Antoine Di Ciacca is a Postdoctoral Researcher and Lecturer at the University of Neuchâtel, affiliated with the Faculty of Science and the Centre for Hydrogeology and Geothermics (CHYN). His research focuses on quantifying interactions between groundwater, surface water, soils, vegetation, and the atmosphere, employing numerical models, remote sensing, and field data. He leads the URBA-SOIL project, investigating urban soil ecosystem services in water and heat regulation. Past roles include a Postdoctoral position at Lincoln Agritech Ltd., New Zealand (2020–2024), and a PhD at SCK CEN (Belgian Nuclear Research Center) and KU Leuven, Belgium (2015–2020). Teaching responsibilities include courses on Soil Physics and Introduction to Hydrology and Hydrogeology within the Bachelor in Natural Systems program. His research interests span hydrology, soil physics, and hydrogeology, with a focus on global change impacts on water resources and ecosystem renaturalization. His work bridges field observations, advanced modeling, and remote sensing to address contemporary environmental challenges. Contact: antoine.diciacca@unine.ch | Office E307, Rue Emile-Argand 11, 2000 Neuchâtel
Karin Schroen is a Full Professor in Food Process Engineering at Wageningen University & Research, focusing on food emulsions, lipid oxidation, and sustainable packaging materials. Her research integrates nanotechnology, colloid science, and membrane processes to develop innovative food systems and biodegradable materials. Her work addresses challenges in food stability, nutrient delivery, and environmental impact through projects like bio-nanocomposite packaging and controlled lipid digestion systems. She supervises multiple PhD candidates and collaborates on interdisciplinary initiatives, including the INSIGHT project for probiotic delivery and food structure design. Key areas include Pickering emulsions, chitin-based nanocomposites, and oxidative stability mechanisms. Her contributions span over 396 publications, with recent emphasis on lipid oxidation dynamics and microfluidics applications.
Dr. Michelle Zhu is a Professor and Associate Director for Faculty and Academic Affairs at the School of Computing, Montclair State University. She previously held roles as Associate Professor and Director of Undergraduate Programs at Southern Illinois University Carbondale. Dr. Zhu holds a Ph.D. in Computer Science from Louisiana State University and a B.S. in Biomedical Engineering from Zhejiang University. Her research focuses on parallel/distributed computing, big data analytics, and high-performance networking, supported by grants from NSF, DOE, and NVIDIA. She has authored over 150 peer-reviewed publications. Education: Ph.D., Computer Science, Louisiana State University (2005) M.Sc., Computer Science, Louisiana State University (2002) B.S., Biomedical Engineering, Zhejiang University (1996) Her research interests span parallel computing architectures, cloud workflow scheduling, and cybersecurity. She has led initiatives integrating computational thinking into STEM education and developed robotics-based learning tools. Her work has been funded through NSF grants such as the $1.1M "Assimilating Computational and Mathematical Thinking into Earth and Environmental Science" project (2017–2022). Dr. Zhu’s articles explore topics like blockchain-based cloud security, GPU-accelerated Gibbs sampling, and edge computing deployment strategies. She actively contributes to academic governance, serving on Montclair State’s Middle States accreditation committee and the University Academic Assessment Council. Key Grants: NSF MRI: Multimodal Collaborative Robot System (MCROS), $321,737 (2021–2024) DOE: Scalable Application Support Platform for E-Sciences, $389,398 (2009–2013) Service Roles: Curriculum Committee Chair, Computer Science Department Blue Ribbon Task Force for Gen Ed Redesign (2019–2020) She collaborates on robotics projects like MCROS and leads outreach efforts to engage pre-university communities in AI and robotics education.
Professor Zhifeng Bao is a faculty member at RMIT University's School of Computing Technologies. His research focuses on enhancing data usability across heterogeneous domains, including structured, unstructured, and spatial-temporal data. His work spans database management, keyword search optimization, social network analysis, and spatio-textual data processing. He coordinates the course COSC1169: Intranet and Internet Data Engineering and supervises PhD/Masters students in projects such as trajectory data processing, data asset valuation, and edge computing optimization. Research interests emphasize improving data accessibility and efficiency through methodologies like query relaxation, visual analytics, and provenance tracking. His recent projects include cost-effective edge node placement, traffic accident risk prediction, and differentially private federated learning. Teaching and supervision activities highlight a commitment to bridging theory and practical data engineering challenges.
Camelia D. Brumar is a PhD Candidate in Computer Science at Tufts University and a Visiting PhD Student at Harvard University's Visual Computing Group. She co-founded Boston Vis , a collaborative network for visualization researchers in the Greater Boston Area. Education: B.S. in Theoretical Mathematics from University of Maryland, College Park Research Focus: Systematic visualization design for decision-making processes, bridging gaps between problem spaces and design spaces through qualitative methods Her work intersects Visual Analytics , Human-Computer Interaction , and Machine Learning , with recent publications on decision-making taxonomies, dimensionality reduction explanations, and knowledge graph visualization. Key trends include: Interactive predicate logic for pattern explanation Domain expert challenges in automated data science Anomaly reasoning frameworks Medical AI applications for embryo grading Scientific Achievements: Organizer of Boston Vis (2024) Tutorial presenter on LLMs for research paper interaction (2024) IEEE Visualization 2024 Doctoral Colloquium participant Contributor to Dagstuhl Seminar on provenance in automated data science (2023) Industry experience includes roles at Tableau Research , Alife Health , and Bose Corporation , with collaborations spanning MIT Lincoln Laboratory, National Renewable Energy Laboratory, and Worcester Polytechnic Institute.
Ahmet Tekalp is a Professor in the Department of Electrical and Computer Engineering at Koc University's College of Engineering since 2001. He holds dual citizenship in Turkey and the USA, with prior academic roles at the University of Rochester (1986-2005) and research positions at Eastman Kodak (1984-1987) and Rensselaer Polytechnic Institute (1981-1984). He chairs the Electronics and Informatics Group at TUBITAK since 2004 as a part-time position. B.S. (1980) in Electrical Engineering & Mathematics, Bogaziçi University M.S. (1982) and Ph.D. (1984) in Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute His research focuses on digital image and video processing, including video compression, motion-compensated filtering for high-resolution applications, video segmentation, object tracking, content-based video analysis, multi-camera surveillance processing, and digital content protection. He has led numerous European and U.S. grants, including FP7 STREP projects and NSF awards, emphasizing applications in sensor networks, visual databases, and medical imaging. His scholarly work spans diverse areas such as superresolution reconstruction, head gesture animation, 3DTV streaming, and reversible data hiding. He has played pivotal roles in editorial boards, including serving as Editor-in-Chief of Signal Processing: Image Communication, and has contributed to major standards bodies like ISO MPEG and ANSI NCITS. Member, Turkish Academy of Sciences (TUBA) Fellow, IEEE Fulbright Senior Scholarship (1999) TUBITAK Science Award (2004) IEEE Signal Processing Society Distinguished Lecturer (1998) He has led multiple international research collaborations and projects, including European FP6/FP7 networks and NATO programs, with substantial grant funding from NSF, NYSTAR, and industry partners like Eastman Kodak, Xerox, and Siemens.
Dr. Sudip Seal is a Joint ORNL-UT Faculty in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, and leads the Systems and Decision Sciences Group at Oak Ridge National Laboratory (ORNL). He holds dual PhDs in Computer Engineering (Iowa State University) and Theoretical High Energy Physics (New Mexico State University). His expertise spans scalable algorithms, AI-driven methods for large-scale science, and high-performance computing. He has led over $55M in multidisciplinary projects and currently leads the FORESEE initiative for extreme-scale computing ecosystems. Education: PhD in Computer Engineering, Iowa State University, 2007 PhD in Theoretical High Energy Physics, New Mexico State University, 2002 Research Interests: Design and optimization of scalable algorithms for extreme-scale scientific computing, AI/ML workloads, parallel simulations, architecture-aware algorithms, numerical methods, computational fusion and materials science, and energy-efficient computing. Awards: Best Paper Award (ACM SIGSIM PADS 2024) Paramount Accomplishment Award (ORNL 2024) Significant Event Awards (ORNL 2017 & 2014) Multiple Best Paper Finalist/Runner-up recognitions (2010–2024) Indian Government Fellowships (NTPC, UGC, CSIR) Leadership & Grants: Principal Investigator (PI) and Co-PI for multi-million dollar projects, including the ExaLearn Co-design Center. Leads ORNL's CCSD LDRD FORESEE initiative. Serves as Associate Editor for the Journal of Parallel and Distributed Computing and chairs major HPC conference committees. Labs/Teams: Systems and Decision Sciences Group (ORNL), collaborating with the Computer Science and Mathematics Division on foundational HPC research.
André Jansson is a Professor of Media and Communication Studies at Karlstad University, Sweden, and Director of the Centre for Geomedia Studies. His research explores media use, identity, and power through an interdisciplinary lens, integrating social phenomenology, human geography, and cultural sociology. He investigates mediatization processes and their impact on social space, focusing on topics like coworking spaces, digital disconnection, and transmedia tourism. Jansson leads major projects funded by the Swedish Research Council and the Ander Foundation, including studies on post-digital work environments and analytical tools for measuring mediatization. Education: PhD (2001) in Media Studies from Gothenburg University; Post-doctoral research at McGill University (2005-06); Docent (2005) at Malmö University; Professor at Karlstad University since 2007. He completed an RJ Sabbatical Grant (2020-21) to complete his monograph Rethinking Communication Geographies . Research interests include geomedia, digital logistics, surveillance culture, and the socio-spatial implications of media technologies. His work bridges communication studies, geography, and sociology, emphasizing critical humanistic perspectives. Editorial roles: Annals of the AAG; Communication and the Public; MedieKultur; and the book series Media Geography . Awards: Member of Academia Europaea (2020-). Key projects include Hot Desks in Cool Places (coworking spaces) and Measuring Mediatization , which develops tools to assess mediatization in everyday life. His recent publications address post-digital workplaces, smartphone morality, and the spatial dimensions of digital reliance.
Bernhard Pucher is a Senior Scientist at the Institute of Sanitary Engineering, Industrial Water Management and Water Pollution Control (SIG), within the Department of Landscape, Water and Infrastructure at the University of Natural Resources and Life Sciences, Vienna (BOKU). He holds a doctorate in technical natural sciences and is actively leading and participating in multiple research projects focused on urban water management and nature-based solutions. His research interests lie at the intersection of urban sustainability and environmental engineering, with a strong focus on urban water management , circular economy , nature-based solutions , treatment wetlands , vertical greening systems , and greywater treatment . His work emphasizes process-based modeling of water and solute transport, particularly using the HYDRUS software, to optimize the design and performance of decentralized water treatment systems. The recent articles highlight a consistent trend in developing and evaluating nature-based technologies for sustainable urban water cycles. Key themes include the performance assessment of vertical and horizontal flow wetlands, numerical modeling for design optimization, the multifunctionality of green walls for cooling and water reuse, and the integration of blue-green infrastructure into circular city frameworks. His research bridges technical modeling with practical implementation, aiming to quantify resource recovery and improve urban resilience. Board member of the IWA national committee Austria (2023) Member of the Management Committee, IWA Specialist Group on 'Wetland Systems for Water Pollution Control' (2019) Active reviewer for journals including Chemical Engineering Journal , Science of the Total Environment , and Water Science and Technology Served on scientific advisory boards for major conferences like WETPOL and IWA ecoSTP He has supervised numerous master’s theses on topics such as greywater use for vertical greening, treatment performance of living walls, and modeling of rainwater use. His projects are funded by diverse sources including the European Commission (Horizon), FFG, national companies, and private foundations, demonstrating strong grant acquisition capability. He is also involved in knowledge transfer through public reports, media contributions, and participation in policy-relevant seminars. Bernhard Pucher is a key member of a research team that includes collaborators like Günter Langergraber, Ulrike Pitha, and Isabella Zluwa. His work is often conducted within interdisciplinary projects such as 'resilientRAIN', 'UrBan hEat islands REsilience', and the EU COST Action 'Circular City Re.Solution', reflecting a collaborative approach to addressing complex urban environmental challenges.
George N. Karystinos is currently a Professor and Dean of the School of Electrical and Computer Engineering at the Technical University of Crete , Greece. He joined TUC in 2005 and was promoted to full Professor in 2019. His academic journey began with a Ph.D. in Electrical Engineering from SUNY Buffalo (2003) and a Diploma in Computer Engineering and Science from the University of Patras (1997). Specialty: Communication theory, coding theory, adaptive signal processing Key research areas: Wireless communications, signal waveform design, L1-norm principal component analysis Leadership: Dean of School of ECE (2021–present) His work focuses on noncoherent detection for RFID/IoT systems and L1-norm PCA for robust signal processing. Recent publications explore power line communication and low-complexity sequence detection . Scientific Awards: 2003 IEEE Transactions on Neural Networks Outstanding Paper Award 2001 IEEE ICT Best Paper Award 2018 IEEE MOCAST Best Student Paper Award 2015 IEEE ICASSP Best Student Paper Award 2013 IEEE ISWCS Best Paper Award 2011 IEEE RFID-TA Second Best Student Paper Award He is affiliated with the Telecommunications Laboratory at TUC and has supervised award-winning research in wireless systems and signal processing.
Shueng-Han Gary Chan is a faculty member in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), within the College of Engineering. He is actively engaged in research and mentoring, with a strong publication record in mobile computing, indoor localization, and AI for pervasive systems. His research focuses on indoor localization using Wi-Fi, geomagnetic, and inertial signals , sensor fusion , crowd counting with deep learning , domain adaptation , and efficient mobile AI systems . His work bridges theoretical innovation with real-world deployment, as seen in systems for missing person search and indoor navigation. Recent publications (2023–2025) show a consistent trend toward self-supervised and domain-agnostic learning , efficient model design for mobile devices , and robust signal fusion in noisy environments . His team leverages transformer architectures, graph neural networks, and novel optimization techniques to solve real-world challenges in urban and indoor spaces. He has advised numerous graduate students, including Jierun Chen, Zhuoxuan Peng, and Tianlang He, who have contributed as first authors to joint publications. His collaborations span institutions and include work on large-scale system deployments and mobile AI. He leads a research group focused on mobile and pervasive computing , with projects involving IoT-based contact tracing, indoor navigation (e.g., DeepNavi, SiFu), and real-time localization systems. The team emphasizes practical deployment and system robustness.
Włodzimierz Kasprzak is a Professor at the Institute of Control and Computation Engineering, Faculty of Electronics and Information Technology, Warsaw University of Technology. His research focuses on computer vision, robotics, human-computer interaction, and machine learning. He has contributed to advancements in human action classification, skeleton-based feature analysis, and multimodal interface design. Research Highlights: Development of lightweight classification models for human actions in video using skeleton-based features. Advances in multi-stream fusion techniques for image and video analysis. Design of embodied agent systems for cybersecurity event visualization and control. Awards and Recognition: 2024: Individual First Class Rector's Award for Scientific Achievements (2022-2023) 2021: Medal of the Commission of National Education 2011: Golden Cross of Merit His work integrates theoretical contributions with practical applications in robotics, surveillance systems, and human-centered technologies.
Sivan Sabato is an Associate Professor at McMaster University's Department of Computing and Software , a Canada CIFAR AI Chair, and faculty member at the Vector Institute of Artificial Intelligence . She holds a joint appointment at Ben-Gurion University's Department of Computer Science while on leave. Her research focuses on machine learning theory, active learning algorithms , and fairness in machine learning . Education: PhD in Computer Science, Hebrew University of Jerusalem Postdoctoral Fellowship, Microsoft Research New England Her theoretical work develops interactive learning frameworks that optimize information costs through algorithmic interaction patterns. Recent publications emphasize differential privacy and discriminative feature analysis with applications to healthcare and social data. She serves as Action Editor for Journal of Machine Learning Research and organizes conference tracks including ICML 2022-2023 and ALT 2021 . Awards include the Alon Scholarship and Google Anita Borg Memorial Scholarship . Advising: Actively supervises Computer Science PhD and MSc students through McMaster's Faculty of Engineering. Research interns can apply via the Vector Institute program with Summer 2026 opportunities.
Hongxin Hu is a Professor and Associate Chair in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York (SUNY). His research spans security, networking, and machine learning, with publications across top conferences including security (S&P, CCS, USENIX Security, and NDSS), networking (SIGCOMM and NSDI), machine learning (NeurIPS, ICML, and EMNLP), and human-computer interaction (CHI and CSCW). His work has been funded by NSF (SaTC, CNS, IIS, OAC, SOC), USDOT, VMware, Amazon, Google, and Dell. Dr. Hu earned his PhD in Computer Science and Engineering from Arizona State University in 2012. His academic journey has led him to become a prominent researcher in cybersecurity with a strong publication record and significant research impact. Dr. Hu's research interests encompass a wide range of topics at the intersection of security, networking, and artificial intelligence. His work focuses on Emerging Network Technologies and Security (5G/Future-G, NFV, SDN, Edge computing), Machine Learning for Security and Privacy , Security and Privacy in IoT and Cyber-Physical Systems , and AI for Social Good (addressing online abuse, unsafe children's games, and cyberbullying). His interdisciplinary approach has enabled him to tackle complex security challenges through innovative solutions that combine networking expertise with machine learning techniques. His recent publications demonstrate a strong trend toward applying large language models and advanced machine learning techniques to security challenges, particularly in content moderation, vulnerability detection, and privacy protection. The research spans multiple domains including voice assistant security, IoT security, network security, and social media safety, showing a consistent pattern of addressing real-world security problems with cutting-edge technical approaches. IEEE Big Data Security Senior Research Award (2025) ACM SACMAT Test-of-Time Award (2024) NSF CAREER Award (2019) Multiple Best Paper Awards from ACM ASIACCS (2022), ACSAC (2020), IEEE ICC (2020), and ACM SIGCSE (2018) Amazon Faculty Research Award (2022) First Place Award in ACM SIGCOMM 2018 Student Research Competition Dr. Hu has successfully advised multiple PhD students, including Nishant Vishwamitra who joined UT San Antonio as a tenure-track Assistant Professor. His research has been generously funded by major agencies and industry partners. As an active member of the academic community, he serves as Associate Editor for IEEE Transactions on Dependable and Secure Computing and Computers & Security, and has held numerous leadership roles in major security conferences including TPC Co-Chair for ASONAM 2025 and IWSPA 2024/2025. Dr. Hu leads a vibrant research group that has produced significant contributions in network security function virtualization, intrusion detection systems, and privacy-preserving technologies. Current projects include developing LLM-assisted vulnerability detection systems, defenses against jailbreak attacks on large language models, and security mechanisms for emerging networking technologies. His team's work on IoT security, voice assistant applications, and online content moderation has received wide recognition and press coverage.
Antonio Maria Gonzalez Colas is a Full Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the Faculty of Computer Science of Barcelona (FIB). He leads the ARCO research group focused on Microarchitecture and Compilers and is actively engaged in high-impact research in computer architecture, GPUs, and energy-efficient computing. His collaborations extend to the Barcelona Supercomputing Center and various national and European research initiatives. Research Interests: His primary research areas include computer architecture, microarchitecture, compilers, GPUs, and processor design. He focuses on energy-efficient computing, deep neural network (DNN) accelerators, GPU simulation and optimization, memory systems, and architectural support for machine learning and autonomous systems. His work often integrates compiler techniques with hardware design for performance and efficiency. Scientific Production Trends: His recent publications demonstrate a strong focus on energy-efficient hardware for AI workloads, particularly DNN and speech recognition acceleration, GPU architectural innovations, memory optimization, and real-time rendering. He frequently publishes in top-tier venues such as ISCA, MICRO, HPCA, and IEEE/ACM journals. ICREA Academia Award 2024 HiPEAC 2024 Paper Award ACM Senior Member (2020) Advising and Grants: He has advised numerous PhD students whose theses cover topics like energy-efficient architectures for autonomous driving, speech recognition, and neural networks. He leads competitive R&D projects, including an ERC Advanced Grant and projects funded by the Spanish National Program and the ICREA Academia program, focusing on domain-specific architectures and cognitive computing units. Labs and Teams: He is the principal investigator of the ARCO (Microarchitecture and Compilers) research group at UPC, a leading team in computer architecture research in Spain. The group is part of a larger collaborative network within UPC and with international partners.
