Daniela Marić Pfannkuchen is a Senior Research Associate at the Ruđer Bošković Institute's Laboratory for Evolutionary Ecology within the Center for Marine Research. Her research focuses on phytoplankton ecology and taxonomy, particularly in the northern Adriatic Sea. She holds a PhD in Oceanology from the University of Zagreb and a Biology diploma from the University of Trieste. Her work integrates traditional ecological methods with molecular techniques like environmental DNA (eDNA) metabarcoding to assess phytoplankton biodiversity and ecosystem health. Key areas include understanding phytoplankton responses to environmental changes, harmful algal blooms, and the impacts of climate change on marine productivity. Recent studies highlight her contributions to long-term phytoplankton monitoring, revealing disruptions in seasonal patterns due to environmental pressures. She leads projects on genomic resources for Adriatic diatoms and collaborates on coastal observatory initiatives. Her findings emphasize the need for advanced monitoring tools to assess dynamic marine ecosystems. Dr. Marić Pfannkuchen actively participates in international conferences, advancing methodologies for eDNA applications and omics-based approaches in marine research. Her team’s work bridges molecular biology with ecological insights, contributing to both fundamental science and practical environmental management strategies.
Ayman M Mostafa is a University of Arizona faculty member serving as Director of the Center for Urban Smart Agriculture (UACUSA) and a Regional Specialist in Entomology for Maricopa Cooperative Extension. He holds a Ph.D. in Entomology from the University of Manitoba. His work focuses on integrated pest management (IPM), urban agriculture, and sustainable crop production, particularly in alfalfa and forage systems. Education: Ph.D. Entomology, University of Manitoba, Canada (Focus: Plant Bugs on Buckwheat and Alfalfa) Research Interests: Alfalfa pest management, including weevils and aphids IPM strategy development for low desert crops Bee health and community pollinator management Urban agriculture needs and extension programs Fertilizer optimization for forage crops His research emphasizes economically viable pest control methods, pesticide resistance monitoring, and sustainable practices for small-scale and urban farmers. Awards: 2025 University of Arizona Cooperative Extension Faculty of the Year Award 2023 Distinguished Achievement in Extension Award (ESA Pacific Branch) 2022 Distinguished Service Award (NACAA) Grants & Advising: Leads programs addressing urban farming challenges, including the Small-Scale and Beginner Farmer Initiative. Collaborates on projects funded by USDA-NRCS and Arizona Department of Agriculture. Labs/Teams: Directs UACUSA, a hub for urban agriculture research and outreach, and coordinates with the Arizona Pest Management Center.
Luis Gravano is a Professor of Computer Science at Columbia University, specializing in databases, information retrieval, and web search. He joined Columbia in 1997 and holds a Ph.D. from Stanford University. His research focuses on scalable information extraction, event detection in social media, and applications of machine learning in public health monitoring. Gravano has advised over a dozen Ph.D. students, many of whom now hold prominent roles in academia and tech industries such as Google and Microsoft. Education: Ph.D. (1997), M.S. (1994) in Computer Science from Stanford University; B.S. (1991) from Escuela Superior Latinoamericana de Informática (ESLAI), Argentina. Research interests span databases, web search systems, and applying computational methods to public health challenges. Notable projects include extracting health-related insights from Yelp reviews and social media to detect foodborne illnesses and outbreaks. He has also contributed to query optimization for hidden-web databases and time-series clustering algorithms. Awards include NSF CAREER Award, multiple best-paper awards at SIGMOD and ICDE conferences, and teaching recognitions from Columbia Engineering. Current roles include teaching Advanced Database Systems (COMS E6111) and leading the Columbia University Database Research Group.
Nikoleta Anicic is a Scientific Collaborator in Vector Ecology at the Department of Environment Constructions and Design (DACD) at the University of Applied Sciences and Arts of Southern Switzerland (SUPSI), where she focuses on monitoring and researching invasive mosquito species and their ecological impacts. Education: PhD in Evolutionary Ecology, University of Namur (Belgium), 2017 Master of Science in Biology with specialization in environmental microbiology and ecology, University of Zurich, 2017 Bachelor of Science in Biology, University of Neuchâtel, 2014 Anicic's research centers on vector ecology with particular expertise in mosquito monitoring and control. Her work combines molecular biology, entomology (specializing in mosquitoes), data management, ArcGIS, and programming in R to address public health challenges posed by invasive species. She has developed specialized skills in high-resolution optical identification of mosquito eggs and spatio-temporal modeling of invasive species dynamics. Her research has direct applications for arboviral disease surveillance and prevention, particularly for diseases like Dengue, Chikungunya, and Zika transmitted by invasive Aedes species. Analysis of her publication record reveals a strong interdisciplinary approach spanning entomology, environmental microbiology, and computational ecology. Her research trajectory shows progression from fundamental ecological studies on subterranean biodiversity and freshwater zooplankton to increasingly applied work on invasive mosquito surveillance. Recent publications demonstrate sophisticated integration of machine learning techniques with traditional ecological monitoring to predict seasonal mosquito population dynamics across multiple European countries. Nikoleta Anicic leads and participates in numerous research projects focused on invasive mosquito surveillance across Swiss cantons (including Zurich, Uri, Glarus, Schwyz, and the Romandy region) and Liechtenstein. These projects involve close collaboration with cantonal environmental offices and national authorities, with SUPSI serving as the national coordination center for invasive species monitoring designated by the Swiss Federal Office for the Environment. Her work directly informs Swiss public health strategies for controlling invasive mosquito species including Ae. albopictus, Ae. japonicus, and Ae. koreicus. At SUPSI, Anicic is a core member of the Vector Ecology Sector (SECOVETT) within the Institute of Microbiology. She contributes significantly to the Swiss mosquito network, providing scientific expertise for developing monitoring protocols, analyzing field samples, and interpreting spatial patterns of mosquito invasion. Her recent presentation at the 26th International Conference on Subterranean Biology demonstrates her continued engagement with broader ecological questions beyond her primary mosquito research focus.
Chao Huang is an Assistant Professor at the Department of Computer Science and Institute of Data Science at the University of Hong Kong (HKU). As the director of the Data Intelligence Lab@HKU, his research focuses on Large Language Models (LLMs), LLM Agents, Graph Learning, Recommender Systems, and AI for Smart Cities. He holds a PhD from the University of Notre Dame. Education: PhD in Computer Science from University of Notre Dame (USA). Research Interests: His work bridges machine learning with practical applications, including: Developing advanced LLM frameworks like GraphGPT and UrbanGPT Creating automated research tools (AutoAgent, AI-Researcher) Designing recommendation systems with LLM integration (RLMRec, LLMRec) Exploring spatio-temporal AI for urban challenges Notable Achievements: Over 11,000 Google Scholar citations (h-index 55), multiple top conference awards (WWW/SIGIR/KDD), and open-source projects with thousands of GitHub stars. His work has been recognized as most influential/pioneering in major AI conferences. Labs/Teams: Leads the Data Intelligence Lab, collaborating on projects like LightRAG, MiniRAG, and VideoRAG. The lab emphasizes open-source contributions with repositories on GitHub. Grants/Advising: Supervises PhD/MPhil students and offers research internships. Active in recruiting motivated researchers and students through HKU's programs.
Dr. Helene Løvstrand Svarva is an Associate Professor at the Norwegian University of Science and Technology (NTNU) Science Museum , specializing in dendrochronology and radiocarbon dating . Her research bridges environmental science , archaeology , and historical climate reconstruction , with a focus on Scandinavian climate history and wooden artifact dating . She has actively participated in collaborative projects involving stave churches and historical manuscripts . Address: Old Physics, 164A, Gløshaugen, Sem Sælands vei 5, Trondheim, Norway Email: helene.svarva@ntnu.no Contact: +47 73593307 / +47 45616923 Her scientific work emphasizes tree-ring analysis for climate proxies, including studies on the Little Ice Age and bomb radiocarbon spikes from nuclear testing periods. She investigates carbon source modeling , cellulose pretreatment methods , and historical timber trade through interdisciplinary projects in archaeology and environmental history . Recent publications highlight her contributions to radiocarbon calibration using Norwegian Pinus sylvestris , analysis of subannual ¹⁴C variability , and dendrochronological dating of medieval structures. She frequently presents at international conferences, including the Radiocarbon Conference and European Geosciences Union meetings. Collaborations with institutions like the ETH Zürich and University of Bern demonstrate her role in European archaeological science networks. Her work often integrates climate history with human activity patterns , as seen in studies on 18th-century agricultural crises and pre-Black Death population trends .
Thomas Nordahl Petersen is an Associate Professor at the Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark (DTU). His research focuses on antimicrobial resistance, metagenomics, and genomic epidemiology, with significant contributions to public health and food safety surveillance systems. Research Interests: Genomic Epidemiology of foodborne pathogens Antimicrobial Resistance (AMR) and the resistome Metagenomic analysis of environmental and clinical samples Mobile genetic elements in AMR transmission Wastewater and livestock-based surveillance Bioinformatics pipeline development for AMR gene detection His recent work involves large-scale metagenomic studies of sewage, livestock, and global AMR spread, leveraging next-generation sequencing for real-time disease monitoring. He leads and supervises multiple PhD projects related to aquaculture, foodborne infections, and resistome dynamics. Scientific Contributions and Trends: Development of ARGprofiler for AMR gene and flanking region analysis Creation of comprehensive datasets like PanRes and MetalResistance Longitudinal studies of AMR in Danish swine production Investigation of co-selection mechanisms in resistomes Application of metagenomics in public health early warning systems Advising and Research Leadership: Main supervisor for PhD projects on global AMR spread and mobile elements Co-supervisor for projects on NGS in foodborne infections and aquaculture monitoring Examiner and collaborator on industrial PhDs in probiotic genomics Active involvement in large consortia such as the EFFORT consortium Laboratories and Collaborations: Research Group for Genomic Epidemiology at DTU Food Collaborations with national and international public health institutions Integration of computational and experimental approaches in AMR research Strong focus on One Health perspectives linking human, animal, and environmental health
Tobias May is an Associate Professor at the Department of Health Technology, Technical University of Denmark (DTU). He holds a binational Ph.D. from the University of Oldenburg and Eindhoven University of Technology, with postdoctoral experience at DTU since 2013. Current academic rank: Associate Professor Department: Health Technology Research focus: Computational auditory modeling, signal processing, and hearing technology Research Interests His work spans computational auditory scene analysis, binaural signal processing, and machine learning applications in hearing instruments. Key contributions include diffusion-based speech enhancement systems and studies on communication in noisy environments. Research aligns with UN SDGs related to health and technology innovation. Supervision Active PhD supervision in projects like Characterizing Listener Behaviour and Robust Speech Enhancement . Collaborates internationally with institutions in Germany, Netherlands, and Denmark. Contact Email: tobmay@dtu.dk | DTU Health Technology Website
Paul MacNeilage is an Associate Professor and Director of the Cognitive & Brain Science Ph.D. Program at the University of Nevada, Reno, Department of Psychology. His research focuses on human spatial orientation, integrating sensory and cognitive processes to understand how we perceive movement and maintain balance during activities like walking, driving, and virtual reality interactions. Ph.D., Vision Science, University of California Berkeley (2007) B.A., Biological Anthropology, Harvard University (1996) Research in his Self-Motion Lab examines visual-vestibular interactions, head motion statistics, and perceptual stability. Key methods include VR motion simulators, head-mounted eye tracking, and computational modeling. Applications span vertigo diagnosis, VR development, and autonomous agent systems. Recent publications highlight his work on sensory conflict detection, dynamic gaze error, and VR sickness mitigation. His lab has developed open-source tools like GazeMetrics and the Visual Experience Database. Grants supporting his research include UNR Neuroscience COBRE, OIA Track-2 FEC and IIS CHS:Small, Nevada NASA Space Grant Consortium, and Transfer Project DT-1 (BCCN Munich).
Halil Bisgin is an Associate Professor in the Department of Computer Science, Engineering, and Physics at the College of Innovation and Technology, University of Michigan-Flint. He holds a PhD in Computer & Information Science (2012) and his research bridges Machine Learning, Cybersecurity, Bioinformatics, and Social Network Analysis . PhD in Computer & Information Science (2012) His work focuses on AI-driven solutions for cybersecurity (malware detection, app privacy), deep learning for biological data (species identification, Alzheimer’s prediction), and social media analysis (Flint Water Crisis causality, political manifesto interpretation). Recent articles examine open-set image classification and generative AI for password security . Scientific awards include the 2025 Provost's Teaching and Innovation Prize and the 2024 Scholarly Achievement Award. He leads NSF-funded projects on cybersecurity education and NIH grants for AI in biomedical procurement systems .
Seth Pettie is a faculty member in the Department of Electrical Engineering and Computer Science (EECS) at the University of Michigan. His research focuses on algorithms, graph theory, distributed computing, and data structures, with significant contributions to problems like minimum spanning trees, Davenport-Schinzel sequences, and energy complexity in radio networks. Research Interests : Algorithms, graph theory, distributed systems, combinatorics, and computational complexity. Students : Mentored numerous PhD students and postdocs, including Dingyu Wang, Shang-En Huang, and Yi-Jun Chang, some of whom have won prestigious awards like the Principles of Distributed Computing Doctoral Dissertation Award. Scientific Contributions : Authored over 15 recent articles (2021–2025) on topics spanning connectivity labeling, fraud detection, extremal combinatorics, and energy-efficient distributed algorithms. His work often bridges theoretical insights with practical applications in databases and network optimization. Awards : Recipient of the Outstanding Dissertation Award (2004) and Best Student Paper Award at ICALP 2002. His students have also received recognition for their work. Professional Service : Organized workshops (e.g., Dagstuhl, Bertinoro) and served on steering/editorial/program committees for major conferences like SODA, STOC, and PODC.
Burkhardt Funk is a full Professor of Business Informatics (especially Data Science) at Leuphana University of Lüneburg. His research spans interdisciplinary applications of data science, including machine learning , digital mental health interventions , and online advertising . University: Leuphana University of Lüneburg Department: Business Informatics Email: burkhardt.funk@leuphana.de Research interests include: Machine learning for digital health (e.g., predicting treatment dropout, analyzing mouse trajectories) Natural Language Processing in therapeutic contexts (e.g., fidelity evaluation in digital CBT) Clickstream analysis and cross-channel advertising (e.g., bid strategies, organic/paid search interactions) Automotive data science (e.g., road elevation measurement using vehicle sensors) Publication trends show a blend of health informatics , marketing analytics , and engineering applications , with recent work focusing on LLMs in education and privacy in digital epidemiology . His projects include KI-basierte Extraktion von Rechnungspositionen and DATAxtended for data literacy education. No explicit scientific awards or student advising details are listed in the provided texts.
Bas Kempen is a PE&RC Research Associate at ISRIC - World Soil Information , part of Wageningen University & Research. His work focuses on Digital Soil Mapping , Tropical Soils , and Machine Learning Applications in soil science. He leads projects like Validatie BVU and contributes to SoilGrids , a global soil data infrastructure initiative. PhD candidate in Digital Soil Mapping (2006-2011) Co-promotor for Mathematical Modeling projects Research highlights include: Transfer functions for nutrient modeling in tropical regions Bayesian statistics for soil health data collection Spatial yield predictions using QUEFTS in Sub-Saharan Africa Development of SoilGrids 2.0 with quantified uncertainty His collaborations span Rwanda, Kenya, India, and Malawi. As Project Leader for BVU validation (2010-2014), he established standardized soil data exchange protocols.
Dennis Calvin is an Associate Dean and Affiliate Researcher at Penn State University's College of Agricultural Sciences . His work focuses on insect-plant interactions , pest management modeling , and climate impact on insect populations , particularly on invasive species like the Spotted Lanternfly and European corn borer. Research Themes : Population dynamics, biological system modeling, climatic uncertainty effects, and sampling technology Key Keywords : Ostrinia nubilalis, Hemiptera, Fulgoridae, Maize, Corn, Integrated Pest Management
Taylor Gogan is a Lecturer in Psychology within the School of Health Sciences at Swinburne University of Technology, where he also earned his PhD in 2022. His academic work spans social and cognitive psychology, with a strong focus on how people form impressions from faces, recognize identity, and perceive trustworthiness and dominance. He is actively engaged in research on public perceptions of facial recognition technology and child protection systems. Research Interests: Social and personality psychology Face and identity perception Public understanding of restorative justice in child protection Procedural justice in investigative interviewing Impact of generative AI on student creativity Cultural logics of dignity, honor, and face His recent publications reveal a consistent trend in examining how contextual, cultural, and perceptual factors shape social judgments. He frequently employs experimental and survey methodologies across diverse populations, including international practitioners and student samples. His work bridges theoretical psychology with real-world applications in law, education, and technology. Scientific Contributions: Pioneered research on how face masks influenced trustworthiness perceptions during and after the pandemic Explored the stability of trait judgments when identity is known Investigated global applicability of the valence-dominance model of face evaluation Examined public misconceptions about restorative child protection practices Assessed the role of AI tools like ChatGPT in enhancing student creativity Taylor Gogan is actively involved in academic supervision, currently guiding a PhD candidate on the topic of justice and child protection. His collaborations span multiple institutions and disciplines, reflecting a highly networked research profile. He has no listed awards in the provided text, but his publication record in high-impact journals such as Nature Human Behaviour and Psychology, Crime & Law indicates strong scholarly recognition. Laboratory and Research Environment: While no formal lab name is mentioned, his research appears to be conducted within cognitive and social psychology research groups at Swinburne, likely involving student researchers and interdisciplinary collaborators in law, criminology, and computer science.
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