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Leah FindlaterView profile

Associate Professor

• Accessibility
• Human-Centered AI
• Human-Computer Interaction
• +3 more

Leah Findlater is an Associate Professor in the Department of Human-Centered Design & Engineering at the University of Washington (College of Engineering). She also holds adjunct and affiliate appointments in Computer Science & Engineering and Disability Studies, respectively, and serves as Associate Director of UW CREATE (Center for Research and Education on Accessible Technology and Experiences). Since 2021, she has led a research team in AI and accessibility at Apple. Her research focuses on creating adaptive technologies that accommodate individual needs, particularly for people with disabilities. Key areas include touchscreen personalization, machine learning interfaces, and sound recognition systems for deaf and hard-of-hearing users. Funding sources include NSF, DoD, and major tech companies. Recent work explores AI-driven tactile graphics, visual privacy management for blind users, and sound recognition systems. Her research combines lab studies, field deployments, and qualitative methods. NSF CAREER Award (2014) She advises through the Inclusive Design Lab, emphasizing mixed-methods research and collaborations with disability communities.

Liadh KellyView profile

Assistant Professor

• Applied Artificial Intelligence
• Intelligent Search
• Ubiquitous Computing
• +3 more

Liadh Kelly is an Assistant Professor in the Department of Computer Science at Maynooth University's Faculty of Science & Engineering. She supervises PhD students in applied artificial intelligence, focusing on intelligent search, ubiquitous computing, and multimodal information access. She is affiliated with the ADAPT SFI Research Centre, SFI Centre for Research Training in Foundations of Data Science, and Human Health Institute. BSc in Computer Science MSc (Research) in Computer Science PhD in Computer Science Her research explores context-sensitive retrieval and evaluation methodology in AI-driven systems. Key areas include ubiquitous computing for personal data analysis, deep learning classification for mental wellness indicators, and multimodal lifelogging integration. Recent publications focus on urban mental wellbeing classification , contextual cue analysis , and AI-driven health search systems . Articles address smart city applications , consumer health search , and cross-lingual medical retrieval . Professional roles include Doctoral Consortium Chair at ECIR 2023 and Programme Committee member for SIGIR and ICWSM conferences. She leads grants for 4-year PhD studentships with stipend and fee coverage.

Sara MagliacaneView profile

Assistant Professor

• Causality
• Causal Representation Learning
• Causality-inspired Machine Learning
• +4 more

Sara Magliacane is an Assistant Professor at the University of Amsterdam , affiliated with the Amsterdam Machine Learning Lab (AMLab) and the Informatics Institute . She also holds a Research Scientist position at the MIT-IBM Watson AI Lab and has been an ELLIS Scholar since 2022. Education PhD in Artificial Intelligence (2017), VU Amsterdam MSc in Computer Engineering (2011), Politecnico di Milano BSc in Computer Engineering (2008), Università degli Studi di Trieste Research Focus : At the intersection of Causality and Machine Learning , her work addresses Causal Representation Learning from high-dimensional data (images, sequences) Causal Discovery in latent confounder scenarios Causality-inspired Reinforcement Learning for robustness and adaptability Neurosymbolic AI for theoretical guarantees Publication Trends : Her recent work explores Factored adaptation in non-stationary environments (NeurIPS 2022) Temporal causal identifiability (ICML 2022) Binary interaction-based causal discovery (UAI 2023) Safe exploration in visual RL (HSCC 2021) Structure learning lower bounds (NeurIPS 2020) Scientific Recognition : ELLIS Scholar (2022–present) Spotlight presentations at ICML 2022 and ICLR 2022 Advising & Collaborations : Currently supervising 6 PhD students at the University of Amsterdam and AUMC, with 12 alumni advisees. Collaborates with researchers at MIT-IBM Watson AI Lab, Simons Institute, and TUM.

• Analog and mixed-signal integrated circuit design
• Computer-aided design (CAD) of electronic circuits
• Design automation (EDA)
• +5 more

Georges Gielen is Full Professor in the Department of Electrical Engineering (ESAT) at KU Leuven, Belgium, and part-time Research Director at imec. He has held multiple leadership roles including Chair of ESAT Department (2012-2013, 2020-2024) and Vice-Rector for Science, Engineering & Technology (2013-2017). His academic career spans over 30 years at KU Leuven, progressing from Assistant to Full Professor. His research focuses on analog and mixed-signal integrated circuit design automation , with expertise in CAD tools, design optimization, sensor interfaces, and neuromorphic systems. His work bridges hardware design with machine learning, particularly in hardware-efficient AI implementations and biomedical applications. He has pioneered techniques for automated analog circuit sizing, topology synthesis, and reliability-aware design in nanometer CMOS. Gielen has received numerous accolades including the IEEE CAS Mac Van Valkenburg Award (2015), IEEE CAS Charles Desoer Award (2020), and EDAA Achievement Award (2021). He holds an ERC Advanced Grant AnalogCreate and is an IEEE Fellow since 2002. As a prolific scholar, he has chaired major conferences including DATE (2006), ICCAD (2007), and ESSCIRC (2017). He has graduated over 55 PhD students through the MICAS research group at KU Leuven, currently supervising 13 doctoral candidates. His research team collaborates extensively with imec and industry partners on cutting-edge projects in carbon-aware AI accelerators, uncertainty-aware design, and neuromorphic sensor interfaces.

• International Arbitration
• Mediation
• Alternative Dispute Resolution
• +5 more

Marta Gonzalo Quiroga serves as a faculty member at King Juan Carlos University's School of Law, specializing in Private International Law with extensive contributions to international arbitration, mediation systems, and the intersection of artificial intelligence with legal frameworks. Her academic profile spans over two decades of scholarly work, thesis supervision, and active engagement in legal reform initiatives across European and Latin American jurisdictions. Her research focuses on the evolving landscape of Alternative Dispute Resolution (ADR) mechanisms, with particular emphasis on how artificial intelligence transforms family law arbitration, sustainable development goal integration in mediation practices, and cross-border legal harmonization. Recent publications demonstrate a strategic pivot toward technology's role in legal systems, examining AI applications in international arbitration while maintaining foundational work in traditional mediation frameworks and private international law. Academic leadership is evidenced through her direction of four doctoral theses addressing critical gaps in mediation practices across Ecuador, Spain, and Mexico, with research outputs contributing to emerging frameworks like the University Coexistence Law and transnational mediation protocols. Her collaborative work extends to European regulatory frameworks, particularly in developing standardized mediation practices across jurisdictions while addressing cultural and systemic differences. Professional engagement includes significant contributions to collective works on international dispute resolution, with recent chapters addressing psychosocial risks in digital-age conflict resolution and technological innovations in workplace mediation. Her scholarly impact is reflected in a publication record spanning 25 journal articles, 48 collective work contributions, 11 books, and consistent engagement with contemporary legal challenges through both theoretical and practical lenses.

Joo Heung YoonView profile

Assistant Professor

• Machine Learning in Medicine
• Critical Care Medicine
• Hemodynamic Monitoring and Prediction
• +3 more

Joo Heung Yoon, MD is an Assistant Professor of Medicine in the Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine at the University of Pittsburgh School of Medicine. His research develops machine learning models for predicting hemodynamic instability in critical care settings, with applications extending to space medicine environments. His educational background includes: MD from Catholic University of Korea, Seoul, South Korea (2002) Internal Medicine Internship at Maimonides Medical Center - SUNY Downstate (2007) Internal Medicine Residency at New York Medical College (2009) Research Fellowship at Massachusetts General Hospital / Harvard Medical School (2011) Research Fellowship at Beth Israel Deaconess Medical Center / Harvard Medical School (2014) Fellowship in Pulmonary and Critical Care Medicine at University of Pittsburgh School of Medicine (2017) Dr. Yoon specializes in identifying hidden pathologic patterns through machine learning, developing prediction models for shock, hemorrhage, and tachycardia using large-scale clinical data. His work bridges critical care medicine with AI, focusing on real-world ICU implementation through alert systems and user interfaces. He actively explores microgravity applications, aiming to create feasible prediction algorithms for resource-constrained space missions where timely high-stake decisions are critical. His publication trend (2018-2020) reveals consistent advancement in hemodynamic prediction models, transitioning from theoretical frameworks to practical implementation strategies. These works integrate supervised ML and deep neural networks to address circulatory shock, hemorrhage identification, and instability surrogates, demonstrating strong interdisciplinary collaboration between clinical medicine and engineering. Notable awards include: SCCM Gold Snapshot Award (2019) ATS Abstract Award (2018) Excellence in Clinical Service Award (2010) Partners in Excellence Award (2009) Richard D. Levere Teaching Award (2008) As Principal Investigator for NIH K23 grant GM138984 (2020-2025), Dr. Yoon leads research on machine learning-driven shock prediction models. He mentors medical students and house staff daily in the ICU, specializing in cardiopulmonary physiology teaching. His grant portfolio focuses on therapeutic strategies for circulatory shock in critically-ill patients, with strong industry-academic partnerships. Based at UPMC Montefiore, Dr. Yoon collaborates with Carnegie Mellon University's Machine Learning School and Pitt Engineering to develop clinical decision support systems. His team is designing graphic user interfaces for spaceflight applications where resource limitations demand highly efficient predictive analytics for hemodynamic crises.

• Media Linguistics
• Ethnomethodological Conversation Analysis
• Human-Machine Interaction
• +6 more

Tim Moritz Hector is a Research Associate at the University of Siegen since 2020, affiliated with subproject B06. He completed his PhD in Applied Linguistics in April 2024 with a dissertation on voice assistants as conversational participants. His research focuses on media linguistics, ethnomethodological conversation analysis, human-machine interaction, linguistic praxeology, and cultural linguistics. Education: German (linguistics), political science, and educational science (2012–2019) at Münster and Bonn Academic roles: Student assistant (2015–2019), research assistant (2019), and current research associate Research Themes: Hector investigates voice user interfaces, domestication of smart technologies, and interactional practices between humans and AI systems. His work bridges linguistic analysis with digital media studies, focusing on how voice assistants reshape social practices in households. Article Trends: Recent publications emphasize smart speaker domestication , human-machine agency , voice interface practices , sensory smart home systems , and data practices in AI adoption . He explores how voice assistants become embedded in daily routines through linguistic and praxeological frameworks. Academic Affiliations: Member of the Society for Applied Linguistics (GAL) and German Cultural Studies Society (KWG). Former Wikimedia Deutschland e.V. board chair and UNO-Flüchtlingshilfe e.V. supervisory board member. Conference Contributions: Active in conferences like IPrA, Social Interaction, and COST networks. Key presentations include topics on multisensory interaction, invectives in voice technology use, and responsive smart home systems. Collaborations: Co-organized major conferences including Machine–Body–Space (2024) and Voice Assistants in Private Homes (2023) with interdisciplinary teams from Siegen, Bremen, and Brussels.

• Biomaterials
• Biomedical Engineering
• Non-clinical testing methodology for Medical Devices
• +3 more

Professor Kiyotaka Iwasaki at Waseda University's Faculty of Science and Engineering is a leading figure in biomedical engineering with a focus on cardiovascular device development , tissue engineering , and regulatory science . His career spans over two decades at Waseda University, including roles as Associate Professor (2006-2014) and positions at Harvard Medical School's Laboratory for Tissue Engineering. Holding a Doctor of Engineering from Waseda, he serves on numerous international regulatory committees and has contributed to ISO/TC194 standards for medical devices. 1993-2002: Waseda University Education in Mechanical Engineering 2001-2004: Research Associate at Waseda University 2004: Research Scientist at Harvard Medical School 2018-Present: Professor at Waseda University His research interests include Non-clinical testing methodologies for medical devices Regulatory science frameworks Tissue engineering for ligament and cardiac applications Cardiovascular biomedical engineering His scientific contributions reveal through Development of decellularized tissue grafts for orthopaedic surgery Innovations in 3D cardiac tissue engineering using fibrin-based cell sheet stacking Pioneering bioresorbable stent technology with magnesium alloys Creation of biomechanical simulators for valvular disease modeling His awards span from the 2021 Japanese Ministerial Science Commendation 2020 JSME Standards Award 2018 ARIA Innovation Award 2001 ASAIO Fellowship While his publications demonstrate expertise in Vascular and cardiac device testing Bioresorbable stent evaluation Machine learning in medical device regulation Decellularized tissue applications

• Game Theory
• Algorithmic Game Theory
• Congestion Games
• +9 more

Alexander Skopalik is an Assistant Professor in the Mathematics of Operations Research department, specializing in Game Theory, Congestion Games, and Algorithmic Game Theory. His work explores Strategic Resource Allocation, Equilibrium Analysis, and Network Games, with significant contributions to multi-agent systems and facility location optimization. Key research areas: Congestion Games Facility Location Nash Equilibrium Strategic Resource Allocation Algorithmic Game Theory His recent publications focus on equilibrium dynamics in facility location, battery charging games, and strategic resource allocation, emphasizing the interplay between theoretical guarantees and practical applications in AI and mobility systems. He actively participates as a committee member in leading conferences such as IJCAI and AAMAS.

Isabel García VelázquezView profile

Researcher

• Social Robotics
• Autism Studies
• Artificial Intelligence
• +3 more

Isabel García Velázquez is a researcher at Linköping University 's Department of Thematic Studies , affiliated with Theme Gender (TEMAG) . Her work intersects social robotics , autism studies , and AI ethics , informed by feminist and decolonial frameworks. Her research critically examines how autism is conceptualized in robotic therapy and AI systems , questioning the social capabilities of robots and the ethical implications of their use in healthcare. She actively participates in the WASP-HS program , contributing to interdisciplinary discussions on AI's societal impact. Her recent publications focus on gendered embodiment in robotics , maternal mental health applications , and decolonial critiques of AI . She can be contacted at isabel.garcia.velazquez@liu.se .

• Robotics
• Human-Robot Interaction
• Machine Learning
• +7 more

Christian Smith is an Associate Professor and Lecturer at the Department of Robotics, Perception and Learning at Kungliga Tekniska Högskolan (KTH Royal Institute of Technology). His research focuses on robotics and applications in human-centered environments like home environments, small workshops, and healthcare facilities, including the development of new robotic systems for research. Teaching Roles: Course Coordinator/Teacher/Examiner for courses such as Introduction to Robotics (DD2410), Research Project in Robotics (DD2411), and Java Programming for Python Programmers (DD1380) Research Themes: Human-Robot Interaction, Behavior Trees, Exoskeletons, Intent Recognition, and Multimodal Perception Awards: No specific scientific awards mentioned in the provided text His KTH profile highlights work on adaptive robotics systems and formalized control strategies. The research portfolio spans from theoretical studies on behavior tree programming to applied work in assistive technologies and teleoperation systems.

Chu (Ivy) DangView profile

Assistant Professor

• quantitative marketing
• economics of information
• consumer search
• +9 more

Professor Chu (Ivy) Dang is an Assistant Professor of Marketing at the Business School of The University of Hong Kong, where she has been teaching since 2020. Her research focuses on the economics of information in quantitative marketing, examining how consumers search for information, how this information influences their choices, and the information provision strategies of firms in digital environments. Business School, The University of Hong Kong Assistant Professor of Marketing Specializes in consumer behavior in digital contexts Professor Dang received her Ph.D. in Marketing from The Chinese University of Hong Kong, where she also earned an M.S. in Economics. Her undergraduate degree is a B.S. in Applied Physics from Beijing Jiaotong University. Prior to her business studies, she spent two years conducting research in quantum information at RB Liu Lab as a Hong Kong PhD Fellowship Scheme (HKPFS) candidate in physics. Her research spans multiple dimensions of consumer behavior in digital environments, with particular emphasis on consumer search behavior and information economics. She investigates how consumers acquire and process information in online contexts, with applications to social media marketing where she examines the effects of Marketer-Generated Content (MGC), User-Generated Content (UGC), and increasingly, AI-Generated Content (AIGC). Her work on emerging trends in live-commerce and influencer marketing has provided new insights into how these formats reshape consumer decision processes. Analysis of her publications reveals a consistent focus on empirical methods to study information economics, with increasing attention to social media dynamics and emerging e-commerce formats. Professor Dang has secured significant research funding as Principal Investigator, including a General Research Fund grant (#17506824) and an Early Career Scheme grant (#27504221) from the Hong Kong Research Grants Council. She also leads projects funded by the HKU Business School Shenzhen Research Institutes and the HKU Seed Fund for Research. She recently co-organized the 14th Consumer Search and Switching Costs Workshop in Hong Kong in June 2025, demonstrating her leadership in this specialized research area. Her research has been published in top-tier journals including Journal of Marketing Research, Information Systems Research, and Marketing Science. Her teaching portfolio includes Social Media Marketing at both undergraduate and Master's levels, where she brings her cutting-edge research insights into the classroom to prepare students for the rapidly evolving digital marketing landscape. In her personal time, Professor Dang enjoys running, hiking, and spending time with her family.

Pavel P. KuksaView profile

Academic

• Bioinformatics
• Computer Science
• Functional Genomics
• +5 more

Pavel P. Kuksa is a Research Assistant Professor in the Department of Pathology and Laboratory Medicine, specializing in bioinformatics, computer science, and functional genomics. His work focuses on high-throughput sequencing analysis, chromatin interaction data, and developing scalable software platforms for genomics research.

Hailiang ChenView profile

Professor

• Artificial Intelligence
• FinTech
• Social Media
• +8 more

Hailiang Chen serves as Professor in Innovation and Information Management, Assistant Dean (Taught Postgraduate), and Director of the Artificial Intelligence Research Institute at HKU Business School, The University of Hong Kong. His academic journey includes a PhD and MS from Purdue University and a BM from Tsinghua University. Doctoral Degree: Management Information Systems, Purdue University Master Degree: Economics, Purdue University Bachelor Degree: Information Management and Information Systems, Tsinghua University Professor Chen's research spans artificial intelligence, FinTech, social media analytics, and platform economics, with significant contributions to understanding how digital interactions shape financial markets and consumer behavior. His work frequently examines the intersection of technology adoption and economic outcomes, particularly in cryptocurrency markets, live-stream commerce, and venture capital decision-making. His research methodology combines large-scale data analysis with experimental designs to uncover causal relationships in digital ecosystems. His publications in elite journals like Journal of Financial Economics and Management Science demonstrate consistent impact, with multiple ESI Highly Cited Papers. Current projects include Gov-RAG for e-government services and comparative studies of AI search tools. His research has received continuous funding from Hong Kong's Research Grants Council for five consecutive years (2019-2023). Faculty Outstanding Researcher Award, HKU Business School (2022-23) INFORMS ISS Sandra A. Slaughter Early Career Award (2022) Association for Information Systems Early Career Award (2019) Three ESI Highly Cited Papers (Top 1% in field) Professor Chen actively contributes to academic service as Associate Editor for Journal of Management Information Systems and MIS Quarterly , and serves as Program Chair for the International Conference on Smart Finance. His industry collaborations include Alibaba, HSBC, and China Construction Bank, bridging academic research with real-world business applications in AI implementation and digital transformation.

Li YangView profile

Assistant Professor

• Cybersecurity
• Machine Learning
• Deep Learning
• +12 more

Li Yang is an Assistant Professor in the Department of Information Technology , part of the Faculty of Business and Information Technology at Ontario Tech University. His research focuses on applying AI and machine learning to cybersecurity, particularly in intrusion detection and anomaly detection for 5G/6G networks and IoT systems. He holds a PhD in Electrical and Computer Engineering from Western University (2022), and has held roles such as Vice Chair of IEEE Computer Society, London Section (2022–2023). Education: PhD in Electrical and Computer Engineering, Western University (2022) Master of Science, University of Guelph (2018) Bachelor of Engineering, Wuhan University of Science and Technology (2016) Research Interests: His work spans cybersecurity, machine learning, deep learning, AutoML, model optimization, network automation, IoT security, intrusion detection, and adversarial machine learning. He develops frameworks for concept drift adaptation and online learning to enhance cybersecurity measures, with a focus on trustworthy AI and defense strategies against adversarial attacks. Awards: Graduate Student Award for Excellence in Research (2022) Graduate Symposium Award for Best Presentation (2022) Mitacs Accelerate Fellowship (2021) OC2 Lab Industrial Research Excellence Award (2020) Ranked in Stanford/Elsevier's Top 2% Scientists (2024) Grants & Involvement: Li Yang has contributed to conferences like IEEE GlobeCom and IEEE CCECE, and authored patents such as 'Convenient primary-secondary barrels' (2009). His work has garnered thousands of citations and GitHub stars, emphasizing practical applications of AI in cybersecurity.