Josh Reiss is a Professor of Audio Engineering at Queen Mary University of London (QMUL), part of the School of Electronic Engineering and Computer Science . He holds additional roles including President-Elect and Fellow of the Audio Engineering Society (AES), and Visiting Professor at Birmingham City University. His research focuses on audio signal processing, procedural audio, and intelligent music production. He earned degrees including BSc in Physics, BSc in Mathematics, and a PhD. Research & Awards : Reiss has published over 200 papers, authored books like Intelligent Music Production , and received awards such as the AES Board of Governors Award (2009, 2010) and Best JAES Paper 2016. His work spans sound synthesis, dynamic range compression, and live audio systems. Teaching & Industry : Teaches modules like Artificial Intelligence and Sound Design. Co-founded startups LandR (AI mixing), Tonz, and Nemisindo. Leads the Centre for Digital Music at QMUL, advancing research in audio technology. Labs & Teams : Active in the Centre for Digital Music, collaborating on projects like the Open Multitrack Testbed and semantic audio evaluation tools.
Dr. Apostolos Georgakis is an Associate Professor in Electrical and Electronic Engineering at the School of Computing and Engineering, University of West London (UWL). He joined UWL in 2017 after serving at King’s College London’s Division of Engineering. His academic role involves teaching and research in engineering with a strong focus on signal processing and biomedical applications. University: University of West London School: School of Computing and Engineering Department: Department of Electrical and Electronic Engineering Academic Rank: Associate Professor Email: apostolos.georgakis@uwl.ac.uk Dr. Georgakis holds an MSc in Mathematics and Statistics and a PhD in Engineering. His research interests center on biomedical signal processing, audio engineering, and medical diagnostics using advanced signal analysis techniques. He has made significant contributions to the fields of electroglottography for vocal tract pathology detection and heart rate monitoring via tracheal audio signals. His work bridges engineering with healthcare applications, particularly in non-invasive monitoring and diagnostic systems. His recent publications (2022–2024) demonstrate a clear trend toward applying digital signal processing and machine learning methods to medical diagnostics. Topics include laryngeal pathology detection using MFCC/GTCC features, systematic reviews on electroglottography, and automatic heart rate estimation during sleep. Earlier works (2014–2015) focus on theoretical signal restoration and denoising techniques using fractional Fourier transforms and mask operations, showing a strong foundation in mathematical signal processing. A 2019 publication also highlights his interdisciplinary work in thermal engineering involving liquid desiccant systems. Dr. Georgakis teaches across multiple programs, including: MSc Electronic and Robotic Engineering BEng (Hons) Electrical and Electronic Engineering (with and without Foundation Year) BSc (Hons) Sound Engineering (with and without Foundation Year) BSc (Hons) Mathematics and Statistics (with and without Foundation Year) MSc Digital Audio Engineering PhD Engineering While no specific scientific awards are listed, his sustained publication record in high-impact journals such as Digital Signal Processing , Signal Processing , and MDPI Diagnostics reflects active research engagement. He collaborates with researchers internationally, particularly in biomedical signal analysis and veterinary monitoring. Dr. Georgakis advises postgraduate students and supervises PhD candidates in engineering disciplines, though specific student names are not listed. He has not received mention of external research grants in the provided text, but his involvement in applied research suggests potential grant-funded projects. His work in wireless acoustic sensors and medical diagnostics may involve future expansion into wearable health technologies and AI-driven diagnostic tools. There is no mention of a dedicated lab or research team in the provided text, but his research themes suggest potential affiliation with biomedical engineering or audio signal processing groups within the School of Computing and Engineering at UWL.
Professor Anne Flanagan is a faculty member at Queen Mary University of London's School of Law, affiliated with the Centre for Commercial Law Studies (CCLS). She holds academic positions as Professor of Communications Law, with expertise spanning telecommunications law, data protection, and internet law. Her professional background includes legal practice in New York and roles in the financial services sector. Education: BA, JD, LLM. She teaches courses on IT Law, Internet Law, and European Communications Law, both on-campus and through distance learning platforms. Research Interests: Her work focuses on communications law, copyright, privacy/data protection, competition law, freedom of information, and e-government. She contributes to projects like EU data protection training initiatives and collaborates with institutions such as the Institute of Computer and Communications Law (ICCL). Publications: Key works include analyses of internet law, computer crime legislation, and cross-border data regulation. Her scholarship bridges legal frameworks with evolving technological challenges. Professional Engagements: Former Senior Counsel at TIAA-CREF, advising on IT divisions, and licensed attorney in New York State.
Associate Professor Myfany Turpin is an Associate Dean of Indigenous Strategy and Services at the Sydney Conservatorium of Music, University of Sydney. Her research focuses on ethnomusicology, linguistics, and ethnobiology, with a particular emphasis on Central Australian Indigenous cultures. She collaborates extensively with Indigenous communities to document and revitalize endangered languages and performance traditions. Education & Research: PhD in Musicology (2005) Specialization in Kaytetye and Warlpiri language documentation Leader of ARC-funded projects investigating dingo lexicon and traveling songs Research Interests: Turpin explores intersections between language and music, including poetic meter in Aboriginal song-poetry and biocultural knowledge embedded in ceremonial practices. She develops innovative tools like the Kaytetyemoji app to support language revitalization. Grants & Collaborations: ARC Discovery Project (2025-2028): Dingo Lingo ARC Indigenous Discovery Project (2024-2029): Recirculating Travelling Songs Modularised Cultural Heritage Archives (2022-2024) Awards: Received Honorable Mention from International Council for Traditional Music (2021) for work on Warlpiri seed ceremonies. Labs & Teams: Co-director of Sydney Southeast Asia Centre and member of Charles Perkins Centre. Collaborates with Batchelor Institute and Australian Institute of Aboriginal and Torres Strait Islander Studies.
Marie Hay is a Senior Lecturer in Dance at De Montfort University (DMU), affiliated with the School of Humanities and Performing Arts within the Faculty of Arts, Design and Humanities. She is a key member of the Centre for Interdisciplinary Research in Dance (CIRID), the Institute of Drama, Dance and Performance Studies, and the Institute of Creative Technologies (IOCT). As Programme Leader for undergraduate dance programmes, she plays a central role in curriculum development, outreach, and advancing decolonising initiatives in dance education. Her educational background includes a BA (Hons) in Contemporary Dance, an MA in Dance, and a PGCertHE, all from DMU. She was awarded the DMU Teacher Fellow in 2011 and is a Fellow of the Higher Education Academy. Marie's research centers on the integration of speech and movement in contemporary dance, exploring themes of being, identity, and self-disclosure through her innovative 'speakingdance' practice. Her work bridges philosophy, performance, and pedagogy, with a strong focus on autonomy, embodiment, and feminist perspectives. She has developed frameworks for autonomous learning and assessment that have been applied across dance and media technology, influencing both higher and secondary education. The 15 most recent articles reflect a deep engagement with interdisciplinary inquiry, combining dance, philosophy, education, and somatic practices. They reveal consistent exploration of ontology, autobiographical performance, and pedagogical innovation, often grounded in Heideggerian thought and practice-based research methodologies. DMU Teacher Fellow (August 2011) Fellow of the Higher Education Academy (2006 – present) Marie has led multiple internally and externally funded research projects, including those supported by the Centre for Excellence in Performance Arts, Research in Teaching Awards, and PALATINE. She has supervised research students and collaborated with colleagues such as Dr. Lucy Mathers. Her consultancy includes advising Babington College on feedback strategies and serving as an assessor for the BBC Performing Arts Fund. She has also contributed as a reviewer for academic conferences and journals. She is actively involved in research groups such as CIRID, IOCT, and the Institute of Drama, Dance and Performance Studies, where she contributes to interdisciplinary collaborations, performance events, and knowledge exchange. Her international performances and teaching engagements—in Prague, Croatia, Beijing, and London—demonstrate the global reach of her artistic and scholarly practice.
Zijian Diao is an Associate Professor in the Department of Mathematics at Ohio University's College of Arts and Sciences, where he contributes to both teaching and research. He is based at the Eastern Campus in Shannon Hall and teaches a wide range of undergraduate mathematics courses. Education: Ph.D. in Mathematics, Texas A&M University, 2001 M.S. in Computer Science, University of Illinois, 2003 B.S. in Automation, University of Science and Technology of China, 1996 His research spans interdisciplinary areas with a strong focus on quantum computation and information theory , where he has made contributions to Grover's algorithm, quantum counting, and quantum circuit design. He has also worked in natural language processing , particularly in multilingual speech-to-speech translation systems like MARS. Additional interests include control theory , partial differential equations , and mathematical modeling . His recent and ongoing publications reflect a blend of theoretical mathematics and applied computational science. The works trend toward quantum algorithms and foundational mathematical proofs, with earlier contributions in NLP and control systems. His research bridges pure mathematics with practical implementations in quantum computing and language technologies. Scientific Awards: Ohio University Regional Higher Education Outstanding Professor Dr. Diao advises undergraduate and graduate students in mathematics and related fields, though specific student names are not listed. He has been involved in research projects supported by academic grants, particularly in quantum computing and interdisciplinary technology development. His curriculum vitae indicates sustained scholarly activity across multiple domains. He is associated with research groups and collaborations in quantum computing, having co-authored works with G. Chen, C. Huang, and others. His work in NLP was part of larger team efforts involving researchers from industry and academia, suggesting active participation in collaborative technical teams.
Zhiyi Huang is an Associate Professor of Computer Science at the University of Hong Kong, leading the Computer Science Division within the School of Computing and Data Science. He holds a PhD from the University of Pennsylvania (2013) and completed a postdoctoral fellowship at Stanford University (2013–2014). His research focuses on Theoretical Computer Science, Algorithmic Game Theory, Online Algorithms, and Differential Privacy, with notable contributions to Machine Learning and Computer Networks. Education: PhD in Computer and Information Science, University of Pennsylvania (2013) Postdoctoral Researcher, Stanford University (2013–2014) Bachelor's Degree from the Yao Class at Tsinghua University (2008) Research interests span foundational areas including algorithmic game theory, online optimization, and privacy-preserving mechanisms. He has pioneered work on revenue maximization in single-parameter settings and developed novel frameworks for analyzing price of anarchy in game theory. Key Awards: Early Career Award (Research Grant Council of Hong Kong, 2014) Best Paper Award at ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2015) Morris and Dorothy Rubinoff Dissertation Award (2013) Simons Graduate Fellowship in Theoretical Computer Science (2012–2013) Recent grants include studies on algorithmic foundations of Bayesian mechanism design (HK$675,647), online primal dual techniques (HK$496,028), and privacy-preserving mechanisms (HK$931,737). His work bridges theoretical advancements with practical applications in healthcare, autonomous systems, and cybersecurity. Notable Projects: Medical predictive systems for acute cardiopulmonary events AI-driven maritime navigation using AIS data Secure federated learning frameworks with blockchain
Per Bækgaard is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), specializing in Cognitive Systems. He serves as Head of Study for Human-Centered Artificial Intelligence, leading research in human-computer interaction, user experience, eye tracking, and cognitive neuroscience. His work bridges AI and human cognition to create systems that enhance daily life and support meaningful tasks. PhD, MSc EE, Technical University of Denmark His research interests center on Human-Computer Interaction (HCI) , User Experience , and Human-Centered Artificial Intelligence , with strong emphasis on Eye Tracking , Cognitive Neuroscience , and Digital Media . He explores how digital systems can adapt to users’ cognitive states using physiological signals like pupil dilation and gaze patterns, aiming to improve learning, health, and decision-making. His work aligns with UN Sustainable Development Goals in health and education. The recent publications reflect a strong trend in integrating eye tracking and pupillometry with AI-driven adaptive systems , particularly in education and healthcare. Themes include generative AI in learning , trustworthy AI in supply chains , and digital micro-interventions for mental health . The interdisciplinary nature spans computer science, psychology, and biomedical engineering, showcasing a cohesive focus on human-centered technology evaluation. Scientific Awards: Best Paper Award, 26 Jun 2020 – for contributions to gaze interaction research Per Bækgaard actively supervises PhD students and leads multiple research projects, including those involving generative AI in education , digital phenotyping , and AI in nursing and mental health . He is the main supervisor for several PhD projects and a co-supervisor or examiner in others, demonstrating a strong commitment to academic mentoring. His grant involvement includes projects funded by DTU and collaborative research initiatives in digital health and AI. He is part of the Cognitive Systems group at DTU, contributing to interdisciplinary research in AI, neuroscience, and human factors. His team collaborates on projects involving real-time physiological monitoring, adaptive interfaces, and AI-mediated learning systems, positioning him at the forefront of human-centered AI research in Scandinavia.
Zurich University of Applied Sciences (ZHAW)Switzerland
Leo Wanner is a prominent Professor at Universitat Pompeu Fabra's Department of Information and Communication Technologies, specializing in Natural Language Processing. With a research career spanning over three decades, he has made significant contributions to computational linguistics, particularly in natural language generation, collocations, and hate speech detection. He has served as editor for multiple editions of the International Conference on Computational Linguistics (COLING) including the 2025 edition. Wanner's research interests encompass a wide range of topics in computational linguistics, with recent work focusing on hate speech detection, multilingual processing, and the capabilities of large language models. His work bridges theoretical linguistics with practical applications, addressing challenges in lexical semantics, syntax, and discourse analysis. Notably, he has pioneered research in collocation processing and has contributed to the development of frameworks for analyzing thematic progression in texts. His publication record demonstrates consistent productivity with significant contributions across multiple subfields. Recent work shows a strong focus on contemporary challenges in NLP, particularly hate speech detection and the capabilities of large language models. His research often takes a multilingual perspective, addressing challenges across different language families including Romance and Slavic languages. Wanner has led significant research projects including the development of FORGe, a multilingual deep sentence generator based on the Meaning-Text Theory, which achieved top performance in the WebNLG challenge. His work on multilingual surface realization has established important benchmarks in the field through shared tasks that have engaged researchers worldwide. As an academic leader, Wanner has mentored numerous researchers and contributed to building research infrastructure through corpus development and annotation schema design. His work on collocation resources, thematic progression analysis, and hate speech detection frameworks has provided valuable resources for the broader NLP community.
Barry Haddow is a Senior Research Fellow at the Institute for Language, Cognition and Computation (ILCC) within the School of Informatics at The University of Edinburgh. With over 15 years of research experience, he coordinates major international projects in machine translation and natural language processing, including HPLT (Horizon Europe) and Utter (Horizon Europe). His work spans both theoretical and applied aspects of language technology with significant impact on multilingual systems. Haddow's research focuses on machine translation, particularly addressing challenges in low-resource languages, multilingual models, and speech translation. His recent work demonstrates a strong shift toward leveraging large language models for translation tasks while investigating their limitations in cross-lingual settings. He has made significant contributions to understanding how to adapt general language models for specialized translation scenarios and evaluating their performance across diverse language pairs. Analysis of Haddow's recent publications (2023-2025) reveals a clear research trajectory focusing on the intersection of large language models and machine translation. His work examines how to effectively adapt LLMs for translation tasks, investigates evaluation methodologies for multilingual systems, and develops techniques for improving translation quality across diverse language families. A notable trend is his focus on practical applications of these technologies in real-world settings, including financial language processing and speech translation systems. Haddow has coordinated multiple major European research projects including HPLT (2022-2025), Utter (2022-2025), GOURMET (2019-2022), ELITR (2019-2022), and HIML (2015-2018), securing substantial research funding from Horizon Europe and other sources. His work has established him as a leading figure in the machine translation community, regularly contributing to major shared tasks like WMT (Conference on Machine Translation). As a core member of the Institute for Language, Cognition and Computation at Edinburgh, Haddow collaborates closely with the Language Technology Group. His research directly contributes to the institute's mission of advancing computational approaches to human language processing, with particular emphasis on developing technologies that can operate effectively across the world's diverse languages.
Bjorn Ross is a Lecturer in Computational Social Science at the School of Informatics, University of Edinburgh. He is affiliated with the Institute for Language, Cognition and Computation and actively contributes to the Computational Social Science research area. He serves as Director of the SMASH research group and is part of the management team for the Centre for Doctoral Training in Natural Language Processing (CDT in NLP). Education: PhD, 2019, University of Duisburg-Essen MSc in Computer Science, 2016, University of Münster Exchange year, 2014–2015, University of Strasbourg BSc in Information Systems, 2013, University of Münster His research focuses on computational methods for analyzing social media, particularly using natural language processing, social network analysis, and agent-based modeling. Key interests include misinformation, hate speech, social bots, and the ethical implications of automated systems. He emphasizes fairness, bias, and data ethics in AI applications. His recent publications span topics such as queerphobic bias in sentiment analysis, explainable hate speech detection, temporal generalizability in misinformation models, and cross-lingual bias amplification. These works appear in leading venues including ACL, ICWSM, Social Science Computer Review, and Big Data & Society, reflecting a strong interdisciplinary focus bridging computer science, social science, and ethics. Scientific Awards: Best Paper Award, Electronic Government track, HICSS 2018 Ross supervises multiple PhD students and welcomes new applicants. He has also contributed to software tools and web-based platforms for argument analysis and counterspeech. He is an Associate Editor for Business & Information Systems Engineering and a member of AIS, ACL, and ACM. His teaching includes courses on Text Technologies for Data Science and digital persuasion. He leads the SMASH group, which focuses on social media analytics and societal challenges, and collaborates extensively within the CDT in NLP and the Institute for Language, Cognition and Computation.
Hiroshi Shimodaira is a Senior Lecturer in the School of Informatics at The University of Edinburgh, where he has been a faculty member since September 2004. He is affiliated with the Centre for Speech Technology Research (CSTR) and the Institute for Language, Cognition and Computation, contributing to interdisciplinary research in speech and language technologies. His research focuses on lifelike conversational agents with personalities, speech recognition (particularly acoustic models), character recognition, machine learning, and medical-image processing. He is particularly known for his work on anthropomorphic spoken dialogue agents and the development of the Galatea toolkit, an open-source software framework for lifelike conversational agents. His interests also extend to support vector machines and optimization techniques in pattern recognition. The recent publications and projects indicate a strong emphasis on machine learning applied to speech and character recognition, with a trend toward developing intelligent, interactive systems that emulate human conversational behavior. His work bridges theoretical machine learning with practical human-centered applications. Acoustics Society of Japan IEEE Signal Processing Society Japanese Society for Artificial Intelligence (JSAI) IPSJ (Information Processing Society of Japan) Dr. Shimodaira has advised PhD students and led several research initiatives, including the Galatea Project for anthropomorphic dialogue agents and work on handwriting-based communication for the visually impaired. He was previously a co-director of the Intelligent Information Processing Laboratory at JAIST, indicating a sustained record of research leadership. While no specific grants are listed, his project pages suggest involvement in funded research efforts. He leads and contributes to research groups such as CSTR and HCRC, and his lab work focuses on spoken dialogue systems, lifelike agents, and machine learning applications in speech and vision. The Galatea project represents a major software and research output from his team.
Dr. Krister Linden is a Research Director at the University of Helsinki ’s Department of Digital Humanities under the Faculty of Arts. He is the National Coordinator for FIN-CLARIN and supervises doctoral research, including Rosa Suviranta’s PhD thesis. Research Interests include language technology applications, digital humanities focused on Ancient Near Eastern Empires, science policy, and development of language resources infrastructure. He leads the Language Bank of Finland and participates in EU projects like FIN-CLARIAH and LAREINA. Active in computational linguistics and NLP Contributes to research infrastructures Works on Akkadian text analysis Organizes international conferences Recent Projects include coordination of the Business Finland-funded BF LAREINA (2023–2025) for Finnish speech corpus analysis and leadership in the Digital Europe Programme’s Open European Family of Large Language Models (2025–2028).
Dr. Elena Abrusci serves as Senior Lecturer in Law at Brunel Law School within Brunel University London's College of Business, Arts and Social Sciences, joining in 2021 after impactful roles including Policy Advisor on Digital Regulation at the UK Department for Digital, Culture, Media and Sport and Senior Research Officer at the University of Essex's ESRC-funded 'Human Rights, Big Data and Technology Project'. Her interdisciplinary expertise bridges law and politics with significant contributions to modern slavery research through the Rights Lab and Walk Free Foundation. Her academic credentials feature a PhD in Law from the University of Nottingham (awarded Vice-Chancellor Scholarship for Research Excellence), Postgraduate Advanced Diploma in Politics from Sant'Anna School of Advanced Studies (Honor Fellow), MA in International Relations from the University of Florence and Sciences-Po Paris, and BA in Politics and International Relations from the University of Pisa. Dr. Abrusci's research critically examines regional human rights systems alongside technology's impact on fundamental rights, with particular focus on AI governance, online disinformation/misinformation, hate speech regulation, and digital platform accountability. Her work consistently analyzes how emerging technologies challenge traditional human rights frameworks while proposing regulatory solutions for democratic participation. Analysis of her 2017-2024 publications reveals evolving scholarly attention from judicial convergence in regional human rights systems toward contemporary digital governance challenges, with increasing emphasis on automated decision-making, content moderation frameworks, and cross-jurisdictional regulatory comparisons between EU/UK legislation. Scientific recognition includes: Vice-Chancellor Scholarship for Research Excellence (University of Nottingham) Honor Fellow designation at Sant'Anna School of Advanced Studies She actively supervises PhD candidates in regional human rights systems, human rights technology intersections, and AI governance, while contributing to major research initiatives including the ESRC-funded 'Human Rights, Big Data and Technology Project' and Walk Free Foundation's Global Slavery Index. Her consultancy for UN agencies (WHO, UNESCO, OHCHR), governments, and tech companies demonstrates real-world policy impact. At Brunel, she co-leads the Human Rights, Society & Arts research group and serves as SLS Council Member, building on prior affiliations with Nottingham's Rights Lab and Essex's Human Rights Project to advance interdisciplinary human rights scholarship in digital contexts.
Susan Gilles is a Professor at Capital University Law School , where she has taught since 1990. Her work focuses on Civil Procedure , First Amendment Law , and Media Law , with recent scholarship including the interactive online casebook Click & Learn: Civil Procedure (2020). She holds an LL.M. from Harvard University and an LL.B. with honors in Public Law from the University of Glasgow, Scotland. Chair, Academic Affairs Committee Advisor, Women’s Law Association Her research spans constitutional privacy , tort law , and legal education innovation , with a focus on applying technology to enhance procedural law pedagogy. Publications include analyses of libel litigation processes ( Taking First Amendment Procedure Seriously , 1998), media accountability in defamation cases ( Food Lion as Reform or Revolution , 2000), and evolving privacy doctrines ( From Rehnquist to Roberts , 2007). Her work often examines the interplay between legal procedure and constitutional principles , particularly in media contexts.
