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Xiaofan JiangView profile

Associate Professor

• Systems and Data
• Intelligent Embedded Systems
• Mobile and Wearable Computing
• +12 more

Xiaofan (Fred) Jiang is an Associate Professor of Electrical Engineering at Columbia University and an Affiliate in the Computer Science Department. He serves as Co-Chair of the Smart Cities Center at the Data Science Institute and Vice Chair of ACM SIGEnergy. His research spans intelligent embedded systems, mobile/wearable computing, Internet of Things, and connected health. Education B.Sc. (2004), M.Sc. (2007), Ph.D. (2010) in Electrical Engineering and Computer Science from UC Berkeley His work focuses on City-scale energy footprint tracking with real-time analytics Privacy-preserving wearable systems for urban safety AI-driven thermal comfort estimation in buildings Magnetic-based indoor localization Smart plug meters and energy analytics LLM integration for medical diagnostics Recent publications highlight trends in Reconfigurable drone systems for physical-digital interfaces Transformer architectures for speech and sensor data Generative AR for sensor data visualization Multi-modal physiological data analysis Programless smart home interfaces Scientific Awards NSF Graduate Fellowship Vodafone-US Foundation Fellowship NSF CAREER Award Students Jingping Nie (Ph.D., UNC Chapel Hill faculty from 2025) Minghui (Scott) Zhao (Ph.D. candidate, ACM SRC winner) Qijia Shao (Ph.D., now at HKUST) and active lab members contributing to ACM HumanSys, SenSys, and MobiCom publications.

• Information Retrieval
• Natural Language Processing
• Machine Learning
• +3 more

Emine Yilmaz is a Professor at the Department of Computer Science, University College London (UCL), and an EPSRC Fellow. She is also a faculty fellow at the Alan Turing Institute, an ELLIS fellow, and an Amazon Scholar working with the Alexa Shopping team. She leads the Web Intelligence Group at UCL's Centre for Artificial Intelligence and co-founded Humanloop, a UCL spinout company. Her research focuses on information retrieval and natural language processing, leveraging machine learning, statistics, and information theory. She has authored over 150 papers, with significant contributions to conversational search, synthetic data evaluation, and AI ethics. Her work is funded by EU Horizon 2020, EPSRC, Google, and Bloomberg. Key awards include the Karen Sparck Jones Award and Google/Bloomberg research awards. She serves as co-editor-in-chief for the Information Retrieval Journal and holds editorial roles in AI Journal and ACM Transactions on Information Systems. She has organized major conferences like ACM SIGIR and TREC Deep Learning Track since 2019. Current research includes proactive conversational systems, bias analysis in synthetic data, and large language model evaluation. She advises numerous PhD students and postdocs, with notable alumni holding faculty and research roles globally.

Mircea StanView profile

Professor

• Computer Engineering
• VLSI Design
• Low-Power Circuits
• +6 more

Mircea R. Stan is the Virginia Microelectronics Consortium Professor of Electrical and Computer Engineering at the University of Virginia School of Engineering and Applied Science. He currently serves as Director of UVA's Computer Engineering Program, leading efforts to integrate interdisciplinary research in areas like AI/ML, IoT, and energy-efficient computing. His academic career includes 28+ years at UVA, where he has mentored 26 Ph.D. students and established the High-Performance Low-Power Lab. Educational Background: Earned Ph.D. and M.S. from University of Massachusetts Amherst (1990s), and a diploma from Polytechnic Institute in Bucharest, Romania. His research focuses on high-performance low-power VLSI systems, spintronic devices, and cross-layer resilience strategies. He is a Fellow of the IEEE and recipient of the NSF CAREER Award. Research Interests: Pioneers innovations in thermal-aware 3D-IC design (e.g., Cool-3D framework), magnetic racetrack memory, and energy-harvesting systems. Collaborates with the Link Lab (cyber-physical systems) and CRISP (in-memory computing). Current work emphasizes AI-driven hardware for edge computing and fault-tolerant architectures. Awards: Recognized for contributions to cross-layer resilience (CLEAR initiative), memory system reliability, and energy-efficient computing. His work bridges foundational research with practical applications in biomedical engineering and autonomous systems. Leadership: Served as interim director of NSF's Division of Translational Impacts (2022-2024) and led UVA's computer engineering program since 2022. Advocates for curriculum integration of AI/ML with traditional EECS disciplines. Spearheading faculty searches to expand capabilities in terahertz systems and neuromorphic engineering. Labs/Teams: Directs the High-Performance Low-Power Lab and collaborates with the Center for Research in Intelligent Storage and Processing in Memory (CRISP). His team develops open-source tools like PiMulator for PIM emulation and Grapefruit for FPGA-based automata processing.

• Information Retrieval
• Natural Language Processing
• Machine Learning
• +4 more

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.

• Information Retrieval
• Deep Reinforcement Learning
• Conversational Agents
• +2 more

Dr. Grace Hui Yang is Professor and Director of Graduate Studies in the Department of Computer Science at Georgetown University, where she leads the InfoSense (Information Retrieval and Sense-Making) research group. She holds a Ph.D. in Computer Science and Language Technologies from Carnegie Mellon University and has received prestigious recognition including an NSF CAREER Award. Her research focuses on: Deep reinforcement learning for interactive systems Privacy-preserving information retrieval Proactive conversational agents Neural information retrieval architectures Publication analysis reveals three primary research trajectories: (1) Fundamental advances in neural IR infrastructure including segment-based indexing and gaze-incorporated models; (2) Theoretical frameworks for understanding search behavior and task classification; (3) Applied systems for conversational AI and proactive interaction. Recent work increasingly examines LLM integration in information systems. Dr. Yang has led major initiatives including TREC Dynamic Domain tracks and SIGIR workshops on privacy-preserving IR. She currently supervises multiple PhD students working on large language models and conversational agents. Her research has been supported by DARPA and NSF, including a recent $599,974 grant for developing proactive conversational systems.

Wolfgang MinkerView profile

Professor

• Artificial Intelligence
• Dialogue Systems
• Human-Robot Interaction
• +4 more

Prof. Wolfgang Minker is a University Professor at the Institute of Communications Engineering, Ulm University, Germany. He holds dual doctorates in Engineering Science and Computer Science from the University of Karlsruhe and Université Paris-Sud. His professional roles include serving as Dean of Studies, Director of the Interns' Office, and Ombudsperson for PhD Programs. He co-directed the International Research Laboratory for Multimodal Biometric and Speech Systems at ITMO University (2017–2022) and currently leads the ERSAMUS Educational Coordination team. His research focuses on AI-driven dialogue systems, human-robot interaction, and computational paralinguistics, emphasizing trust modeling, empathetic systems, and cross-cultural applications. Key projects include the BEA argumentation framework and the KURT household assistance robot. Education: 1997/1998: Dual Doctorate in Engineering Science (Karlsruhe) and Computer Science (Paris-Sud) 1993: Diplom Degree in Engineering Science (Karlsruhe) & DEA in Computer Science (Paris-Sud) 1987–1993: Electronics Systems Engineering studies at University of Karlsruhe with ERASMUS specialization in Paris Research Themes: Proactive dialogue systems, AI ethics, multimodal interaction, affective computing, and human-centric AI applications in healthcare and education. His work bridges theoretical frameworks with real-world deployment, addressing challenges in trust, cultural adaptation, and ethical AI integration. Key Contributions: Pioneered context-aware dialogue systems (e.g., Robert DIY assistant), developed emotion recognition pipelines using audiovisual fusion, and advanced argumentative dialogue architectures. His research emphasizes socially-aware reinforcement learning and user engagement optimization in group interactions. Institutional Roles: Member of Habilitation Committee & Examination Boards Admission Board representative for engineering programs Coordinator for international educational partnerships

• Health Informatics
• Ubiquitous Computing
• Machine Learning
• +4 more

Sang Won Bae is an Assistant Professor at the Department of Systems and Enterprises, Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology. He also holds affiliate roles at the Stevens Institute for Artificial Intelligence (SIAI) and Semer Center for Healthcare Innovation. His research focuses on developing AI-driven health intervention systems using mobile sensing and machine learning, with applications in predicting risky behaviors like substance use and hospital readmissions. Dr. Bae earned a PhD in Human-Computer Interaction/Cognitive Science from Yonsei University (2013) and an additional degree in Human-Computer Interaction/Computer Science from Carnegie Mellon University (2017). He previously served as a Systems Scientist at Carnegie Mellon’s Human-Computer Interaction Institute (2014–2019). His work has been supported by NIH grants (R21, U01) and NIDA SBIR grants. Notable achievements include the Best Paper Award in Cancer Informatics (ACM) and recognition in Forbes. He has authored over 50 peer-reviewed publications and holds leadership roles in top conferences like CHI and UbiComp. Dr. Bae’s research emphasizes personalized healthcare solutions, such as AI chatbots for mental health and explainable clinical decision support systems. He actively contributes to professional societies including ACM and IEEE.

• Natural Language Processing
• Information Retrieval
• Recommender Systems
• +2 more

Dr. Annalina Caputo is an Assistant Professor in the School of Computing at Dublin City University and Academic Lead for the part-time MSc in Artificial Intelligence program. Since 2022, she serves as Assistant Head for Research Management. She is a funded investigator in the ADAPT and I-Form research centres, leading the Proactive Experience & Agency challenge. Her research spans Natural Language Processing, Information Retrieval, and Machine Learning, with applications in personalization systems. Dr. Caputo holds a Ph.D. in Computer Science from the University of Bari Aldo Moro, where she researched Semantics and Information Retrieval. She previously held research positions at Trinity College Dublin as an EDGE COFUND Marie Curie Fellow and at the University of Bari. She has participated in numerous evaluation campaigns including CLEF, SemEval, and WSDM Cup. Her current research focuses on Intelligent Information Access, Text Representation, Temporal Dynamics in IR, Personalized Retrieval, Semantic IR, Quantum IR, Cross-Language Retrieval, Question Answering, and Recommender Systems in NLP and Additive Manufacturing contexts. Dr. Caputo serves as Guest Editor for the Special Issue on Knowledge Graphs for Search and Recommendation and is General Co-Chair for ECIR 2023. Her recent publications demonstrate strong focus on transformer-based recommender systems, NLP applications in healthcare/manufacturing, and interactive retrieval systems.

Robert LegensteinView profile

Professor

• Computational Neuroscience
• Neuromorphic Computing
• Spiking Neural Networks
• +3 more

Dr. Robert Legenstein is a Full Professor and Institute Head at the Institute of Machine Learning and Neural Computation , Graz University of Technology. He serves as Speaker of the Graz Center for Machine Learning and Action Editor for Transactions on Machine Learning Research (TMLR) . His research bridges computational neuroscience and machine learning, focusing on neuromorphic computing systems that mimic biological neural networks. Research Leadership: Leads EU-funded projects like Adaptive Optical Dendrites (FET-Open) , SYNCH (FET-Proactive) , and Stochastic Assemblies in SNNs (FWF) . Scientific Contributions: Develops learning algorithms for spiking neural networks (SNNs), with applications to memristive architectures, neuroprosthetics, and energy-efficient AI systems. Key Publications: 15+ recent works on topics including dendritic computing, hardware-aware training, and context-dependent neural processing. Teaching Roles: Offers courses like Deep Learning , Principles of Brain Computation , and Data Structures & Algorithms . Contact: robert.legenstein@tugraz.at | +43 316 873 5824 | Inffeldgasse 16b/I, 8010 Graz, Austria.

• Personalisation
• User Modelling
• Adaptive Hypermedia
• +4 more

Owen Conlan is Professor of Computer Science at Trinity College Dublin and Head of Artificial Intelligence Discipline. As Co-director of Trinity Centre for Digital Humanities, his research focuses on personalization, adaptive hypermedia, and user modelling. Awarded Fellow of Trinity College (2015) for contributions to personalized systems. Education includes PhD in Computer Science. Leads ADAPT Centre's Personalising User Experience theme with €10.8m research funding. Teaches undergraduate/postgraduate courses on AI and digital humanities. Publications demonstrate consistent focus on explainable AI and user control in personalized systems. Recent work explores virtual humans for medical training, misinformation countermeasures, and time management assistants. Hypertext 2021 General Chair; ACM Web Conference 2027 General Chair. Research groups: Artificial Intelligence and Knowledge & Data Engineering (KDEG).

• Artificial Intelligence
• Data Science
• Neuroscience
• +7 more

Yashar Moshfeghi is an Associate Professor in Artificial Intelligence and Data Science at the University of Strathclyde, leading the NeuraSearch Lab. His research bridges Neuroscience, AI, and Data Science, focusing on Recommender Systems, Information Retrieval, and EEG-based cognitive modeling. He has pioneered over 90 publications and collaborates with industries via KTP and consultancy. Awards include Honorary Senior Research Fellow at Glasgow (2024) and the BAE Stars Award (2024). Education & Roles: Based in the Faculty of Science’s Computer & Information Sciences department, Moshfeghi holds leadership roles such as SICSA Director of Research (2024) and BCS-IRSG Inclusion Officer (2021). Research Interests: Proactive information systems, neurophysiological approaches to search, and ethical AI. His lab integrates MRI/EEG data to predict user needs, with applications in dementia care and generative AI. Grants & Projects: Leads over £10k in grants, including EPSRC Critical Mass Programmes (2025) and the PHAWM Project (2024–2028). Recent initiatives include 'Shaping Dementia Care with Generative AI' (2024) and the Industrial CASE Account with Niall McGuire (2022–2027). Labs & Teams: Directs the NeuraSearch Lab, fostering interdisciplinary collaborations in AI ethics, healthcare tech, and neuro-IR. His team advises on PhD/Marie Curie Fellowships and hosts workshops like NeuroPhysIIR (2025).

Ilhan AslanView profile

Associate Professor

• Human-Computer Interaction (HCI)
• Artificial Intelligence (AI)
• Machine Learning
• +6 more

Ilhan Aslan is an Associate Professor in the Department of Computer Science at Aalborg University (Denmark), affiliated with the Technical Faculty of IT and Design. His work focuses on Human-Centered Computing, with a strong emphasis on AI-driven interaction design, emotion-aware systems, and tangible/somaesthetic interfaces. He leads research in areas such as conversational AI, mobile computing, and smart environments, integrating machine learning with user-centered methodologies. Aslan's recent projects explore emotional speech processing, proactive AI agents, and creativity support tools, often bridging technical innovation with human well-being applications. His research spans over two decades, with notable contributions to mobile navigation systems (e.g., Bum Bag Navigator), gesture-based interaction, and ambient intelligence. Media coverage highlights his work on AI solutions for COPD patients and stress management applications. Aslan's approach combines rigorous technical development with ethnographic and participatory design practices, ensuring ethical and user-centric outcomes. His lab collaborates across disciplines, addressing challenges in HCI, AI ethics, and sustainable computing. Key Research Themes : Emotion-Aware AI, Human-AI Collaboration, Tangible Interaction, Mobile Health, Interactive Machine Learning Notable Projects : 'Feel my Speech' (haptic emotion conversion), 'BEHAVE AI' (ethical agent design), and somaesthetic smarthome systems Media Impact : Featured in 400,000+ Danes-relevant health tech stories and COPD patient support innovations Aslan's publications reflect a prolific trajectory from early mobile learning platforms (2000s) to cutting-edge generative AI and multimodal systems. His work consistently prioritizes real-world applicability through iterative prototyping and user studies, making him a key figure in both academic and applied HCI domains.

Shirish C. SrivastavaView profile

Professor

• e-government
• services sourcing
• technology enabled innovation
• +5 more

Dr. Shirish C. Srivastava serves as a tenured Full Professor and GS1 France Chair holder in Digital Content for Omni Channel at HEC Paris, affiliated with the Information Systems and Operations Management department. He teaches across Grand Ecole, Masters, Doctoral, Executive MBA, and Custom Executive Education programs while coaching senior executives on technology management and digital transformation. His educational foundation includes a Ph.D. from the National University of Singapore (2008), an MBA with Prime Minister's Gold Medal from India's Management Development Institute (2000), the Kellogg School of Management's International Teachers Programme (2011), and a Habilitation from Université de Lorraine, France (2016). Ph.D., NUS Business School (2008) MBA, Management Development Institute, India (2000) International Teachers Programme, Kellogg (2011) Habilitation, Université de Lorraine (2016) Dr. Srivastava's research pioneers critical intersections of technology and organizational behavior, with core expertise in e-government frameworks, AI-driven innovation, open source governance, and cross-cultural virtual team dynamics. His work addresses real-world challenges in digital transformation for microbusinesses, conversational AI humanization, and social media engagement strategies, emphasizing practical applications in global business contexts. Digital transformation in public and microbusiness sectors AI ethics and human-AI interaction design Open source project sustainability models Cross-cultural virtual team innovation His publication portfolio reveals strong thematic continuity in digital innovation, with recent works examining government-orchestrated microbusiness transformation, open source governance mechanisms, and anthropomorphism in AI agents. These studies demonstrate interdisciplinary rigor through mixed-methods approaches combining information systems theory with organizational behavior and cross-cultural management insights. Dr. Srivastava's scientific recognition includes the 2024 JAIS Best Paper Award, 2023 Kauffman ICIS Award, multiple Syntec Management Awards (2016, 2022), the Gerardine DeSanctis Award (2009), and SIM Best Paper Honorable Mention (2007). JAIS Best Paper Award (2024) Kauffman ICIS Award (2023) Syntec Academic Award (2022) Gerardine DeSanctis Award (2009) Prime Minister's Gold Medal (2001) As Senior Editor for the Journal of the Association for Information Systems and European Journal of Information Systems, he shapes scholarly discourse while serving on multiple editorial boards. His executive education impact spans over 30 countries through speaking engagements on AI implementation, digital transformation, and cross-border business relationships, bridging academic research with corporate strategy development.

Monica RosselliView profile

Professor

• Neuropsychological Assessment
• Cognitive Development
• Bilingualism
• +3 more

Monica Rosselli serves as Professor and Associate Chair of Psychology at Florida Atlantic University's Charles E. Schmidt College of Science, where she directs the Neuropsychology Laboratory. Her research integrates clinical neuropsychology with cultural neuroscience to address critical gaps in aging and cognitive assessment. Educational background: Ph.D. in Biomedical Sciences (Neuropsychology), National Autonomous University of Mexico, 1989 Dr. Rosselli's research centers on neuropsychological assessment across diverse populations, with emphasis on how bilingualism and cultural factors influence cognitive testing. She investigates neural mechanisms of cognitive development and aging through ERP studies, examines driving safety in neurocognitive disorders, and pioneers cross-culturally valid diagnostic tools for dementia. Her work uniquely bridges laboratory neuroscience with real-world functional outcomes. Analysis of her 2024-2025 publications reveals three dominant trends: (1) advancing plasma biomarkers (p-tau217, GFAP) for Alzheimer's detection in ethnically diverse cohorts; (2) developing AI-driven driving safety technologies using in-vehicle sensors; and (3) addressing social determinants of health in dementia research through the ADRC network. Her scholarship consistently prioritizes reducing diagnostic disparities for Latino and immigrant populations. As leader of FAU's Neuropsychology Laboratory, she oversees five interconnected research streams: neuropsychology of aging, cultural/bilingual assessment factors, ERP correlates of specialized experience, cognitive development, and driving safety in neurocognitive disorders. Her team actively collaborates with the 1Florida ADRC on biomarker validation and longitudinal cognitive tracking.

ChengXiang ZhaiView profile

Professor

• Intelligent information systems
• Information retrieval
• Data mining
• +4 more

ChengXiang Zhai is the Donald Biggar Willett Professor in Engineering at the University of Illinois at Urbana-Champaign , holding appointments in the Department of Computer Science , Carl R. Woese Institute for Genomic Biology , and the Department of Statistics . He leads research in intelligent information systems, with a focus on information retrieval, data mining, NLP, and machine learning. His TIMAN research group and DAIS explore applications in healthcare, education, and scientific discovery. He develops MOOCs on text retrieval and mining, and has published extensively on topics including LLM alignment, user simulation, and multimodal systems. Key Research Areas : Intelligent search engines, explainable AI, human-AI collaboration, biomedical informatics Recent Trends : LLM economics, knowledge overshadowing, just-in-time recommendation systems He has received the ACM Fellow title, SIGIR Salton Award , and multiple teaching honors including Rose Award and Graduate Mentoring Award . He serves as series editor for Springer Information Retrieval Book Series .