Paola Perucchini is a Professor in the Department of Educational Sciences at the University of Rome III, specializing in child development, educational psychology, and environmental learning. Her work bridges early childhood education with interdisciplinary research on intercultural understanding, ADHD intervention, and sustainability pedagogy. Full Professor, Department of Educational Sciences Director of the Department of Educational Sciences Member of Academic Senate and Research Commission Her research focuses on reducing social biases, inclusive pedagogy, and the cognitive benefits of green environments. She pioneered the ODIS (Osservazione della DIScussione) framework for analyzing classroom communication and the Yesterday-Today-Tomorrow e-learning program for migration education. Recent publications (2023-2025) emphasize prosocial behavior promotion, intergroup coalition formation, and outdoor education's role in attention restoration. Earlier work (1997-2004) explores gestural development in autism and its implications for theory-of-mind cognition. She collaborates with the MuSEd – Mauro Laeng Museum of School and Education , integrating historical pedagogy with modern inclusive education strategies. Her teaching emphasizes socio-communicative teacher traits and remote learning adaptation, particularly in pandemic contexts.
Wei Zhang is an Assistant Professor in the School of Foreign Studies at Nanjing University, China. His research focuses on speech perception, production, and prosody, employing behavioral experiments, corpus studies, and computational modeling. He holds a PhD in Linguistics from McGill University, where his advisors included Meghan Clayards, Morgan Sonderegger, and Michael Wagner. His educational background includes a doctoral program at McGill University specializing in Linguistics. Research interests center on tonal systems (particularly Mandarin and Taiwanese Southern Min), acoustic cue interactions, and the role of F0 and duration in speech processing. He has also explored machine learning applications in natural language processing and speech technologies. Zhang's recent work reveals a focus on cross-linguistic comparisons of prosodic features, computational methods for pitch analysis, and neural network architectures enhancing natural language understanding. His 2024 studies on focus effects and constituency in Mandarin/English prosody demonstrate methodological innovation in phonological interfaces. Earlier work established foundational insights into F0 range dominance in tonal perception. Key contributions include advancements in pitch-range estimation, tonal imitation patterns, and speech corpus methodologies. Despite prolific publication (over 20 peer-reviewed works across 2014-2025), no advising roles or grants are explicitly mentioned. His lab/teams' activities remain unspecified in the provided materials.
Sanjay Rao is a Professor in the School of Electrical and Computer Engineering at Purdue University, leading the Internet Systems Laboratory. His research focuses on network synthesis/design/verification and Internet video distribution. He holds a B.Tech from IIT Madras and a Ph.D from Carnegie Mellon University. He has held visiting roles at Google, AT&T Research, and Princeton University. Research & Awards: His work includes groundbreaking contributions like End System Multicast (winner of the ACM SIGMETRICS Test of Time Award), Oboe (ABR auto-tuning), and Veritas (causal video streaming analysis). He received the NSF CAREER Award (2010) and is an ACM Distinguished Member (2021). Teaching: Courses include Computer Networking (ECE 463), Object-Oriented Programming (ECE 39595), and Computer Network Systems (ECE 595). Service: Chair, ACM Sigcomm Doctoral Dissertation Award Committee (2022); Associate Editor, IEEE/ACM Transactions on Networking (2016–2020). Labs & Teams: Directs the Internet Systems Lab (ISL) with active projects on video streaming, network resilience, and intent-based design. Graduate students collaborate on these initiatives.
Prof. William Stewart is a Professor in the Department of Recreation, Sport, and Tourism at the University of Illinois at Urbana-Champaign. He holds a PhD in Watershed Management and Forestry from the University of Arizona. His research focuses on community-based conservation, park development, and the intersection of human well-being with environmental landscapes. Research Interests: His work emphasizes understanding place meanings, community resilience, and the integration of socio-cultural values into ecological planning. Stewart collaborates with interdisciplinary teams including ecologists, economists, and urban planners to address landscape change and resource management challenges. Recent projects include the Chicago Large Lot Program (assessing urban greenspace impact) and rural community resilience in protected grasslands. Teaching: Stewart teaches courses like RST 393/594 on Community Conservation and Restoration, emphasizing regional-scale planning for mixed-use landscapes. He co-leads the Park and Environmental Behavior (PEB) Research Lab, guiding over 10 graduate and undergraduate researchers. Affiliations: Affiliated with the Departments of Natural Resources and Environmental Sciences, and Landscape Architecture. His work is funded by USDA, National Park Service, and National Institute of Food and Agriculture grants. Labs/Teams: Directs the PEB Lab, which focuses on participatory conservation methods, sense of place studies, and urban-rural interface dynamics. Collaborations span international institutions like Beijing Forestry University and Tongji University.
Alexander Karlsson is an Associate Professor at the Department of Information Technology, School of Informatics, University of Skövde. His research focuses on machine learning, information fusion, and their applications in transportation, healthcare, and industrial systems. He leads projects like I2Connect, developing advanced driver assistance systems using deep learning and situation awareness algorithms. Key research interests include driver intention recognition, predictive maintenance, telecommunication anomaly detection, and biomedical data analysis. He has published extensively in top venues like IEEE Transactions, ACM journals, and conferences like IPMU and MDAI. Education: PhD in Information Fusion (2010) from University of Skövde. Teaching: Coordinates courses in data analytics and AI at graduate and postgraduate levels. Projects: Active in industrial collaborations (e.g., automotive, steel production, telecommunication). His work bridges theoretical advances in machine learning with practical industrial challenges, emphasizing uncertainty quantification and robust decision-making frameworks.
Jing Tang is an Assistant Professor at Northumbria University's Newcastle Business School, specializing in Business Analytics and Artificial Intelligence. She teaches undergraduate and graduate level courses in Business Analytics, Machine Learning, Data Management and Visualization, and Decision Making. Her research focuses on the intersection of business applications and artificial intelligence, with particular expertise in: Business Analytics and Data-driven Decision Making Artificial Intelligence and Machine Learning for business applications Optimization and Heuristic Algorithms Social Networks Analysis and Recommender Systems Dr. Tang's recent publications demonstrate a strong focus on applying AI techniques to business problems, particularly in consumer behavior analysis, recommendation systems, and cyber security for online retail. Her work often combines theoretical AI approaches with practical business applications. Among her notable achievements: Supervising PhD student Yijing Li on "Understanding Online Consumer Behaviour through Implicit Feedback: Intention Recognition and Modelling for Business Strategy" since October 2022 Publishing in top-tier journals including IEEE Transactions, ACM Transactions, and Information Sciences Dr. Tang is actively contributing to the advancement of Business Analytics through her research and teaching, bridging the gap between theoretical AI and practical business applications.
Merike Kaseorg is a Lecturer in Entrepreneurship at the University of Tartu's School of Economics and Business Administration. She holds an MBA (2002) and a BA in Marketing and Trade (1995). Her career spans over three decades, beginning as an Office Assistant in 1980 and progressing to academic roles since 2004. She specializes in entrepreneurship education, lifelong learning, and university-industry collaboration. Current Position: Junior Lecturer in Entrepreneurship (2023–present) Previous Roles: Assistant of Entrepreneurship (2018–2022), Lecturer of Management (2016–2017), and various teaching positions since 2004 Her research focuses on entrepreneurship education effectiveness, social entrepreneurship, family business dynamics, and internship programs. She has organized workshops on blockchain, FAIR data principles, and entrepreneurship pedagogy. Active in international conferences, she has participated in events in Finland, the USA, and Greece. Publications span entrepreneurship education frameworks, business model analysis, and social innovation. Collaborations with institutions like the Baltic Family Firm Institute highlight her engagement in regional academic networks.
Dr. Adeel Rafiq is a Lecturer at the School of Engineering, Computing and Mathematical Sciences, University of Wolverhampton. With a PhD in Computer Engineering from Jeju National University (South Korea) and over a decade of combined academic and industrial experience, he specializes in AI-driven network management, 5G/6G networking, and software-defined infrastructure. Education : PhD (2018-2021), MSc (2012-2014), BSc (2007-2011) Professional Affiliations : Member of Institution of Engineering and Technology (MIET), HEC Pakistan-approved PhD Supervisor, Registered Engineer (Pakistan Engineering Council) His research focuses on cutting-edge advancements in network systems, including Intent-Based Networking , Network Function Virtualization , and Machine Learning for Network Optimization . His work bridges theoretical innovation with practical implementation in 5G/6G, IoT, and cloud environments. Dr. Rafiq's publication record spans high-impact journals like IEEE TNSM and Cluster Computing, as well as key conferences including IEEE BigComp and APNOMS. His contributions include patents in intent-based resource management and network optimization. Scientific Awards : 4 patents (2 granted, 2 under review) focused on SDN/NFV innovations In industry, he has led AI-powered network monitoring systems through Knowledge Transfer Partnerships and contributed to telecom solutions at AdvOSS and Gazuntite Pvt. Ltd. He holds certifications in SAFe Product Management, Docker, Agile, and Machine Learning.
Univ.Prof. Dr. Yusak Susilo is a Professor at the Institute of Transport Engineering , University of Natural Resources and Life Sciences, Vienna (BOKU). He holds a Doctor of Engineering from Kyoto University and has previously served as Full Professor at KTH Royal Institute of Technology, Senior Lecturer at University of the West of England, and Visiting Professor in Indonesia, Malta, and the Netherlands. His research focuses on transport and urban planning, human behavior modeling, agent-based simulations, and equity in mobility systems. Education : Doctor of Engineering (Kyoto University, Japan, 2005); Master of Engineering in Transportation Engineering (Bandung Institute of Technology, Indonesia, 2000); Bachelor of Engineering (Maranatha Christian University, Indonesia, 1998). His work explores decision-making processes, adaptation to technological innovations, time-use dynamics, and system-level impacts of decarbonization. He leads projects like Shaping E-Roads Efficiency for Freight Automation and UNLOCK15 - Transitionspfade zur 15-Minuten-Stadt . Articles highlight his contributions to understanding automated bus acceptance, micro-mobility, demand-responsive transport, and health impacts of mobility patterns. Scientific awards include the Ars Docendi Sonderwürdigung (2024), Smart Transportation Alliance Innovation Award (2019), and multiple Eric Pas Dissertation competition honors. He has supervised 14 theses, including PhD and Master’s students analyzing SuperApp adoption, micromobility impacts, and automated bus deployment. Prof. Susilo’s projects span sustainable urban development, mobility hubs, and virtual reality applications for transport research. He contributes to editorial boards of journals like Transportation Research Part A and Journal of Transport & Health , and serves as Vice President of the International Association of Travel Behavior Research (IATBR).
Youssef Al Hariri is a Research Fellow at the Institute for Language, Cognition and Computation (ILCC) within the School of Informatics, University of Edinburgh. He holds a PhD in Informatics (2023), an MSc in Artificial Intelligence with Distinction (2018), and a BSc in Computer Engineering (2017). PhD: Informatics, University of Edinburgh (2023) MSc: Artificial Intelligence with Distinction, University of Edinburgh (2018) BSc: Computer Engineering, Qatar University (2017) His research focuses on computational social science, social network analysis, machine learning, and natural language processing. He studies human-generated content, networks, and narratives, applying qualitative and quantitative methods to analyze online communities’ interactions, contributions, and network dynamics. Current projects include FANToM (Finding Adversary Narratives: Topic and Momentum) , aiming to enhance AI-based narrative analysis tools, and past work includes modeling audience interactions using state-of-the-art AI techniques. His recent publications highlight trends in social media analysis, Arabic NLP, and narrative detection. Key contributions include TwiXplorer (2024), an interactive tool for historical Twitter data analysis; SMASH group papers at AraFinNLP2024 (2024) and StanceEval2024 (2024) on Arabic intent detection and stance detection; and ESG communication studies during COP events (2024). Earlier works (2019, 2021) explore religious polarization in Arab online communities. Labs & Teams: Member of the Social Media Analysis and Support for Humanity (SMASH) Lab, Neuropolitics Research Lab (NRLabs), and Digital Influence & Intelligence Lab (DIIL). Current teaching includes Text Technologies for Data Science (2023/2024). Past grants include the Alan Turing Institute for FANToM and Modelling Audience Interactions.
Ido Guy is a researcher at Yahoo Labs, specializing in recommender systems, e-commerce, and social media analytics. He has extensive publications in top-tier venues like WWW, SIGIR, WSDM, and NeurIPS, often collaborating with researchers such as Sharon Hirsch, Kira Radinsky, and Slava Novgorodov. Key research areas: Recommender systems, temporal modeling, graph neural networks, and e-commerce search. Notable projects: Automated category tree construction, calibration error measurement, and event-driven consumer demand prediction. His work integrates natural language processing and machine learning to solve practical challenges in product recommendation, review analysis, and enterprise social media. While no awards or students are listed here, his contributions to algorithm design and data-driven system development are significant.
Wei GAO is an Associate Professor of Computer Science at Singapore Management University's School of Computing and Information Systems (SCIS), where he serves as full-time faculty. His research focuses on artificial intelligence applications in social computing, misinformation analysis, and natural language processing. Professor GAO leads research on large language models, rumor detection, and social media analytics through computational approaches. Research Focus Professor GAO's expertise spans several interconnected domains: AI & Data Science : Developing advanced machine learning models for complex data analysis Social Media Analytics : Studying misinformation propagation and user behavior patterns Natural Language Processing : Creating novel methods for text understanding and generation Computational Social Science : Quantifying psychological and social phenomena through AI Publication Trends Recent works demonstrate strong emphasis on enhancing large language models for: misinformation detection (rumor verification, fake news debunking), social computing (stance classification, moral reasoning), and efficient AI (model compression, transfer learning). Multimodal approaches and explainable AI frameworks appear consistently across publications. Academic Activities Professor GAO supervises PhD students including LAI Yibin, with mentorship focus on NLP and social computing research. He teaches courses on Natural Language Communication and contributes to SMU's research initiatives in digital transformation and AI safety.
Nicholas Mastronarde is an Associate Professor and Associate Chair in the Department of Electrical Engineering at the University at Buffalo, State University of New York, within the School of Engineering and Applied Sciences. He leads the WIRED Lab (Wireless Networking, Reinforcement Learning, and Drones Lab), which conducts cutting-edge research in wireless communications, AI/ML for networks, and UAV systems. Ph.D. in Electrical Engineering from UCLA (2011) M.S. in Electrical Engineering from UC Davis (2006) B.S. in Electrical Engineering from UC Davis (2005, Highest Honors) Dr. Mastronarde's research focuses on wireless networking, reinforcement learning, and drone systems. His work spans AI/ML for wireless networks (reinforcement learning for energy harvesting wireless sensors, IoT, 5G scheduling), NextG wireless networks (active-passive coexistence, software-defined networking, mmWave networks), and modeling, simulation, and field experimentation for future networks. His research has significant applications in spectrum coexistence, digital twin technology, and UAV networking, with emphasis on practical implementation through platforms like UB-ANC and NeXT. His recent publications demonstrate a strong trend toward integrating AI/ML techniques with wireless communications to develop more efficient, adaptive, and intelligent network systems, particularly focusing on spectrum coexistence between satellite and terrestrial networks, digital twin-enabled network simulation, and reinforcement learning applications for next-generation wireless systems. Dimitris N. Chorafas Foundation Award (2011) UCLA Graduate Division Dissertation Year Fellowship (2010-2011) IBM Research Watson Lab Graduate Intern Fellowship (2010) 2020 SEAS Senior Teacher of the Year Award UB's Teaching Innovation Award 2022 Dr. Mastronarde has successfully advised numerous graduate students, including current PhD candidates and multiple alumni who have gone on to work at companies like Qualcomm. His research is supported by prestigious organizations including the US Air Force Research Laboratory, US SOCOM, the National Science Foundation (including the NSF SWIFT award), GE Aviation, US Ignite, ARMOR-IIMAK, and SUNY. His extensive publication record includes over 100 peer-reviewed articles in top-tier journals and conferences. As the leader of the WIRED Lab, Dr. Mastronarde oversees several key research initiatives including UB-ANC (unmanned aerial vehicle networking simulation/emulation), RF-SITL (software-defined transceiver and channel emulation), NeXT (digital twin-enabled multi-fidelity network simulator), and UnionLabs (cloud-based platform for testbed sharing). His team consists of current PhD students, research scientists, and undergraduate researchers working collaboratively on cutting-edge wireless communication projects.
Graham Massey is a Senior Lecturer at the University of Technology Sydney (UTS), based in the Marketing Discipline Group within the UTS Business School. He holds a PhD in Marketing from the University of New South Wales. His research focuses on cross-functional working relationships between Marketing, Sales, and R&D managers during new product development (NPD), emphasizing structural equation modeling and data from multiple managerial perspectives. Key research interests include identifying factors influencing effective/ineffective cross-functional relationships, conflict management, and organizational learning. He has published in leading journals like European Journal of Marketing , Industrial Marketing Management , and Journal of Business and Industrial Marketing , and co-authored chapters in the Oxford Handbook of Strategic Sales and Sales Management . Awards include the Emerald Literati Network Award (2005) and Best Paper at the UK Academy of Marketing Conference (2008). He serves on editorial boards for Industrial Marketing Management and Australasian Marketing Journal , and reviews for several top-tier journals. Professional Activities include core membership in UTS’s CMOS Research Centre, participation in international conferences (e.g., ANZMAC, EMAC, ISPIM), and collaboration with institutions like Penn State’s Institute for the Study of Business Markets. He has secured research funding for projects such as the NSW Government CX Survey Master Questionnaire design (2021). Teaching responsibilities include Postgraduate Marketing Management courses at UTS.
Professor Emine Yilmaz is a distinguished academic at University College London (Department of Computer Science), holding concurrent roles as a Turing Fellow and Amazon Scholar. She leads the Web Intelligence Group at the UCL Centre for Artificial Intelligence and collaborates with Amazon's Alexa Shopping team as an Amazon Scholar. Her research focuses on information retrieval, natural language processing, and machine learning, with over 150 publications (6,250+ citations, H-index 39). Notable awards include the Karen Sparck Jones Award, Google Faculty Research Award, and Bloomberg Data Science Research Award. Her work is funded by EU Horizon 2020, EPSRC, and industry partners like Google and Bloomberg. She has served in leadership roles for journals (e.g., Information Retrieval Journal) and conferences (e.g., ACM SIGIR 2024 PC Chair). Recent projects include organizing the TREC Deep Learning Track and co-founding Humanloop, a UCL spinout company. Research Interests: Machine learning for search systems, conversational AI, educational technology, and ethical AI. Key Contributions: Synthetic test collections (SYNDL), contextual understanding in dialogue systems, and knowledge-enhanced retrieval frameworks. Her articles emphasize robustness in retrieval-augmented generation (RAG), proactive search systems, and bias mitigation in synthetic data. Recent highlights include work on personalization benchmarks (PersonaLens) and trustworthiness in AI systems (TrustRAG). Awards: Karen Sparck Jones Award (2021), Google Faculty Research Award (2020), Bloomberg Data Science Award (2019). She advises over 10 current PhD students and has mentored 9 former students, many now in academia and industry. Her grants span EU, UK, and industry funding, with recent support from Bloomberg’s PhD fellowship program and Google Research Awards. Labs/Teams: Web Intelligence Group (UCL), co-founder of Humanloop, and key contributor to the TREC Deep Learning initiative.
