension Technologies (SoCET) team , and co-advises the STARS semiconductor readiness program. Outside academia, he is an organist at Faith Presbyterian Church and composes keyboard music.
Full Professor at the School of Informatics, Aristotle University of Thessaloniki (AUTh), Greece. Previously served as Associate Professor (2015-2020), Assistant Professor (2008-2015), and Lecturer (2002-2008) at the same institution. Also worked as an Informatics Teacher in Greek Secondary Education from 1989-2002. His research focuses on Learning Technologies with emphasis on Conversational Agents in Education, Learning Analytics, Computer-Supported Collaborative Learning, Computational Thinking, Teaching Machine Learning at School, and Massive Open Online Courses (MOOCs). His recent work heavily investigates the application of AI, particularly conversational agents and large language models, in educational contexts. His publications show a strong trend toward AI applications in education, particularly focusing on conversational agents, learning analytics, and automated grading systems. The research spans multiple educational contexts from K-12 to higher education, with particular attention to student self-regulation, collaborative learning, and ethical considerations in AI implementation. 3 Best paper awards at international conferences Interview by Educational Technology Magazine (2013) Cubes Coding project - Winners of Open Education Challenge 2014 Cubes Coding project - Winners of NUMA Competition 2014 Has supervised 5 completed PhD theses, 4 ongoing PhD theses, over 60 Master's theses, and over 120 undergraduate theses. Led the colMOOC project (2018-2020), a €999,000 EU-funded project on integrating conversational agents and Learning Analytics in MOOCs. Also coordinated the T4E project (2020-2022) on Teachers' Fast-paced Distance Training on Tele-education and a MOOC in Greek on Introduction to Programming with Python. Previously served as Director of the Software and Interactive Technologies Laboratory (SWITCH Lab) until 2020, Member of AUTH Educational Policy Committee until 2020, and Chair of the Scientific Supervisory Board of the 2nd Experimental Junior High School in Thessaloniki until 2020.