Véronique Benzaken is a Full Professor at the University of Paris-Saclay , affiliated with the Computer Science Department and member of the VALS (Verification of Algorithms, Languages, and Systems) research group at LRI (CNRS) and the Toccata group at INRIA-Saclay. Her research focuses on Data-Centric Programming Languages and Deep Specification with Proof Assistants , particularly SQL/XML formalization and Coq-based verification systems. Her work includes the development of the ℂDuce XML-centric functional programming language and the Datacert project (2016-2021) for certifying data-intensive systems using Coq and Why(3). She collaborates with Oracle Labs on multi-lingual query interfaces (QIR) and formalizes languages like XQuery, Datalog, and SQL execution plans. She has received significant funding through the ANR grants for the Typex (2016) and Datacert (2016-2021) projects. Her publications in venues like CPP, ESOP, ITP, and SPLASH reflect her leadership in formal methods for data systems. Education : Habilitation (1996), PhD (1990), DEA in Theoretical Computer Science (1986), and degree in Singing/Opera (1983). Employment : Full Professor at Paris-Sud 11 since 1998; Assistant Professor at Paris 1 Panthéon-Sorbonne (1990-1998); INRIA researcher (1986-1990).
Dr. Ioana Andreea Brezestean is a Scientific Researcher III (R2 rank) at the National Institute for Research and Development in Isotopic and Molecular Technologies (Cluj-Napoca, Romania). She holds a PhD in Physics (2022) and Master's degrees in Medical Physics (2013, 2015) from Babeș-Bolyai University . Her work focuses on nanomaterial synthesis , SERS substrate development , and environmental/health monitoring through advanced spectroscopic techniques. Current projects include NanedisSERS (bioinspired 3D nanoplatforms for neurodegenerative disease diagnostics) and AL-DIBI SERS (Alzheimer's biomarker detection using gold nanourchins). Her expertise spans nanoparticle fabrication (silver/gold), microfluidic sensor design , and multi-modal characterization (Raman, FT-Raman, SERS, TERS, microscopy). She contributes to eco-friendly nanocomposite development in projects like ECONANO4AUTO (bio-PA materials with chicken feather derivatives). Key collaborations include SINTEF AS (Norway), University of Medicine and Pharmacy 'Iuliu Hațieganu' , and NANOM MEMS SRL . Her methodology integrates DFT calculations , quantum chemistry modeling , and statistical pattern recognition for pathogen resistance analysis.
Martin Zurowietz is a researcher at the Genome Informatics Group , Institute for Bioinformatics Infrastructure (BIBI) , and Center for Biotechnology (CeBiTec) at Bielefeld University . His work focuses on bioinformatics infrastructure, marine data analysis, and deep learning applications for environmental monitoring. Research Interests : Bioinformatics, computational biology, machine learning, marine ecology, and data science. Technical Contributions : Development of platforms like BIIGLE and MAIA for large-scale image annotation, FAIR data principles in marine imaging, and automated diatom taxonomy. Key Collaborations : Projects involving polymetallic nodule fields, Vazella pourtalesii assemblages, and environmental impact assessments using deep learning. Recent Publications highlight his expertise in: Deep learning for biodiversity analysis Marine imaging systems and workshops Digital microscopy methods Data management for marine ecosystems Interactive visualization tools for scientific data
Dr Alan Cannon is a Research Fellow at Edinburgh Napier University's School of Computing , affiliated with the Centre for Algorithms, Visualisation and Evolving Systems . His work spans data-driven web technologies, information visualization, interaction design, and software evaluation. Education: PhD: Interactive Visualisation Tools for Supporting Taxonomists Working Practice (2006) Alan specializes in creating visualization systems for biological and taxonomic data through projects like MaTSE and TaxVis . His recent work focuses on mobile platforms for safety engineering inspections and data-driven web services for academic and commercial applications. His publications demonstrate expertise in bioinformatics visualization, ontology-driven systems, and mobile application development across multiple domains including taxonomy, property management, and safety engineering. Research Grants: Data Driven Analysis of PEMFT Benefits (2022, £5,000) Solicitor Data Management for TC Young (2018, £5,000) Managing Archaeological Projects (2017, £5,000) Follow-on development for Plansafe Ltd. (2015-2016, £35,837) TrueBuild App Development (2014-2015, £5,000) Scottish Forestry Project (2016-2017, £28,492) Alan has extensive experience in academic-industry collaboration, commercialization activities, and developing visualization tools for complex data sets across biological sciences, engineering, and database systems.
Bobby May is a Lecturer in the School of Psychology and Neuroscience at the University of St Andrews, affiliated with the Centre for Research into Equality, Diversity & Inclusion and the Centre for Social Learning & Cognitive Evolution. He is actively engaged in research and teaching, focusing on sex differences in human social behavior. His research interests center on sex differences in risky behavior, aggression, and emotional dynamics in social contexts. He employs meta-analytic and experimental methods to investigate how these differences manifest and evolve. A current focus is on how psychological sex differences are perceived and communicated in the media. His work aligns with UN Sustainable Development Goals, particularly gender equality. His recent publications (2023–2024) emphasize meta-analytic studies on aggression, heart rate variability, and emotional conflict in relationships. He has contributed to datasets and software tools supporting open science. His research often intersects with behavioral neuroscience, social psychology, and evolutionary perspectives. Bobby May has received no individual scientific awards listed in the text, though his collaborators have been recognized for public engagement. He is involved in advising students, as seen through his supervision of datasets and student projects. He is a Co-Investigator on two recent projects: one on digital skills development in response to COVID-19, and another on building a database for domestic abuse services. These reflect his engagement with applied research and community impact. He also participates in public science events such as EXPLORATHON and the Edinburgh Fringe, promoting science communication. Bobby May supervises research students and contributes to collaborative research teams, particularly with researchers like Donaldson, Cross, and McCurry. He supports open science through data and software sharing via repositories like Zenodo and the University of St Andrews data archive.
Arnaldo Pereira is an Invited Assistant Professor at the Instituto Politécnico de Bragança. He holds a Ph.D. in Informatics from a collaborative program between the University of Aveiro, University of Porto, and University of Minho (MAPi), focusing on semantic data querying and visualization. His research interests include Artificial Intelligence, Intelligent Systems, and their applications in biomedical informatics and FAIR data practices. He has contributed to European research projects advancing data integration and control systems. Education: Ph.D. in Informatics (Collaborative Program: University of Aveiro, University of Porto, University of Minho) Research Interests: Dr. Pereira specializes in semantic data technologies, FAIR data principles, and their application to biomedical database systems. His work emphasizes query optimization, visualization tools for complex data, and the development of interoperable systems in healthcare and industrial contexts. Recent efforts focus on collaborative workshops (BYOD) to enhance data management practices and knowledge sharing in interdisciplinary environments. Key Research Trends (2020–2024): His publications highlight advancements in FAIR-compliant tools, semantic querying of biomedical databases, and the integration of AI-driven approaches for data accessibility and system monitoring. Earlier work includes contributions to industrial cyber-physical systems, KPI optimization, and agent-based enterprise architectures. Grants & Collaborations: Active participant in EU-funded research projects focusing on data integration and intelligent systems. No specific grant details provided in the text. Labs/Teams: Affiliated with computational and biomedical informatics groups at his institution, though specific lab names are not mentioned.
Vasilis Efthymiou is an Assistant Professor at the Department of Informatics and Telematics at Harokopio University of Athens (HUA), Greece. His research focuses on Big Data database systems, entity resolution, knowledge graphs, and machine learning applications. He has held postdoctoral positions at IBM Research and FORTH-ICS, and contributed to initiatives like the SemTab challenges and TaDA workshops. Education: Diploma in Computer Science (2010), University of Crete. Masters in Information Systems and Bioinformatics (2012), University of Crete. PhD in Entity Resolution in the Web of Data (2017), University of Crete. Research Interests: Efthymiou’s work emphasizes scalable entity resolution techniques, fairness-aware AI systems, and knowledge graph integration. He explores applications in cybersecurity, natural language interfaces, and privacy-preserving data analytics. Recent projects include automated entity resolution pipelines (e.g., TREATS) and hybrid graph neural networks for entity alignment (HybEA). Publications: His 60+ papers span venues like VLDB, SIGMOD, and AAAI. He co-authored two books and holds four US patents in data systems. Notable works include surveys on end-to-end entity resolution and fairness-aware entity resolution tools. Grants & Labs: He co-organized international workshops (e.g., TaDA) and contributed to benchmarking systems like SemTab. His team develops tools like FairER and pyJedAI, emphasizing open-source solutions for data integration challenges.
Dr. Temechu Girma Zewdie is an Assistant Professor of Computer Science and Engineering at the University of the District of Columbia’s School of Engineering and Applied Sciences. He holds a Ph.D. in Computer Science and Engineering from UDC and multiple advanced degrees in Cybersecurity, Software Engineering, and Management. His expertise focuses on cybersecurity, artificial intelligence, cloud computing, IoT security, and machine learning. Dr. Zewdie’s research addresses critical challenges in cybersecurity, including ransomware detection in IoT systems, malware identification in cyber-physical systems, and securing software-defined networks against DDoS attacks. He has published extensively in top venues such as HCI International conferences and journals like Issues in Information Systems . His work emphasizes practical applications of AI and machine learning to enhance cybersecurity frameworks and IoT resilience. He teaches courses on database administration, IT security, data communication, and programming in Python and C++. Dr. Zewdie actively contributes to academic conferences and workshops, including presentations on cybersecurity in industrial robotics at Robotics: Science and Systems Conference. His research portfolio reflects a strong focus on interdisciplinary solutions, combining network science, machine learning, and human-computer interaction principles to address evolving cybersecurity threats. While no awards are explicitly mentioned, his prolific publication record underscores his impact in the field.
Sylvia Ratnasamy is a Professor of Computer Science at the University of California, Berkeley, specializing in networked systems design. She holds affiliations with the International Computer Science Institute (ICSI), the Networked Systems Lab (NETSYS), and the Software Principles for Advanced Networking (SPAN) Center. Her research focuses on scalable network architectures, middlebox virtualization, data center networking, and distributed systems. Education: PhD in Computer Science from UC Berkeley (2002), Bachelor's in Computer Engineering from the University of Pune, India (1997). Research interests include networked systems, software-defined networking, middlebox architectures, and performance optimization. Notable contributions include the design of NetBricks, E2 framework for NFV, and foundational work on data-centric storage (e.g., OpenDHT). Recent work explores cloud-augmented autonomous driving, cellular network architectures, and hardware-accelerated scheduling. Major awards include the ACM Grace Murray Hopper Award (2014), ACM SIGCOMM Test-of-Time Award (2011), and Sloan Research Fellowship (2012). She has advised numerous projects funded by NSF, DARPA, and industry collaborations. Labs/Teams: Co-leads the SPAN Center for networking research. Active in academic service, including SIGCOMM Technical Steering Committee and program committees for top conferences like NSDI, SOSP, and HotNets.
Tahereh T Jafari serves as a Senior Lecturer in the Department of Finance, Information Systems, Economics, and Risk Management at the University of Houston-Downtown, bringing over 15 years of teaching experience in Information Technology and computer science alongside prior industry expertise as a computer project manager and analyst at ExxonMobil. Her academic role encompasses extensive instruction in business applications, database management, and information systems infrastructure. Education: MS in Computer Science, University of Houston BS in Computer Science, University of Houston Research Interests: Jafari's scholarship centers on transformative applications of artificial intelligence in business education, particularly examining how generative AI tools like ChatGPT enhance student comprehension, collaborative problem-solving, and critical thinking development. Her work bridges educational technology with Management Information Systems, investigating multimedia platforms like Blackboard Voice Thread and signature assignments to foster active learning, while earlier research explored risk preference correlations between financial and academic contexts among college students. Publication Trends: Her scholarly output demonstrates a clear evolution from foundational work in database interfaces (2016) toward cutting-edge AI education research (2024), with recent publications emphasizing generative AI's pedagogical opportunities and ethical challenges. This interdisciplinary trajectory spans computer science, educational psychology, and business information systems, reflecting her commitment to innovating teaching methodologies through technological integration. Scientific Awards: Certificate in Effective Teaching Practice Framework Facilitating Engaging Class Discussions Planning Effective Class Discussions Promoting Active Learning Using the Active Learning Cycle Developing Effective Class Sessions and Lectures Teaching Powerful Note-Taking Skills Using Groups to Ensure Active Learning Developing Self-Directed Learners Inspiring Inquiry and Preparing Lifelong Learners Using Advanced Questioning Techniques Using Student Achievement and Feedback to Improve Your Teaching Motivating Your Students Providing Clear Directions and Explanations Using Concept Maps and Other Visualization Tools Building Community and Managing Discourse Establishing an Inclusive Learning Environment Evaluating Teaching Effectiveness Evidence-Based Instruction Exploring Universal Design for Learning Flexible Instructional Frameworks Inclusive Teaching Scholarship of Teaching and Learning Student Motivation in the Classroom & Beyond UHD CTLE Teaching Certificate Writing for English Language Learners Decision Filters for an Aligned Course Design Designing a Quality Course Learning Assessments & Feedback Learning Environment Modeling @ UHD Advising and Service: Jafari actively mentors students through recruiting initiatives and structured mentoring programs while serving on numerous university committees including Faculty Affairs, Scholarship, and Search Committees at departmental, college, and institutional levels. Her professional service encompasses SAP University Alliances membership, conference workshop leadership, and contributions to course assessment and industry-academic relationship building, though no specific research grants are documented.
Peter van de Waerdt is a Lecturer in Technology Law and Competition Law at the Faculty of Law, University of Groningen, where he is also a PhD candidate in the Transboundary Legal Studies department. His academic work bridges data protection law and competition law, focusing on the challenges posed by dominant digital platforms and the interdependence between personal data and market power. Education: LLM in International and European Law, University of Groningen (focus: European human rights law) Research LLM, University of Groningen (thesis: "The Economic Value of Personal Data in European Law") Study period at George Washington University, Washington D.C. (2014, focus: American fundamental rights) PhD candidate at the University of Groningen (since September 2016, supervisors: Prof. G.P. Mifsud Bonnici and Prof. H.H.B. Vedder) His research interests revolve around the legal and economic dynamics of data-driven markets, particularly how large online platforms leverage personal data to consolidate market dominance. He critically examines the limitations of existing regulations such as the GDPR and explores how competition law can be strengthened in conjunction with data protection frameworks. His work engages with emerging EU legislation like the Digital Markets Act and investigates structural issues such as information asymmetry, data ecosystems, and consumer lock-in. His recent publications demonstrate a strong trend toward integrating competition and data protection law, emphasizing that data is not just a privacy concern but a source of market power. Articles like "Data is Power" and "Reinforcing data protection and competition through art. 6(2) of the Digital Markets Act" argue for a more holistic regulatory approach. His scholarship is published in leading journals such as International Review of Law and Economics , World Competition , and Computer Law & Security Review . Scientific Recognition: Media expert commentary on his PhD thesis (November 2024) ORCID: 0000-0002-4069-935X Active presence in academic databases (Scopus, Research Portal, Pure) Peter van de Waerdt contributes to both teaching and research at the University of Groningen. While no formal advisees are listed, his supervisory experience is evident through his role in guiding legal discourse on digital market regulation. He has not received specific named awards yet, but his work has garnered significant academic attention, including over 30 Scopus citations for his 2020 article and widespread downloads of his thesis. His research is aligned with UN Sustainable Development Goals related to justice, inequality, and responsible innovation. He is affiliated with the Transboundary Legal Studies group, which focuses on global legal challenges, and contributes to shaping regulatory responses to digital platform power. His future work is expected to further influence EU digital policy and interdisciplinary legal scholarship at the intersection of law, economics, and technology.
Sharad Kumar Gupta is a Guest Scientist at the Helmholtz-Centre for Environmental Research - UFZ in Leipzig, Germany, and a Scientist at the Center for Advanced Systems Understanding (CASUS) in Görlitz. His research focuses on remote sensing , environmental informatics , and geospatial data analysis with applications in ecological modelling , UAV technology , and environmental risk assessment . Education Ph.D. in Remote Sensing (2015) - Indian Institute of Technology Mandi M.Tech in Geoinformatics (2014) - NIT Bhopal B.Tech in Computer Science (2011) - Uttar Pradesh Technical University Research Highlights Developed Drone4Tree cloud platform for UAV-based tree canopy detection Specialized in hyperspectral data scaling and agricultural stress monitoring Published extensively on environmental data integration , geophysical inversion , and urban green infrastructure Affiliations Dept. Monitoring and Exploration Technologies, UFZ Dept. Earth Systems Research, CASUS (HZDR) Key Publications address landslide susceptibility mapping , UAV-based environmental monitoring , machine learning applications in agriculture, and multi-method data integration for subsurface analysis. His work appears in journals like EGU General Assembly , Permafrost Periglacial Processes , and Environmental Earth Sciences .
Shlomo Geva is an Adjunct Professor in the School of Computer Science at Queensland University of Technology's Faculty of Science. His research focuses on information retrieval systems, particularly in specialized areas including XML search engines, text search engines, link discovery, and document computing. His academic work spans multiple disciplines within computer science, with particular emphasis on information retrieval technologies and their applications. Professor Geva's research interests include clustering algorithms, cross language information retrieval, focused information retrieval, information retrieval systems, link discovery mechanisms, search engine technologies, text indexing and retrieval methods, and XML indexing and retrieval techniques. His work demonstrates a consistent focus on improving the efficiency and effectiveness of information access systems across various data formats and domains. His recent publications reveal a trend toward applications of information retrieval techniques in diverse fields including remote sensing, bioinformatics, and data stream processing. The research shows an evolution from traditional information retrieval problems toward more specialized applications requiring advanced clustering algorithms and efficient data processing techniques for large-scale datasets. Professor Geva has successfully supervised numerous doctoral students whose research topics include indoor environment mapping by robots, cross-language information retrieval, natural language query interfaces for XML, evolvable hardware, and autonomous robot behavior systems.
Lecturer in Programming for Data Science at the Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh. Previously taught at the University of Edinburgh Business School and CodeClan bootcamp. Serves as CTO of FeelingGood App (formerly Sorted), with prior roles as Head of Mobile at Storm Ideas and Technology Advisor at Mara Seaweed. Education: PhD in Computer Science/HCI/UX from Heriot-Watt University Research focuses on democratizing programming education for non-technical audiences through innovative pedagogy in data/text mining and natural language processing. His work bridges human-computer interaction with social data science, particularly examining gender equality metrics and diversity impacts in corporate environments. Develops open educational resources emphasizing pair programming techniques and digital credentialing systems to enhance remote learning accessibility. Publication trends reveal a distinct evolution from early textile interface research (2010-2017) toward contemporary data science education and social impact studies (2020-2025). Recent work analyzes pandemic-era teaching adaptations and investigates correlations between workplace diversity metrics and financial performance, while foundational contributions established methodologies for digital textile simulation and haptic feedback systems. Scientific recognition: Highly Commended for Social Responsibility and Sustainability Changemaker 2020-2021 Mentorship and funding initiatives center on community-driven projects rather than traditional grants. Leads the CodeBar.io mentoring scheme supporting LGBTQIA+ and underrepresented groups in tech, develops open-access Python curriculum through Code Storytelling, and coordinates the Pair Programming Network. Commissioned research on gender equality demonstrates industry collaboration, while non-funded projects like the Social Data Science Hub foster interdisciplinary community engagement. Directs multiple volunteer-based initiatives including the Pair Programming Network and CodeBar.io mentoring scheme, with active participation in the RSE Young Academy of Scotland (2020-2025). These efforts prioritize creating inclusive entry pathways into technology through hands-on coding support and open educational resource development.
Roles & Affiliations Professor of Electrical and Computer Engineering at Rutgers University since at least 2001. Active in the Center for Advanced Information Processing (CAIP) and affiliated with the DISCIPLE project focused on mobile collaboration and medical informatics. Education Dipl. Ing., Electrical and Computer Engineering, University of Zagreb, Croatia (1982) M.S., Computer Science, University of Zagreb, Croatia (1987) Ph.D., Biomedical Engineering, Rutgers University (1994) Research Interests Focus on mobile computing , collaborative systems , and medical informatics . Key areas include: - Design of adaptive interfaces for heterogeneous devices - Quality-of-service optimization in networks - Multimodal interaction (voice, gesture, etc.) - Trauma resuscitation process analysis using RFID/sensors - Groupware systems and distributed collaboration frameworks Teaching & Academic Contributions Teaches graduate and undergraduate courses including: - Software Engineering (multiple variants) - Computer Networking - Digital Logic Design - Web Application Development Projects & Labs Leads the DISCIPLE project exploring mobile collaboration and trauma team support systems. Active in RFID-based medical process monitoring and visual attention analysis.
