Dr. Marcel Mierwald is a researcher at the Department of History Didactics at Ruhr University Bochum, specializing in empirical studies of historical learning. He collaborates on the oral history project "People in Mining" and focuses on digital learning, epistemological beliefs, and language-sensitive history teaching. His work bridges theoretical frameworks with classroom practice. Education: Doctoral degree (2019) at Ruhr University Bochum; Master of Education in social studies and history (Free University of Berlin, 2012). Research Trends: His recent publications emphasize authenticity in learning materials, media comparison studies, and assessment tools for historical argumentation. Collaborations with Nicola Brauch and others highlight interdisciplinary approaches to history education. Scientific Awards: Doctoral scholarship from Professional School of Education (PSE) at Ruhr University Bochum (2013-2016). Teaching: Offers courses on subject didactics, practical semester preparation, and language-sensitive history teaching. Led seminars on migration history, the Weimar Republic, and National Socialism in school labs. Labs & Teams: Active in the Alfried Krupp Student Laboratory and Ruhr University Bochum's student laboratory for humanities, focusing on empirical history education research and innovative teaching methods.
Dr. Alexa Fox is an Associate Professor in the Department of Marketing at the College of Business, The University of Akron, where she teaches undergraduate and graduate courses in Social Media Marketing, Digital Marketing, and Consumer Behavior. She earned her Ph.D. in Business Administration (Marketing) from The University of Memphis, and holds an MBA and BBA from The University of Akron. Ph.D., Business Administration (Marketing), The University of Memphis M.B.A., The University of Akron B.S.B.A., The University of Akron Her research centers on digital marketing, online privacy, and sharenting, with a focus on how consumers, particularly parents, share children's information online. She investigates the psychological and emotional dimensions of consumer behavior through physiological measurement and explores the ethical implications of digital marketing practices. Her work bridges marketing, public policy, and consumer well-being, with a strong emphasis on responsible research. The recent publications of Dr. Fox reflect a cohesive and impactful research agenda centered on digital consumer behavior, privacy, and emotional responses. Her work spans topics such as sharenting, AI in consumer products, ad blockers, social media fatigue (e.g., Fexit), and bereavement marketing. These studies employ diverse methodologies including physiological measurement, surveys, and content analysis, and are published in high-impact journals across marketing, psychology, and policy. Dr. Fox has received numerous scientific honors, including: The University of Akron’s 2024–2025 Outstanding Researcher—Early Achievement in Research Award College of Business Dean's Service Excellence Award (2025) Best Reviewer Award, International Journal of Advertising (2023) AMA-EBSCO-RRBM Award for Responsible Research in Marketing (2022) Dean’s Research Excellence Award (2020) Outstanding Paper, Journal of Consumer Marketing (2019) She has secured multiple research grants, including principal investigator roles on projects related to sharenting and children's digital well-being, funded by The University of Akron and the Association for Consumer Research. She mentors students and serves as Faculty Advisor for honors programs and student organizations. Her service includes leadership in curriculum development, faculty mentoring, and university committees. Dr. Fox is actively involved in academic and public discourse. She serves on the editorial review boards of five top marketing journals, including the Journal of Public Policy & Marketing and Journal of Marketing Education . She also contributes to public understanding through media engagements with Forbes, PBS, and The Washington Post on topics like sharenting and digital privacy.
Prof. Dr. Volker Dellwo is an Associate Professor of Phonetics and head of the Department of Computational Linguistics. His research focuses on phonetics, speech recognition, computational linguistics, and dialectology, with applications in forensic analysis, voice biometrics, and multimodal emotion recognition. Academic Rank: Associate Professor Department: Computational Linguistics His work explores phonetic convergence , speaker discrimination, and the role of prosodic features in voice recognition. Recent studies analyze whispered speech processing, cross-dialect accommodation, and neural mechanisms of speaker identity encoding. Key article trends include self-supervised learning for speech recognition , multimodal emotion detection , and forensic voice analysis . Subfields span acoustic variability, temporal envelope dynamics, and voice quality metrics. Publications emphasize computational phonetics , cross-linguistic studies , and neural network applications in speaker identification. Research also addresses challenges in forensic audio analysis and synthetic speech dataset generation.
Hongkai Wen is a Professor (Chair in Machine Learning Systems) in the Department of Computer Science at the University of Warwick, UK. He holds dual appointments as a Fellow of the Alan Turing Institute (serving as Independent Scientific Advisor for BridgeAI and member of Turing Research Ethics team) and previously worked as Senior Research Scientist at Samsung AI Centre Cambridge and postdoctoral researcher at Oxford University. Education: Computer Science, Keble College, University of Oxford Research Focus: Develops intelligent multi-modal perception systems for real-world deployment with extreme computational efficiency. Core expertise spans ML systems optimization, neural architecture search, and cross-disciplinary applications in robotics, urban mobility, and wearable/IoT security. Pioneered event-based vision techniques and training-free NAS frameworks. Publication Trends: Recent work (2023-2025) demonstrates accelerating innovation in diffusion model efficiency, on-device AI deployment, and sensor fusion techniques. Dominant themes include computational resource optimization for edge devices, multi-modal temporal modeling, and privacy-preserving spatial analytics, with significant contributions to NeurIPS, ICML, and CVPR venues. Scientific Recognition: Best Paper Award, AutoML Conf 2023 (T-CET) Best Paper Runner-up, SenSys 2024 (AdaFlow) Best Paper Awards: IPSN 2014 & EWSN 2013 1st/2nd Place, Zero Cost NAS Competition (AutoML'22) Mentorship & Funding: Actively supervises PhD candidates through thesis committees at Warwick, Ulster, and Queensland universities. Secured National AI Strategy Fund for Macro Neural Architecture Search research. Recruits annually for PhD positions with scholarships from UKRI, Turing Institute, and industry partnerships. Research Leadership: Heads the AI/ML Systems (AMS) Division at Warwick, directing a 15+ member team developing deployable ML frameworks for mobile/robotic platforms. Maintains active collaborations with Samsung AI Centre and Turing Institute's BridgeAI programme on ethical AI deployment.
**FENG Mengling** is an Associate Professor at the National University of Singapore (NUS) and holds primary affiliation with the Saw Swee Hock School of Public Health. She serves as the Domain Leader for the Biostatistics, Modelling, AI and Data Analytics (B.MAD) Domain and Director of the AI for Public Health (AI4PH) Program. Her academic credentials include a Senior Post-doc from Harvard-MIT Health Science Technology Division, a PhD from Nanyang Technological University (2009), and a Bachelor's degree (2003) from NTU. Research & Teaching: Her research focuses on causal inference for evidence-based medicine, generative models for medical time-series analysis, and healthcare data analytics. She teaches courses on big data technologies for healthcare problems and healthcare data analytics. Professional Roles & Awards: She has led the Biomedical and Healthcare Analytics Lab at the Institute for Infocomm Research (2014–2015) and currently serves as an Affiliate Scientist at Harvard-MIT. Notable accolades include the MIT Teaching & Learning Laboratory Kaufman Teaching Certificate and recognition as a finalist in MIT’s 2013 Innovation Showcase. Her work has been featured in prominent media outlets like The Straits Times and Channel NewsAsia, highlighting breakthroughs such as AI nurses and Singlish-speaking healthcare assistants. Publications & Impact: Over 50 peer-reviewed publications span AI-driven clinical decision support, medical imaging analysis, and predictive modeling in critical care. Key contributions include frameworks like MedDreamer (reinforcement learning for EHR analysis) and DivScore (LLM-generated text detection). Her research bridges causal inference, generative AI, and scalable healthcare solutions. Labs & Initiatives: As a leader in NUS’s Public Health AI Innovation Center (launching early 2025), she drives initiatives like FxMammo (AI for breast cancer screening) and the Biomedical and Healthcare Analytics Lab. Her work emphasizes ethical AI deployment and cross-disciplinary collaboration in healthcare.
Waël Jaafar is a Professor in the Department of Software Engineering and IT at École de technologie supérieure (ETS), a constituent school of the Université du Québec system in Montreal, Canada. His research spans multiple critical domains in modern communications and computing infrastructure, with a particular focus on next-generation wireless networks and intelligent systems. Dr. Jaafar holds a B.Eng. from Sup'Com Tunisie, and both M.Sc.A. and Ph.D. degrees from Polytechnique Montréal. His academic background provides a strong foundation for his interdisciplinary research that bridges theoretical concepts with practical engineering solutions. His research interests center around wireless communications systems, with particular emphasis on 5G/6G networks, UAV communications, space telecommunications, and machine learning applications for networking. He has developed significant expertise in federated learning techniques for distributed networks, cybersecurity applications for next-generation mobile systems, and edge computing architectures. His work frequently explores the intersection of communication theory, artificial intelligence, and network security, with applications ranging from industrial IoT to public safety communications. Analysis of his recent publications reveals a strong trend toward integrating artificial intelligence with wireless networking infrastructure, particularly focusing on UAV-assisted communications, federated learning approaches for distributed networks, and security enhancements for 5G/6G systems. His research demonstrates increasing emphasis on practical implementation challenges including energy efficiency, communication overhead reduction, and reliability in non-ideal network conditions. As an academic supervisor, Dr. Jaafar actively mentors numerous graduate students across various projects. He currently supervises doctoral candidates working on blockchain-enhanced security for 5G networks, green network slice orchestration, and federated learning approaches for Open RAN architecture. His master's students are engaged in diverse topics including LiDAR-based power line monitoring, multimodal behavioral authentication, and 5G/6G security using AI techniques. Dr. Jaafar is affiliated with two prominent research laboratories at ETS: LASI (Computer System Architecture Research Laboratory) and LACIME (Communications and Microelectronic Integration Laboratory). At LASI, he contributes to research in AI-based systems engineering, resource orchestration in edge/cloud environments, and intelligent network design. Through LACIME, he engages with broader communications research spanning from microelectronic components to complex communication systems, with particular focus on wireless networks and signal processing applications.
Professor Alice Bell is a Professor of English Language and Literature at Sheffield Hallam University, affiliated with the Sheffield Creative Industries Institute, Humanities Research Centre, and Culture and Creativity Research Institute. She holds a BA, MSc, PGcertHE, and PhD. Her work focuses on digital fiction, narratology, and stylistics, with a particular emphasis on how digital technologies shape narrative forms and reader engagement. Her research explores stylistics, literary-linguistics, and narratology, with a focus on born-digital fiction such as hypertext, app-based stories, and VR narratives. Key areas include interactivity in digital environments, cognitive processing of digital texts, and ontological boundaries between fiction and reality. She has led major projects like the AHRC-funded Reading Digital Fiction (2014-2017) and collaborates on preservation initiatives like the Digital Fiction Curios project. Recent work examines postdigital themes, empirical reader responses in VR fiction, and the interplay between fact and fiction in contemporary narratives. These studies often bridge narrative theory, cognitive poetics, and digital media analysis. Professor Bell has secured significant funding, including a £349,957 AHRC/DFG grant (2023) as PI for Reading Post-Postmodernist Fictions of the Digital . She supervises postgraduate students in areas like cognitive poetics, digital fiction, and experimental writing, including projects such as Alternate Realities: Possible Worlds Theory and Counterfactual Historical Fiction and ‘Digesting Creepypasta’: A Genre Analysis of Social Media Horror Fiction . Her collaborations include work with the One-to-One Development Trust on digital preservation and co-editing projects like Possible Worlds Theory and Contemporary Narratology (2019) and a special issue on fact-fiction dynamics in the European Journal of English Studies .
Matthew Duvall is a Lecturer at the University of Pennsylvania’s Graduate School of Education. His career spans roles as a computer programmer, high school teacher, instructional designer, and writer. His research focuses on leveraging technology to create inclusive learning experiences, particularly for underserved populations. He specializes in game-based learning, computational thinking, teacher professional development, and corporate training. Dr. Duvall’s work includes directing the Skyscraper Games project at Drexel University’s ExCITe Center, where middle school students designed video games displayed on Philadelphia’s Cira Centre. His dissertation explored using Goodreads to engage high school students in English language arts. He has also designed corporate training programs informed by learning science frameworks. His research trends emphasize bridging educational technology with practical applications, such as evaluating serious games, refining teacher feedback models, and integrating literacy tools like Goodreads into classrooms. His articles reflect a focus on equity, innovative pedagogy, and technology’s role in fostering authentic learning experiences. While no specific awards are listed, Dr. Duvall’s projects highlight impactful contributions to educational equity and technology integration. He collaborates with teams like the ExCITe Center and organizations serving individuals with autism, emphasizing collaborative approaches to educational innovation.
Liang-Yuan 'Leo' Wu is a Researcher at the University of Michigan's Computer Science and Engineering department, working with Prof. Dhruv 'DJ' Jain in the Soundability Lab at the AI Laboratory. He recently completed his Master's degree in Computer Science & Engineering at the University of Michigan. His educational background includes: Master of Science in Computer Science & Engineering, University of Michigan (2022-Present) University of Edinburgh (2021) Bachelor's degree, National Taiwan University (2017-2021) Wu's research centers on human-centered AI solutions for auditory accessibility, with deep collaboration with the Deaf and Hard of Hearing (DHH) community. He develops technologies that leverage multimodal AI and large language models to interpret soundscapes, generate personalized audio descriptions, and enhance captioning systems—particularly in challenging environments like clinical settings where communication accuracy is critical. His work bridges technical innovation with real-world user needs through mixed-methods UX research. His publication trajectory reveals a strategic focus on applying cutting-edge AI models to solve accessibility gaps in sound interpretation and captioning, with increasing emphasis on healthcare applications and community-driven design principles. This represents a significant shift toward context-aware, deployable accessibility tools rather than theoretical frameworks. Wu's research impact is recognized through: BEST POSTER AWARD at ASSETS 2024 for CARTGPT Google Academic Research Award for 'Audio Scene Understanding' proposal While not yet mentoring formal advisees, Wu secures competitive research funding through awards like Google's Academic Research Award and actively collaborates with interdisciplinary teams across HCI, AI, and accessibility domains. His work in the Soundability Lab emphasizes community co-creation with DHH individuals to ensure technologies address authentic user needs rather than theoretical scenarios. The Soundability Lab serves as Wu's primary research environment, focusing on making sound universally accessible through AI-driven innovation. The lab maintains direct partnerships with the DHH community throughout the research lifecycle—from problem identification to solution validation—ensuring technologies are both technically robust and socially impactful.
Ying Wang is an Associate Professor in English linguistics at Karlstad University since 2020, specializing in English for academic purposes, applied corpus linguistics, and second language writing. She holds a PhD from Uppsala University (2013) and has taught courses at both undergraduate and graduate levels focusing on academic writing, second language pedagogy, and corpus methodology. Her research explores rhetorical structures in disciplinary genres, evaluative language resources, and the impact of extramural English activities on L2 writing development. Notable projects include the Swedish Learner English Corpus (SLEC) initiative and analyses of predatory publishing practices in political science. She has also examined government communication strategies during the UK's COVID-19 pandemic response through corpus-assisted discourse studies. Key research contributions span formulaic language use in ELF contexts, methodological innovations in corpus linguistics, and linguistic comparisons between well-established and predatory journals. Her work bridges theoretical linguistics with practical applications in education and scholarly publishing ethics. Publications span prestigious journals like English for Specific Purposes , Text & Talk , and Journal of Second Language Writing , reflecting her interdisciplinary approach to language studies. Current projects emphasize corpus-driven research on academic communication practices and their pedagogical implications.
Dr. Yang Zhang is a tenured Professor at the CISPA Helmholtz Center for Information Security . His research focuses on Trustworthy Machine Learning , emphasizing privacy, safety, and security , with additional work on measuring misinformation and unsafe online content like hateful memes. He has published extensively at top conferences (CCS, NDSS, Oakland, USENIX Security) and received multiple awards including the Busy Beaver Award (2022) and NDSS Distinguished Paper Award (2019) . Research Interests : Trustworthy Machine Learning LLM Security, Privacy, and Safety Misinformation and Hate Speech Detection Social Network Analysis Recent Publications examine synthetic data auditing, hate speech detection in LLM-generated content, and privacy risks in curriculum learning, spanning conferences like USENIX Security , IEEE S&P , and ACM CCS . His work often intersects AI security with ethical considerations . Scientific Awards : Busy Beaver Award for “Privacy of Machine Learning” (2022) NDSS Distinguished Paper Award (2019) CCS Best Paper Runner-Up (2022) Best Machine Learning and Security Paper in Cybersecurity Award (2025) Best Paper Finalist at CSAW Europe (2023, 2024) Students in his group include Yixin Wu , Xinyue Shen , and Yiting Qu , the latter recently completing their Ph.D. defense. He actively recruits MSc and PhD students and has contributed to iDRAMA Lab for meme-related research.
Sandra Reimann is a Professor of German Philology at the University of Oulu's Faculty of Humanities, leading the German Language and Culture department. She holds a habilitation in linguistic studies of online self-help communication and has held visiting professorships at institutions like Karl Franzens University in Graz. Her career includes roles at the University of Regensburg since 2001 and radio journalism since 1992. Her research focuses on applied linguistics, media communication, business communication (including advertising), and health communication. She investigates technical language in medicine/psychology, emotional linguistics, digital corpus analysis, and interdisciplinary communication challenges. Key projects include leading the Regensburg Advertising Research Archive and exploring sustainability messaging in cross-cultural contexts. Reimann's recent work examines gender language in job advertisements, sustainability communication strategies, and online health information quality. Her publications span 40+ years of advertising analysis, from historical radio spots to modern digital campaigns. She contributes to both academic conferences and practitioner-oriented research through the Regensburger Verbund für Werbeforschung network. Her professional service includes roles as spokesperson for the Regensburg Advertising Research Network and oversees the advertising archives. Though no formal awards are listed, her extensive research collaborations across European universities highlight her disciplinary influence. She actively bridges academic and corporate sectors through applied linguistic studies in branding, health communication, and technical language mediation.
Talal Shaikh is an Associate Professor at Heriot-Watt University's School of Mathematical and Computer Sciences in Dubai. He serves as Director of Undergraduate Studies and Programme Director for BSc Computer Science, BSc CS (AI), and MSc Software Engineering. With a decade of industry experience as a Chief Information Officer and Software Engineer, he bridges practical insights with academic research. Research Interests: Pervasive Computing, IoT/M2M, AI/ML, WiFi Sensing for Healthcare, Financial Machine Learning, Educational Technology Awards: Teaching Excellence Awards (2017/18), Fellow of the Higher Education Academy (FHEA), multiple Learning and Teaching Oscars (2016, 2017, 2018) His work spans Ubiquitous Computing and IoT , focusing on sensor networks and WiFi-based sensing for healthcare. In Artificial Intelligence , he applies ML to robotics, financial analytics, and educational innovation. Recent articles analyze Reinforcement Learning , Emotion Recognition , and WiFi Sensing applications. His teaching emphasizes student-centric learning, with over 100 supervised dissertations achieving distinctions. Collaborations include international conferences and interdisciplinary research in smart environments and adaptive systems.
Bobby Lee Townsend Sturm JR is an Associate Professor at KTH Royal Institute of Technology, leading the MUSAiC project (ERC-2019-COG). He holds a PhD in Electrical and Computer Engineering from UC Santa Barbara (2009), followed by postdoctoral research at LAM, Paris 6, and academic roles at Aalborg University and Queen Mary University of London. His research focuses on AI ethics in music, generative AI for music, and folk music preservation. Current roles at KTH include teaching and supervising in Machine Learning, Music Informatics, and AI Ethics. He has pioneered AI music generation challenges (e.g., 2020 Double Jigs Challenge) and investigates societal impacts of AI on traditional music cultures. His work bridges technical innovation with cultural and ethical considerations, addressing issues like data colonialism, algorithmic bias, and human-AI collaboration in creative contexts. Education: PhD (UCSB, 2009), Postdoc (Paris 6), Academic appointments at Aalborg University (2010–2014) and Queen Mary University (2014–2018) Key Projects: MUSAiC (ERC), Virtual Session System for Irish Music, Traditional Music Dataset Analysis Teaching: Courses in Machine Learning, Music Acoustics, and ICT Innovation Publications span peer-reviewed journals and conferences, emphasizing ethical AI, music generation, and interdisciplinary research in MIR (Music Information Retrieval). He actively collaborates with musicians, anthropologists, and technologists to ensure culturally informed AI development.
Beatriz Naranjo Sanchez is a researcher at the University of Murcia, Spain, currently affiliated with the Translation, Didactics and Cognition research group and previously with the Translation, Lexicology and Writing Group. Her work bridges translation studies, cognitive psychology, and musicology through experimental methodologies. She earned her PhD from the University of Murcia in 2017 with the dissertation La influencia de la música sobre la calidad y la creatividad en traducción literaria (inglés-español, inglés-italiano) una aproximación estético-psicológica , supervised by Dr. Ana María Rojo López. Her research centers on psychological and emotional dimensions of translation processes, particularly examining how background music influences literary translation creativity, how anger affects decision-making with offensive content, and emotional processing in dubbing. She employs cognitive-experimental approaches to investigate narrative engagement, vocal qualities in emotionally charged scenes, and pandemic-related stressors on evaluative language translation. Analysis of her 2015-2023 publications reveals consistent focus on music-translation interactions and emotional variables, with methodological emphasis on laboratory experiments, psycholinguistic measurements, and cognitive assessments. Her work demonstrates interdisciplinary innovation through the fusion of aesthetic theory, cognitive science, and translation practice. Scientific awards: No awards documented in provided sources. Regarding advising and grants, while she supervises research within university groups, no specific students or funded projects were mentioned. Her institutional affiliation suggests collaborative research within translation psychology frameworks. She actively contributes to the Translation, Didactics and Cognition research group, which investigates cognitive-affective translation processes through experimental paradigms, likely involving lab-based studies on emotional and musical variables in professional translation contexts.
