Gian-Luca Oppo is Professor of Computational and Nonlinear Physics at the University of Strathclyde and Director of the Institute of Complex Systems. His research spans nonlinear photonics, quantum cavity solitons, Bose-Einstein condensates, and optical pattern formation. Oppo develops theoretical models for laser dynamics, quantum correlations in light sources, and soliton formation in microresonators. Recent work (2024-2025) explores topological photonics applications in frequency combs, polarization symmetry breaking for optical Ising machines, and optomechanical quantum droplet dynamics. He has made fundamental contributions to understanding spontaneous symmetry breaking in Kerr resonators and control of extreme optical events. Oppo's group collaborates internationally on experimental implementations of photonic computing architectures and quantum sensing technologies. Honors include the Occhialini Medal (2011), Royal Society-Leverhulme Senior Research Fellowship (2003), and fellowships from the Royal Society of Edinburgh, OSA, and Institute of Physics.
Jun Li is a Full Professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame's College of Science. He specializes in developing statistical and computational methods for big data, with a focus on interdisciplinary applications in bioinformatics, machine learning, and data mining. His career includes tenure as an Assistant Professor (2012–2017) and promotion to Associate Professor (2017) before becoming Full Professor (2020). Dr. Li holds a Ph.D. in Statistics from Stanford University (2012), supervised by Robert Tibshirani, and earlier degrees from Tsinghua University: a B.E. in Automation (2004) and an M.S. in Pattern Recognition and Intelligent Systems (2007). Research Interests : Dr. Li’s work centers on advancing computational frameworks for handling large-scale datasets, integrating statistical rigor with algorithmic innovation. Recent themes include AI-driven code improvement, ethical LLM applications in HCI, and GUI automation. His methodologies emphasize human-AI collaboration and transparency in algorithmic systems. Publications : His 2025 work explores LLM vulnerabilities in GUI agents, AI-assisted education tools like GLITTER, and ethical challenges in HCI research. Earlier studies (2024–2023) address topics such as natural language database queries, privacy-preserving app promotion analysis, and multimodal task learning. Lab/Teams : Affiliated with Notre Dame’s computational statistics research groups, focusing on interdisciplinary projects bridging statistics, computer science, and applied mathematics. His work often involves collaborations with industry and academic partners to translate theoretical advancements into practical applications.
Rosella Gennari is an Associate Professor in Computer Science at the Faculty of Engineering, Free University of Bozen-Bolzano, where she conducts research and teaches in Human-Computer Interaction (HCI). Her work is centered on designing interactive technologies for children, focusing on physical-digital (phygital) artefacts, Technology-Enhanced Learning (TEL), and inclusive design. She leads the Research Unit Human-Centred Intelligent Systems and is actively involved in institutional leadership, including serving on the Third-Mission Board. Ph.D. : Computer Science, Amsterdam University (2002) Postdoctoral Experience : CWI, Amsterdam (ERCIM Alain Bensoussan Fellow); FBK-irst, Trento Leadership : Scientific & Technological Coordinator of the FP7-EU TERENCE project Her research explores how children interact with and design smart technologies, including IoT and AI, through playful and tangible interfaces. She investigates socio-emotional learning, digital well-being, and responsible design, often employing participatory and action research methods. Her work bridges computer science, education, and social impact, aiming to empower young learners as co-creators of technology. The analysis of her recent publications reveals a strong trend in developing and evaluating toolkits and frameworks for children and pre-teens to engage in designing smart things, IoT systems, and sustainable cities. Her work consistently emphasizes inclusivity, reflection, and responsible design, often in collaboration with teachers and learners. The publications span top HCI venues and journals, demonstrating a focus on practical applications in educational settings and the impact of technology on young users. Scientific Awards and Recognition ERCIM Alain Bensoussan Fellowship for talented young researchers Editorial Board Member, Journal of Child Computer Interaction (Elsevier, Q1) Regular reviewer for top HCI conferences and journals Advising and Grants : While specific advisees are not listed, her leadership role in the FP7-EU TERENCE project and numerous other research initiatives indicates extensive experience in securing and managing competitive grants. She mentors students through her research group and teaching, fostering the next generation of HCI researchers. Her collaborative network is extensive, with frequent co-authorship with researchers such as Alessandra Melonio, Maristella Matera, and Mehdi Rizvi. Labs and Teams : She leads the Human-Centred Intelligent Systems research unit, which serves as her primary lab and team. This group focuses on placing humans at the center of computer science and information engineering research. She is also a core member of the organizing committee for the MIS4TEL international conference series, highlighting her role in building and sustaining a global research community in Technology-Enhanced Learning.
Christopher T. Middlebrook is a Professor of Electrical and Computer Engineering at Michigan Technological University (MTU), with an affiliated appointment in the Physics department. He holds a visiting faculty research engineer position at Scientific Applications International Corporation (SAIC) supporting the DoD Executive Agent for Printed Circuits and has served as visiting faculty at the Naval Surface Warfare Center Crane (2016–2020). His expertise spans integrated optical devices, electronic substrate manufacturing, and photonics. Middlebrook leads the Plexus Innovation Laboratory, a campus electronics maker space, and has pioneered PCB fabrication education through courses and media contributions. Education: PhD in Optics from the University of Central Florida, MS in Applied Optics from Rose-Hulman Institute of Technology, and BS in Electrical Engineering from MTU. His research focuses on electro-optic polymers, optoelectronic integration, and advanced manufacturing techniques. He has published 49 papers, holds two patents, and secured grants totaling over $970K, including the Michigan Economic Development Corporation-funded 'Back-End Semiconductor Curriculum' initiative (2024). Research highlights include developing UV resin printer methods for PCB prototyping, optimizing polymer waveguides, and advancing quantum communication technologies. Awards include the HKN Professor of the Year (multiple years), Michigan Tech Graduate Mentor Award, and IPC Carano Teacher Excellence Award. His work bridges academia and industry, emphasizing hands-on learning and innovation. Key Grants: Back-End Semiconductor Curriculum for Advanced Substrates: $970K (2024) Mesosphere Observation Mission (MOMBO): $38K (2022–2023) Labs/Teams: Plexus Innovation Lab, MTU's Electronics Maker Space Courses Taught: EE2230 PCB Fabrication, EE3190 Optical Sensing, EE5500 Stochastic Processes, and 15+ others emphasizing photonics and optoelectronics.
Dr. Richard Gault is a Lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. His research focuses on computer vision and deep learning applied to microscopy data, particularly in medicine, health, and life sciences. He leads a team developing novel methods for medical image analysis, including histopathology and digital pathology, with applications in cancer diagnosis and environmental science. He is actively involved in teaching, having received Excellence in Teaching awards from Queen's University Belfast in 2019 and 2022. His work bridges computational intelligence and healthcare, with notable contributions to AI-driven diagnostics, stain normalization in histopathology, and multimodal data fusion. Dr. Gault's research interests include ensemble learning, fuzzy systems, and generative models like diffusion networks. He supervises multiple PhD students and has mentored graduates now working in machine learning engineering and postdoctoral research. His team’s achievements include awards such as the 2023 Best Oral Presentation at the Pan Ireland Ophthalmology Day and a 2021 Best Paper Award from his school. Key contributions include the LymphoSight AI application for detecting lymphoid structures and HistoClean , open-source software for improving CNN development in histopathology. He has been recognized as a Senior Member of IEEE and a Fellow of the Higher Education Academy. His work is supported by grants such as the R5131ECI project on 3D quantifier approximation via 2D video analysis (2019–2025). He actively engages in academic activities, including conference organization and PhD external examinations across Europe.
Sebastiano Battiato is a Full Professor of Computer Science at the University of Catania's Department of Mathematics and Computer Science. He serves as Scientific Coordinator of the PhD Program in Computer Science and Deputy Rector for Strategic Planning and Information Systems at the University of Catania. As Director and Co-Founder of the International Computer Vision Summer School (ICVSS), he has significantly contributed to computer vision education globally. Education: Bachelor's degree in Computer Science (summa cum laude), University of Catania, 1995 Ph.D. in Computer Science and Applied Mathematics, University of Naples, 1999 Professor Battiato's research primarily focuses on Computer Vision, Imaging Technology, and Multimedia Forensics . His work spans from developing ISP algorithms for embedded devices to creating advanced techniques for image enhancement, coding, and forensic analysis. He has pioneered research in social media forensics, developing methods to determine if images have been processed through specific social platforms. His research has practical applications in assistive technologies, retail, digital marketing, and medical fields. His scholarly output shows a consistent focus on digital forensics and image processing, with an increasing emphasis on social media forensics in recent years. The research trajectory demonstrates progression from foundational image processing techniques to sophisticated forensic applications capable of addressing modern challenges like deepfakes and social media manipulation. Scientific Awards: 2017 PAMI Mark Everingham Prize for the series of annual ICVSS schools 2011 Best Associate Editor Award of IEEE Transactions on Circuits and Systems for Video Technology Professor Battiato has coordinated IPLab's participation in numerous large-scale research projects funded by national and international bodies as well as private companies. He has served as principal investigator on many international and national research projects, demonstrating strong leadership in securing research funding. His editorial work includes serving as associate editor for the SPIE Journal of Electronic Imaging and IET Image Processing Journal, and membership on several other editorial boards. As Director of IPLab research lab (http://iplab.dmi.unict.it), Professor Battiato leads a team focused on computer vision and digital forensics. The lab collaborates extensively with law enforcement agencies through iCTLAB, a university spinoff he founded that provides digital forensic services. IPLab is recognized for its contributions to image/video forensics, with techniques implemented in commercial forensic software like AMPED Authenticate.
Professor David Taubman is a distinguished academic serving as Professor and Deputy Head of School (Research) at the School of Electrical Engineering and Telecommunications (EE&T) at the University of New South Wales (UNSW) in Sydney, Australia. He is also co-director of Kakadu Software Pty. Ltd. and its affiliates Kakadu R&D and Kakadu GPU. With a career spanning over three decades, Professor Taubman has made significant contributions to the field of image and video compression, most notably as the author of the EBCOT coding algorithm adopted in the JPEG2000 international standard. Professor Taubman earned his B.Sc. in Mathematics and Computer Science (1986) and B.E. (Medal) in Electrical Engineering (1988) from the University of Sydney, followed by an M.Sc. (1992) and Ph.D. (1994) in Electrical Engineering from the University of California at Berkeley. His professional journey includes engineering work at the Electricity Commission of N.S.W. (1988-1990), research positions at Hewlett-Packard Laboratories in Palo Alto (1994-1998), and an academic career at UNSW where he progressed from Senior Lecturer (1998-2003) to Associate Professor (2004-2009) and finally to Professor (2009-present). He has held various leadership roles including Head of the EE&T Telecommunications Research Group (2003-2014), Head of the EE&T Signal Processing Research Group (2014-present), Director of Research for the School of EE&T (2011-2016), and Deputy Head of School (Research) since 2017. Professor Taubman's research interests center on image and video compression, with particular expertise in JPEG2000 standards and implementations. His work spans signal processing, wavelet transforms, scalable video coding, motion modeling, and multimedia systems. He has pioneered numerous compression algorithms and frameworks, including the EBCOT coding algorithm that became central to the JPEG2000 standard. His recent research focuses on efficient motion modeling with cuboidal partitioning, learned lifting-based transform structures, and high-throughput implementations of JPEG2000 for video applications. His work bridges theoretical foundations with practical implementations, as evidenced by the commercially successful Kakadu Software tools that have garnered around 500 commercial licensees. Analysis of Professor Taubman's recent publications reveals a consistent focus on advancing compression technologies with particular emphasis on scalability, efficiency, and adaptability. His work spans traditional image compression (JPEG2000 extensions), video coding (cuboid-based partitioning for UHD/360-degree video), and emerging applications (nanopore sequencing data compression). A notable trend is the integration of machine learning techniques with traditional compression frameworks, as seen in his work on learned lifting-based transform structures. His research maintains strong connections to real-world applications across diverse domains including medical imaging, astronomical data processing, and genomic sequencing. IEEE Fellow Engineers Australia Fellow (by invitation) Professor Taubman has served as Associate Editor for the IEEE Transactions on Image Processing for two four-year appointments (2003-2005 and 2010-2013). He has been actively involved in numerous research grants focused on image and video compression technologies, particularly those related to the JPEG2000 standard and its extensions. His work has received significant industry support, reflected in his consultancy with various U.S., Japanese, and Australian corporations. He has also contributed to international standards development as a member of Standards Australia Technical Committee MS-065 (mirroring ISO TC42 on Digital Photography) and as a constitutional member of Standards Australia Technical Committee IT-029 (Coded Representation of Picture, Audio and Multimedia/Hypermedia Information). Professor Taubman co-directs Kakadu Software Pty. Ltd. and its research affiliates Kakadu R&D and Kakadu GPU, which have developed the commercially successful Kakadu Software tools for JPEG2000. His research group at UNSW focuses on advanced image and video compression techniques, with particular expertise in wavelet-based methods, scalable coding, and motion modeling. The group maintains strong industry connections and has contributed significantly to the development and standardization of image compression technologies worldwide.
Alina Landowska serves as Assistant Professor in the Department of Cultural Studies at the Faculty of Humanities, SWPS University of Social Sciences and Humanities in Warsaw. Her academic profile integrates cultural studies, computational linguistics, and ethics, with significant contributions to understanding moral foundations in digital discourse and technological futures. Her educational background includes degrees in Management and Economics from Gdańsk University of Technology and European Integration from the Pontifical University of John Paul II in Krakow, complemented by international scholarship experiences: SDG Academy (United Nations) Tantur Ecumenical Institute, Jerusalem (University of Notre Dame) Baltic University Program, Uppsala Swedish Institute of Environmental Research, Kalmar Royal Danish Student Fund, Copenhagen Landowska's research investigates cultural evolution through computational discourse analysis, focusing on morality-technology intersections. She pioneers text-mining methodologies to examine moral foundations in social media, anticipatory rhetoric in digital communication, and value-based management frameworks. Her work bridges humanities with data science, analyzing polarization mechanisms and proleptic cues in online environments while exploring cooperation ethics in business contexts. Recent publications demonstrate methodological innovation in mapping technological futures through sentiment/emotion analysis and moral-value detection systems. Her article corpus reveals consistent thematic threads: digital rhetoric analysis (particularly prolepsis functions), moral psychology applications in AI/social media, and cultural evolution studies linking cooperation theory with business ethics. This interdisciplinary approach positions her at the nexus of computational social science and humanistic inquiry. No scientific awards or prizes are documented in her current professional profile. As an educator, Landowska mentors students in discourse analysis methodologies and socio-economic media studies while serving as executive coach with EMCC Poland. Her research leadership extends to co-founding the Institute for Development think tank and representing Employers of Poland at the OECD's Business and Industry Advisory Committee (2016-2018). She previously held vice-presidential roles in the Polish Association of Businesswomen. Landowska maintains active research affiliations with the Humanistic Management Center (University of Lucerne), International Council for Small Business (George Washington University), and ArgDiaP association. Her 2022-2024 tenure with New Ethos Lab advanced dialogue studies in persuasion frameworks, complementing her current work on digital rhetoric's ethical dimensions.
Professor Marios C. Angelides is a full-time faculty member at Brunel University London , serving as Professor of Computing and Divisional Lead within the College of Engineering, Design and Physical Sciences . He leads the Creative Computing Research Group under the Institute of Digital Futures and contributes to the Digital Media department at Brunel Design School. BSc (First Class Honours) and PhD in Computing from the London School of Economics (LSE) Chartered Engineer (CEng) and Chartered Fellow of the British Computer Society (FBCS CITP) His research focuses on Creative Computing , specifically applying Machine Learning , Serious Gaming , and Cognitive Modeling to develop Smart IoT Applications . His work spans autonomous drone fleets for environmental monitoring, cybersecurity middleware for Android systems, wearable technology for lifestyle recommendations, and historical analysis of Alan Turing’s legacy in modern AI. Recent publications highlight trends in deploying Machine Learning for: IoT systems optimization Autonomous aerial/underwater vehicle coordination Deepfake detection using Turing’s Imitation Game Energy allocation in CubeSats via gaming mechanics Scientific recognition includes being Deputy Editor of The Computer Journal and runner-up for the 2016 Oxford University Press Wilkes Award . He has supervised PhD students in topics like Smart Android Middleware for Cybersecurity and Wearable Recommendation Systems , with active involvement in editorial boards and international conferences.
Dr. Martin Kleppmann is an Associate Professor at the University of Cambridge, specializing in local-first software and security protocols . He leads research in distributed systems, focusing on decentralized architectures, collaborative editing tools, and cryptographic methods. As a key contributor to the Automerge open-source project, he bridges academic innovation with real-world applications. Formerly a research fellow at TU Munich (2022–2023) and Cambridge (2015–2022), he has also worked as a software engineer and startup founder, including LinkedIn (acquired 2012). Research Interests span Distributed Systems Security , Conflict-Free Replicated Data Types (CRDTs) , Collaborative Software , and Cryptography . His work addresses challenges in decentralized social networks, privacy-preserving protocols, and efficient data synchronization. Recent projects include Kintsugi (end-to-end encrypted key recovery) and Pudding (private user discovery for anonymity networks). Publications emphasize Collaborative text editing (2025: Eg-walker, 2023: The Art of the Fugue) CRDTs for JSON and trees (2021, 2017) Privacy in decentralized systems (2024: Pudding, 2025: Emission Impossible) Scientific Awards include Gilles Muller Best Artifact Award (EuroSys 2025) Distinguished Paper & Artifact Awards (OOPSLA 2017) Best Presentation Awards (Security Protocols Workshop 2018, PaPoC 2025)
Sebastian Risi is a Professor at the IT University of Copenhagen , where he directs the Creative AI Lab and co-directs the Robotics, Evolution and Art Lab (REAL) . His work bridges computational evolution, deep learning, and collective intelligence for applications in robotics, art, and video game design. His research focuses on self-organizing AI systems that grow or assemble through local interactions, inspired by biological development. Key areas include neuroevolution , neural cellular automata , and generative modeling , with applications in adaptive robotics, game content creation, and damage-resilient AI. Recent publications highlight trends in self-assembling neural architectures (NDPs) and 3D functional machine generation (Minecraft experiments). Awards include ERC Consolidator Grant (2022), Best Paper at FDG’21 , and Google Faculty Award (2019). Scientific Awards : ERC Consolidator Grant (GROW-AI), Best Paper FDG’21, Runner-Up IEEE Games’20, GECCO 2017 Competition Winner, Sapere Aude Grant, Amazon/Google Faculty Awards He advises on projects like GROW-AI (EU-funded), AI-TESTER (game testing), and C2SIM (military systems). Media coverage includes Science , Wired , and Popular Science .
Megan Boler is a Full Professor in the Department of Social Justice Education at the Ontario Institute for Studies in Education (OISE), University of Toronto. She holds affiliate faculty positions at Innis College, the Center for the Study of the United States, Cinema Studies, and the Institute for Women’s and Gender Studies at the same institution. Research focuses on affect, algorithms, and the psychology of micro-targeting in digital propaganda. Current projects include studying emotional expression in social media during elections and developing digital tools against 2SLGBTQI+ hate. Recipient of SSHRC and Canadian Heritage grants for interdisciplinary research on digital dissent and disinformation. Her work spans digital media, democracy, and critical pedagogy, with a strong emphasis on racial and gendered dynamics. Recent publications analyze polarized online discourse and the role of melodrama in political narratives. She has received awards for her contributions to media studies and social justice education. Teaches graduate courses in philosophy, feminist theory, and media studies. Advocates for diverse media diets and privacy measures to counter echo chambers.
Dr. Ava Fatah gen. Schieck is a Professor of Media Architecture and Urban Digital Interaction at The Bartlett School of Architecture, University College London (UCL) , where she has been affiliated since 2001. She teaches in the MSc Architectural Computation program, focusing on embodied interactions and urban digital experiences. Education: ATQ03 - Recognised by the HEA as a Fellow (UCL, 2008) Certificate in Learning and Teaching (UCL, 2007) Master of Science (UCL, 2001) Her research explores the intersection of architecture, digital media, and urban spaces. Key themes include: Mediated spatial experiences in museums and public environments Embodied interactions through dance, movement, and performative design Urban screens and community-centered digital installations Smart city critiques focusing on marginalized communities Pervasive computing's impact on social dynamics Her publication corpus (149+ outputs) predominantly addresses media architecture, HCI, museum technology, and sensory interactions , with recent work emphasizing olfactory interfaces, pandemic urbanism, and heritage digitization. Awards & Honors: Fellow of the Royal Society of Arts (FRSA, 2023) Projects & Grants: As Principal Investigator for the EPSRC-funded 'Screens in the Wild' , she examines networked urban screens for community engagement. She previously led the 'SCREAM' project (UrbanBuzz program) and contributed to EPSRC's 'Urban Design and Pervasive Systems'. She reviews grants for EPSRC, UKRI, SNSF, and other international bodies. She directs research through UCL's Space Research Group and VR Centre for the Built Environment , collaborating globally. As program chair for the Media Architecture Biennale (2012-2020), she fosters interdisciplinary dialogue across architecture, HCI, and interaction design.
Christopher G. Healey is the Goodnight Distinguished Professor of Analytics in the Institute for Advanced Analytics and a Professor in the Department of Computer Science at North Carolina State University. His research spans visualization, data analytics, text analytics, sentiment analysis, machine learning, cognitive psychology, computer graphics, and social media analytics. He has graduated 15 Ph.D. and 26 master's students and secured over $6 million in research funding from agencies including the National Science Foundation, Department of Defense, National Security Agency, Army Research Office, and various industry partners. He has published over 100 peer-reviewed articles and is a senior member of both IEEE and ACM, as well as a member of the NC State Academy of Outstanding Teachers. His research focuses on developing visualization techniques that leverage visual perception to support rapid, accurate, and effective analysis of large, complex datasets. More recently, he has been investigating machine learning for natural language processing and text analytics. His work includes projects on visualizing election results, sentiment estimation for social media, and wildfire narratives using large-scale social media data. His publications demonstrate a strong trend toward integrating machine learning with visualization, particularly for text analytics and social media analysis. He has made significant contributions to visualizing deep neural networks, cyber situation awareness, and pandemic response analytics, showing how visualization can enhance understanding of complex systems and large datasets across multiple domains. IBM Faculty Award (2007, 2008, 2010, 2011, 2012) Senior member, Association of Computing Machinery (ACM) (2007) Senior member, Institute of Electrical and Electronics Engineers (IEEE) (2007) NC State Academy of Outstanding Teachers inductee (2003) National Science Foundation Faculty Early CAREER Award (2001) He has successfully mentored numerous graduate students and secured significant research funding across multiple projects. His work with the Laboratory for Analytic Sciences, National Science Foundation, and Department of Defense demonstrates strong industry and government partnerships. His recent projects focus on visualizing social media narratives, deep neural networks for text understanding, and predictive analytics for large document collections. He leads research groups focused on visualization and analytics, working with teams to develop innovative approaches for data exploration and analysis. His current work continues to push the boundaries of how visualization can be used to enhance understanding of complex data across domains including public health, cybersecurity, and social media analysis.
Can Güler is an Assistant Professor in the Department of Lifelong Learning and Adult Education at the Faculty of Education, Anadolu University, Turkey. Previously, from 2002 to 2023, he served as a Lecturer in the Department of Distance Education at the Faculty of Open Education, Anadolu University. His academic career spans over two decades with continuous contributions to open and distance education systems. His educational background includes: Bachelor's degree in Computer and Instructional Technologies Education, Anadolu University (2002) Master's degree in Distance Education, Institute of Social Sciences, Anadolu University (2007) Ph.D. in Distance Education, Institute of Social Sciences, Anadolu University (2022) Güler's research centers on open and distance learning methodologies, educational technology integration, and instructional material development. He specializes in video-based learning systems, interactive media design, and gamification strategies for enhancing learner engagement. His work addresses practical challenges in digital content creation and accessibility for diverse learner demographics, particularly adult populations. Analysis of his publication trajectory reveals consistent innovation in multimedia applications for distance education, with recent emphasis on generative AI awareness among educators and interactive video transformation techniques. His research frequently employs design-based methodologies and institutional case studies from Anadolu University's open education infrastructure. Scientific Awards: None mentioned in available sources. Advising and Grants: No information provided regarding student supervision or research funding in current documentation.
