Rahim Rahmani is a full Professor at Stockholm University's Department of Computer and Systems Sciences, where he leads the laboratory for Distributed Immersive Participation . His work bridges Distributed Systems , Internet of Things (IoT) , and Healthcare Technology , with a focus on security, edge computing, and immersive systems for societal challenges. Research Interests : Distributed Intelligence, Edge Computing, Blockchain, Extended Reality (XR), Adversarial Machine Learning, and Cognitive Controllers for 5G/6G networks. Teaching : Program Director for the Master's Programme in Computer and Systems Sciences, teaching courses on IoT, Network Security, and Computer Architecture. Publication Trends : His recent work emphasizes secure data sharing in IoV using Blockchain, Federated Learning for healthcare diagnostics (e.g., sepsis and COVID-19 detection), and XR platforms for autism support. Key subfields include Context-Aware Systems , Decentralized Identity Management , and Edge-Cloud Collaboration .
William Wang is a Professor of Computer Science at the University of California, Santa Barbara (UCSB), holding the Mellichamp Chair in Artificial Intelligence. He leads the UCSB NLP Group, directs the Center for Responsible Machine Learning, and co-directs the Mind and Machine Intelligence Initiative. His research focuses on machine learning, natural language processing, and interdisciplinary data science, emphasizing scalable algorithms for complex datasets. He earned his PhD from Carnegie Mellon University and has mentored numerous students in AI and NLP. Affiliations: Director of UCSB NLP Group, UCSB Center for Responsible Machine Learning, and Mind and Machine Intelligence Initiative. Education: PhD in Computer Science from Carnegie Mellon University, MS from Columbia University. Research interests include statistical relational learning, knowledge representation, and ethical AI. Notable awards include the NSF CAREER Award, IEEE AI's 10 to Watch, and the Karen Sparck Jones Award. His work bridges theoretical foundations and practical applications in AI, with contributions to vision-language models, multimodal reasoning, and generative AI. Key publications span top venues like NeurIPS, ICLR, and CVPR, addressing challenges in LLM reasoning, video generation, and ethical AI systems. He has advised over 15 PhD students and postdocs, many now in academia and industry leadership roles. Labs/Teams: UCSB NLP Group, Center for Responsible Machine Learning, and collaborations on multimodal AI and safety.
Assoc. Prof. Peter Schartner is an Associate Professor at the Department of Artificial Intelligence and Cybersecurity, Alpen-Adria-Universität Klagenfurt. He also serves as the Data Protection Officer, overseeing institutional compliance with data privacy regulations. His research focuses on cybersecurity, cryptography, and secure communication systems, with particular emphasis on automotive cybersecurity, quantum-resistant protocols, and secure exam environments. His work spans hardware security for embedded systems, privacy-preserving healthcare technologies, and IoT community-based security models. Notable contributions include developing the Secure Exam Environment (SEE) for online testing, cryptographic authentication methods, and quantum nonce mechanisms. He actively collaborates with the Trust Center to advance interdisciplinary security solutions. Research interests include: Cryptology, Digital Signatures, Information Security, Secure E-Business, and Cybersecurity in distributed systems. His projects often address practical challenges like functional safety in automotive control units and privacy in smart city technologies.
Prof. Laura Falaschetti is a Researcher at the Department of Information Engineering, Polytechnic University of Marche (Ancona, Italy). Her work focuses on embedded systems, neural networks, biomedical engineering, and signal processing. She develops lightweight machine learning models for resource-constrained devices, with applications in healthcare monitoring, environmental sensing, and wearable technology. Key projects include real-time gesture recognition systems, EEG-based disease classification, and low-power IoT devices for disaster early warning. Her research integrates hardware-software co-design (e.g., QEMU/GHDL) and emphasizes practical deployment of AI algorithms on microcontrollers. She holds office hours every Friday 10:00-13:00 at Ufficio docente Q165 DII/Microsoft Teams. Contact: l.falaschetti@staff.univpm.it Publications highlight contributions to embedded vision systems, wearable sensor networks, and multimodal signal fusion for clinical applications. Her work bridges theoretical machine learning with practical embedded system constraints, addressing challenges in energy efficiency, real-time processing, and medical accuracy.
Fabian David Schmidt is a Research Associate and Doctoral Student at the CAIDAS Chair for NLP at Julius-Maximilians-Universität Würzburg. He works on multilingual representation learning and sample-efficient cross-lingual transfer, co-advised by Prof. Dr. Goran Glavaš (University of Würzburg) and Ivan Vulić (University of Cambridge). Research Interests: His work focuses on cross-lingual transfer methods, low-resource NLP, and robust knowledge editing in LLMs. He also explores vision-language benchmarks, process mining, and semantic encoders for information retrieval. Key areas include Robust Cross-Lingual Transfer Sample-Efficient Training Vision-Language Integration LLM Evaluation Publication Trends: Fabian's recent publications emphasize multilingual and cross-lingual NLP advancements, including sliced fine-tuning for NER, model averaging for robustness, and domain adaptation. His 2025 work extends into vision-language tasks and LLM generalization across cultures. He also contributes to spoken language understanding benchmarks. Labs & Teams: Affiliated with the WüNLP group and the CAIDAS Chair at the University of Würzburg, collaborating with international researchers on cross-lingual NLP and LLM optimization.
Professor Graham Morgan is a distinguished faculty member at Newcastle University's School of Computing, where he serves as a Professor in the Department of Computer Science. His research spans multiple domains within computer science with a particular focus on distributed systems, Internet of Things technologies, and the application of gaming technologies to healthcare solutions. He leads several research projects and collaborates extensively with both academic and industry partners across multiple disciplines. Professor Morgan's primary research interests include distributed systems architecture, software transactional memory, IoT simulation frameworks, and the development of serious games for health applications. His work has pioneered approaches that bridge computer science with healthcare, particularly in developing video game-based rehabilitation systems for stroke patients and other therapeutic applications. His recent work has expanded into explainable AI, 6G networking, and advanced simulation techniques for IoT environments. Professor Morgan's publication record demonstrates a clear evolution from foundational work in distributed systems and transactional memory to more applied research in healthcare technology and IoT. His most recent publications (2023-2026) show a strong focus on simulation frameworks for IoT and osmotic computing, explainable AI systems, and the application of AI in clinical decision support. He has developed several notable simulation tools including SimulatorOrchestrator, IoTSimSecure, and SimulatorBridger that address critical challenges in networked systems and healthcare delivery. Principal Investigator for multiple research grants in IoT and healthcare technology Supervisor for numerous PhD and Master's students in computer science Collaborator with healthcare professionals on clinical decision support systems Developer of simulation frameworks for IoT and osmotic computing environments Researcher in AI-enabled clinical decision aids and healthcare applications Professor Morgan leads research teams focused on IoT simulation, serious games for health, and explainable AI. His laboratory develops simulation tools that address real-world challenges in networked systems, energy efficiency, and healthcare delivery. Current projects include the development of 6G-ready simulators, deepfake detection systems, and AI decision aids for clinical settings. He maintains strong collaborations with medical professionals, particularly in stroke rehabilitation and clinical decision support, ensuring his technical research has direct healthcare applications.
Dimitrios Soudris is a Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), leading the Microprocessor and Digital Systems Lab (MicroLab). Previously, he served as Lecturer, Assistant, and Associate Professor at Democritus University of Thrace from 1995 to 2008. Diploma in Electrical Engineering (1987), University of Patras PhD in Electrical Engineering (1992), University of Patras His research focuses on Embedded Systems , Reconfigurable Architectures (FPGAs) , Hardware Accelerators for data centers/space/cloud, Edge Computing , and Low Power VLSI Design . Recent publications highlight trends in: AI/ML acceleration for edge and space applications Secure FPGA architectures for 6G networks Energy-efficient heterogeneous memory systems Approximate computing techniques Transformer optimization for low-power contexts Scientific Awards: INTEL and IBM awards (project LPGD #25256) HiPEAC, DAC, and ISCA awards (2010–2024) XILINX Open Hardware Design Contest (2017, 2019, 2021) He has coordinated >70 R&D projects funded by the European Commission, ENIAC-JU, ESA, and industry partners. As Associate Editor of ACM TODAES and conference chair (PATMOS, VLSI-SOC), he contributes to academic leadership. His lab, MicroLab, specializes in hardware-software co-design for emerging computing paradigms.
Djamel Djenouri serves as an Associate Professor in Computer Science at the University of the West of England (UWE Bristol), Faculty of Environment and Technology. He joined UWE in December 2019 after serving as a senior research scientist (director of research) and deputy director at CERIST research Center. Dr. Djenouri maintains active scholarly engagement as a Senior Member of the ACM, AGYA member, and Fellow of the Higher Education Academy (HEA). Dr. Djenouri's research spans Internet of Things (IoT), Wireless and Mobile Networks, Smart Cities, Network Security, and Machine Learning applications. His scholarly contributions demonstrate expertise in federated learning, intrusion detection systems, IoT security, sensor networks, and privacy-preserving technologies. His work bridges theoretical computer science with practical applications in smart environments, healthcare, and transportation systems. His publication portfolio shows a clear trajectory toward increasingly sophisticated applications of machine learning in IoT security and optimization, with recent work focusing on federated learning approaches that balance privacy, performance, and efficiency. His research demonstrates growing emphasis on practical implementations in smart cities, connected vehicles, and healthcare applications. Senior Member of the ACM AGYA member Fellow of the Higher Education Academy (HEA) Dr. Djenouri has published over 140 papers in international peer-reviewed journals and conference proceedings. He actively contributes to scholarly activities including organizing international conferences and workshops, and serving as editor, guest editor, and reviewer for numerous journals. His research has been supported through collaborations with renowned institutions worldwide. Dr. Djenouri has conducted visiting research at SICS, University of Cape Town, UPC Barcelona, University of Padova, NTNU, and the University of Oxford, establishing an international research network focused on advancing IoT and wireless network technologies.
Peter O'Hearn is a Professor of Computer Science at University College London and Research Scientist at Meta AI (FAIR), renowned for co-developing separation logic which bridges theoretical computer science and industrial-scale program analysis. His dual affiliation exemplifies the synergy between academic research and practical tool development that characterizes his career. His research interests focus on program verification , separation logic , static analysis , and his recent groundbreaking work on incorrectness logic as a complementary approach to traditional verification. O'Hearn pioneered the concept of local reasoning which enables modular verification of large codebases by focusing only on relevant memory regions, forming the theoretical foundation for Facebook Infer. His publications reveal a consistent trajectory from foundational theory to industrial application, with recent work emphasizing Scalable verification for million-line codebases Compositional reasoning for concurrent systems Practical deployment of formal methods in developer workflows Bug-oriented reasoning through incorrectness logic His research consistently addresses the tension between theoretical soundness and practical applicability in program analysis. Notable scientific awards include: 2021 IEEE Cybersecurity Award for Practice 2016 Gödel Prize for separation logic 2016 CAV Award for outstanding contributions POPL 2019 Most Influential Paper Award Fellow of the Royal Society (FRS) Fellow of the Royal Academy of Engineering (FREng) O'Hearn has made substantial contributions to industrial practice through Facebook Infer, which analyzes millions of lines of code daily across Meta's codebase. His work on continuous reasoning integrates formal verification into developer workflows, while his recent focus on incorrectness logic addresses the critical need for effective bug detection in large systems. He maintains active leadership in the programming languages community through conference organization and keynotes.
Eva Pettersson is a Researcher in computational linguistics at Uppsala University's Department of Linguistics and Philology. She is affiliated with the Swedish National Language Bank and collaborates with researchers across multiple institutions, including the University of Gothenburg where she works with Lars Borin on corpus linguistics projects. Her academic work bridges computational methods with historical language analysis. Dr. Pettersson's research focuses on the intersection of digital humanities and computational linguistics, specializing in the processing and analysis of historical texts. Her work spans multiple domains including natural language processing for historical documents, historical cryptology, corpus development, and linguistic analysis of diachronic language change. She has made significant contributions to Swedish historical linguistics through her development of specialized resources and tools. Her publication record demonstrates a consistent trajectory of innovation in historical text processing, with recent work focusing on medieval scribal habits, named entity recognition in 19th century Swedish, rhetorical structure analysis of historical petitions, and historical cryptanalysis. These publications reveal a progression from foundational work on spelling normalization to increasingly sophisticated applications of NLP techniques to historical documents across multiple centuries. Dr. Pettersson has developed significant linguistic resources including the Swedish Diachronic Corpus and the HistCorp collection of historical corpora and tools. These resources have become essential for researchers working on historical Swedish language and provide standardized datasets for computational analysis of language change over time. Her collaborative work extends to international projects like the DECRYPT initiative for historical manuscript decryption and the development of specialized databases for historical ciphers. Through these projects, she has established herself as a key figure in the application of computational methods to historical linguistic materials and cryptological challenges.
Lei Li is an Assistant Professor at Carnegie Mellon University's Language Technologies Institute (LTI) within the School of Computer Science. He also holds affiliations with CMU CyLab and CPCB, as well as the University of California Santa Barbara Computer Science Department. His educational background includes a Ph.D. in Computer Science from Carnegie Mellon University, where he worked under Prof. Christos Faloutsos on efficient algorithms for mining co-evolving time series, and a B.S. in Computer Science from Shanghai Jiao Tong University's prestigious ACM Honored Class. Dr. Li's research centers on multilingual natural language processing , AI security , large language models , and AI-powered drug discovery and protein design . He is particularly known for developing VolcTrans, a multilingual machine translation system serving over 1 billion users across 100 languages, and for his groundbreaking work on LLM watermarking. His lab focuses on building tools to facilitate communication across the world's languages and advancing science through AI. His publication record shows consistent output at top AI conferences including NeurIPS, ACL, EMNLP, ICML, and ICLR, with recent work spanning LLM security, multilingual capabilities, protein design, and watermarking techniques. The trends in his recent publications indicate an increasing focus on the intersection of language technologies and biomedical applications. ACL Best Paper Award Multiple first-place wins in WMT Machine Translation Competition SIGKDD Doctoral Dissertation Award (runner-up) Vocabulary Learning via Optimal Transport for Neural Machine Translation (ACL 2021 Best Paper) Dr. Li advises several students at CMU including Siqi Ouyang, Zhenqiao Song, Danqing Wang, Kexun Zhang, and Ramith Hettiarachchi (from CMU Computational Bio Department), as well as Wenda Xu from UC Santa Barbara. He teaches advanced courses including Large Language Model Systems and Generative AI for Biomedicine. Prior to CMU, he held faculty positions at UC Santa Barbara and served as founding director of the ByteDance AI Lab.
Jared Kutzin serves as an Adjunct Associate Professor at the MGH Institute of Health Professions and holds a dual appointment as Associate Professor of Emergency Medicine and Medical Education at the Icahn School of Medicine at Mount Sinai, where he concurrently serves as Senior Director of the Simulation, Teaching and Research Center at The Mount Sinai Hospital. His educational foundation includes: Doctor of Philosophy, Nursing (candidate), Texas Woman’s University MS in Medical Education Leadership, University of New England - College of Medicine DNP in Public Health Nurse Leadership, UMASS Amherst MPH in Health Policy and Management, Boston University BS in Nursing, Columbia University BS in Community Health Education, Hofstra University Dr. Kutzin's research centers on leveraging simulation-based education and educational technologies to drive behavior change that enhances healthcare quality and safety. His specialized focus spans emergency medicine, nursing practice, pre-hospital systems, and disaster response protocols. Current investigations examine virtual reality educational environments and the critical relationship between built clinical environments and clinician performance. His methodological approach integrates human factors engineering with educational theory to optimize simulation design and implementation. Analysis of his 15 most recent publications reveals a dominant trajectory toward technology-enhanced simulation methodologies, particularly virtual reality and telemedicine applications, with increasing emphasis on global health contexts and economic evaluations of simulation programs. The work consistently bridges clinical practice with educational innovation across emergency medicine, nursing, and prehospital care domains. His distinguished recognition includes: Society for Simulation in Healthcare Educator of the Year (2022) MedEdPORTAL Associate Editor of the Year (2020) Fellow of the Institute for Medical Education Mount Sinai Health System (2020) Fellow of the New York Academy of Medicine (2018) Inaugural Fellow of the Society for Simulation in Healthcare Academy (2017) Long Island Business News 40 under 40 (2015) As an educator and leader, Dr. Kutzin has developed and implemented simulation curricula across multiple clinical settings, significantly impacting staff competency development and patient safety initiatives. His grant-funded work focuses on simulation technology integration and healthcare systems improvement, though specific funding sources aren't detailed in available materials. His leadership extends to the REBEL Lab and Center of Excellence in Healthcare Simulation Research, where he drives innovation in simulation operations, educator development, and cross-disciplinary collaboration to transform clinical education and practice.
Bernhard Schmidpeter is an Assistant Professor at Vienna University of Economics and Business (WU Wien) and a Research Affiliate at the IZA - Institute of Labor Economics since March 2020. Previously, he worked as a Researcher at the Institute for Social and Economic Research (ISER), University of Essex. He earned his Ph.D. from Johannes Kepler University (JKU). His research focuses on labor economics, family economics, and the economics of education , using applied microeconometric methods to investigate how changing labor market conditions affect individual and firm decisions. Schmidpeter's work spans several critical areas including parental bereavement effects on mortality, grandmothers' labor supply decisions, immigration enforcement impacts on families, and the relationship between automation and unemployment. His research consistently employs high-quality administrative data, particularly from Austria, to provide causal evidence on important economic questions. Schmidpeter's publications appear in top economics journals including the Oxford Bulletin of Economics and Statistics, Journal of Human Resources, Journal of Population Economics, and European Economic Review. His work on suicide contagion in the workplace, parental bereavement effects, and the impact of immigration enforcement on children's human capital represents innovative applications of economic methods to important social issues. His research has received significant media attention from major outlets including The Telegraph, Die Presse, Handelsblatt, ORF Science, Süddeutsche Zeitung, and the WSJ Economics Blog, demonstrating the policy relevance of his work. Schmidpeter frequently collaborates with prominent researchers including Wolfgang Frimmel, Martin Halla, Rudolf Winter-Ebmer, Lukas Laffers, and Esther Arenas-Arroyo. Currently, Schmidpeter is working on projects examining the equilibrium effects of cross-firm pay transparency and the demand for green skills in the evolving labor market. His research contributes to understanding how economic policies and social phenomena affect individual behavior, family dynamics, and labor market outcomes across multiple dimensions.
Mitchell Browne is a Research Fellow in the Department of Linguistics at Macquarie University. His research focuses on endangered Australian Aboriginal languages, particularly Pama-Nyungan and Ngumpin-Yapa language families. He specializes in grammar description, syntactic and semantic analysis, and language documentation. Current projects include investigating language genesis in Aboriginal communities and leveraging computational methods for speech analysis in endangered languages. Education: PhD in Linguistics (2021, unpublished doctoral thesis on Warlmanpa) His research interests span grammar description, morphosyntax, language contact, and community-based language revitalization. He combines traditional fieldwork with computational approaches to address challenges in documenting endangered languages. Recent work includes cross-referencing in Pama-Nyungan languages and collaborative projects with First Nations communities in Geelong. He has authored a peer-reviewed book on Warlmanpa grammar and contributed to Oxford's guide on Australian languages. His projects include MQRF 2025 examining language genesis through speaker identity and EES 2024 focused on employment pathways for Indigenous communities. Browne collaborates with institutions like ANU Press and Deakin University, emphasizing ethical engagement with Indigenous knowledge systems. His work bridges theoretical linguistics with applied community initiatives.
Veronique Hoste is a Full Professor of Computational Linguistics at Ghent University's Faculty of Arts and Philosophy , where she serves as Department Head of the Department of Translation, Interpreting and Communication and Director of the LT3 Language and Translation Technology Team . Her work bridges machine learning with natural language processing, focusing on semantics, discourse modeling, and practical applications in emotion detection, irony recognition, and customer service dialogue analysis. PhD in Computational Linguistics from University of Antwerp (2005) 2023-2024: Francqui Chair at Université Libre de Bruxelles 2024: Elected to Royal Flemish Academy of Belgium (KVAB) Research Interests: Specializes in machine learning approaches to coreference resolution, sentiment analysis, and multimodal emotion detection. Leads projects like FlandersAI (empathy in conversational agents), METRICS (emotion trajectories in service dialogues), and SENTiVENT (financial event extraction). Develops high-quality datasets (e.g., EmotioNL , ENCORE ) for broader NLP community use. Recent Publications span Dutch social media irony detection, Classical Chinese poetry sentiment analysis, and multimodal emotion datasets. Collaborates on interdisciplinary initiatives like NewsDNA (news recommendation) and SentEMO (commercial sentiment analysis). Scientific Awards Francqui Chair (2023-2024) KVAB Membership (2024) Outreach includes co-founding AlfaSent (LT3 spin-off for customer feedback analysis) and authoring the first Dutch-language NLP book Taaltechnologie Ontrafeld (2024). Coordinates AI education initiatives like the AI at School project.
