Tajda Laure is a Researcher at the Erasmus School of Social and Behavioural Sciences , Erasmus University Rotterdam. Her work focuses on emotion regulation , mental health , and digital interventions for university students. Specializes in mobile mental health applications Active in mixed methods research design Collaborates with experts like Dr. M. Boffo and Prof. R.C.M.E. Engels Research Trends : Recent articles highlight her development of the ROOM mental health app, optimization of transdiagnostic emotion regulation interventions, and methodologies involving microrandomized trials and mixed method studies . Her work intersects digital health , positive psychology , and mindfulness practices .
Tessa H.S. Eysink is a Full Professor in Instructional Technology, affiliated with the Digital Society Institute. Her research focuses on educational technology, inquiry-based learning, and technology-enhanced STEM education for children. 2024 Research Highlights : Investigated physiological and gaze metrics for learner emotions in Frontiers in Psychology Studied hypothesis generation in simulation-based learning in the Journal of Research in Science Teaching Co-developed the gamified Science Chaser app for STEM engagement at the ACM Interaction Design and Children Conference Her work bridges psychology, computer science, and education, emphasizing multimedia learning and cognitive modeling. No scientific awards or student supervision details were explicitly mentioned in the provided texts.
Dr. Yu Huang is an Assistant Professor in the Department of Computer Science at Vanderbilt University's School of Engineering, with a secondary appointment in the Department of Teaching and Learning at the Peabody School of Education. She is affiliated with the Institute for Software Integrated Systems, the Frist Center for Autism and Innovation, the Vanderbilt Lab for Immersive AI Translation (VALIANT), and the Vanderbilt LIVE Learning Innovation Incubator. Her academic journey began with a BS in Aerospace Engineering from Harbin Institute of Technology in China (2011), followed by an MS in Computer Engineering from the University of Virginia (2015), and culminated with a PhD in Computer Science and Engineering from the University of Michigan in 2021 under Professor Westley Weimer. Dr. Huang's research bridges human cognition and machine intelligence to enhance software development. Her work spans software, hardware, AI, medical imaging (fMRI/fNIRS), eye tracking, and mobile sensing through collaborations with Security, Education, Psychology, and Neuroscience researchers. She leads the MIND Lab (Mixed INtelligence Development for programming lab), investigating programming expertise formation, code comprehension processes, cognitive error patterns, and diversity in programming communities. Her innovative approach combines empirical human studies with AI model development to create more effective programming tools. Her recent publications reveal a growing emphasis on leveraging human attention data to improve code language models, analyzing cognitive biases in security contexts, and examining social factors in technical communication. The research shows strong interdisciplinary connections between neuroscience, psychology, and software engineering, with increasing applications of LLMs in developer tooling. Dr. Huang's work consistently demonstrates how understanding human cognition can inform better AI systems for programming tasks. Dr. Huang has received numerous prestigious recognitions including the 2025 ICPC Vaclav Rajlich Early Career Achievement Award and three ACM SIGSOFT Distinguished Paper Awards (ICSE 2019, FSE 2023, ICSE 2024). Her lab has earned the Best Presentation Award at GI2024, while her students have received the Richard Bennett/Dorothy Danforth Compton Prize scholarship and the C. F. Chen Best Paper award. She actively mentors a diverse team of graduate students (Yifan Zhang, Zach Karas, Zihan Fang, Yueke Zhang, Jiahao Zhang) and undergraduate researchers, with many former students advancing to top institutions (Stanford, Harvard, Duke, UC Berkeley) and organizations (NASA JPL). Her research is supported by a 4-year NSF grant, GitHub Tech for Social Good funding, and the Provost's Faculty Immersion Vanderbilt Grant, enabling comprehensive studies of human-AI collaboration in software engineering. The MIND Lab maintains a strong collaborative culture, frequently working with Professor Kevin Leach's research group and organizing retreats to locations like Radnor State Park and the Great Smoky Mountains. This environment fosters innovation at the intersection of human cognition and software engineering while supporting the professional development of emerging researchers in the field.
Carl Müller-Crepon is an Assistant Professor at the Department of Government, London School of Economics and Political Science (LSE) . His research focuses on state-building, political ethnicity, conflict, and geographic analysis, particularly in Africa and Europe. He previously held roles at the University of Oxford and ETH Zurich, and has affiliations with Harvard University. His work combines computational methods with geospatial data to study historical and modern dynamics of ethnicity, state capacity, and political violence. Education: PhD in Political Science, ETH Zurich (2019) MA in Political Science, ETH Zurich (2015) BA in International Affairs and Economics, University of St. Gallen (2013) Research Interests: His work explores how administrative borders shape ethnic identities, the impact of colonial policies on development, and the role of nationalism in territorial disputes. He innovates in geospatial data analysis and machine learning, publishing in top journals like the American Political Science Review and International Organization . Key Contributions: Developed the SIDE dataset for fine-grained ethnic demography analysis. Studied the reciprocal relationship between ethnic geographies and political borders since the 19th century. Explored state capacity in Africa using travel time metrics and road networks. Grants & Labs: Leading projects on colonial administrative design and ethnic persistence. Collaborations with institutions like ETH Zurich’s International Conflict Research Group.
Cuiyun Gao is a Full Professor and PhD Supervisor at the School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen. She has established herself as a prominent researcher in the intersection of artificial intelligence and software engineering. Her educational background includes a PhD from the Chinese University of Hong Kong (completed in 2018), followed by postdoctoral work at CUHK and a Research Fellowship at Nanyang Technological University. She also had a visiting period at University College London supervised by Prof. Mark Harman and Prof. Federica Sarro. Dr. Gao's research primarily focuses on Software Repository Mining, Natural Language Processing, Code Analysis, Large Language Models, Source Code Understanding, User Review Analysis, Vulnerability Detection, and Mobile Advertising Analysis . Her work bridges the gap between traditional software engineering practices and modern AI techniques, particularly in the context of code intelligence and software maintenance. Her recent publications (2024-2025) demonstrate a strong emphasis on Large Language Models for code-related tasks, including code generation, optimization, vulnerability detection, and software engineering applications. Her research shows a clear trend toward addressing practical challenges in integrating LLMs into the software development lifecycle while maintaining code quality and security. Scientific Awards: Distinguished Paper Award at ASE 2023 Best Paper Award of the Track at ICSE 2024 Distinguished Paper Award at ICSE 2024 Dr. Gao actively supervises multiple PhD and Master's students, contributing to the next generation of software engineering researchers. She has served on numerous conference committees including FSE, ISSTA, ICSE, ASE, and SANER. Her research has received significant attention in the software engineering community, with multiple papers published in top-tier venues like FSE, ICSE, ASE, and TSE. Her lab appears to be actively engaged in both theoretical research and practical applications, particularly in the context of WeChat and other industry collaborations, demonstrating strong industry-academia connections.
Ningchuan Xiao is a Professor of Geography at The Ohio State University's Department of Geography. His work bridges Geographic Information Science (GIScience) with computational methods, emphasizing spatial optimization, cartography, and machine learning integration. Education: Ph.D. in Geography from The University of Iowa (2003). Courses taught include GIS fundamentals, cartography, and Python-based spatial analysis. Research Interests: Spatial Optimization: Developing algorithms for land acquisition, redistricting, and resource allocation. Machine Learning & Cartography: Exploring AI-driven map interpretation and ethical visualization of complex data. Census Data: Innovating privacy-preserving techniques while maintaining data utility, including temporal/spatial modeling. Open Source Tools: Authored GIS Algorithms (2016) and maintains GitHub repository 'gisalgs' for accessible code. Publications: Recent work (2023-2025) highlights advancements in synthetic microdata generation, privacy-utility tradeoffs in census aggregation, and AI-driven cartographic recognition. His 2022 studies include traffic camera analytics and choropleth map QA systems. Awards: Not explicitly listed in the provided texts. Advising & Grants: Collaborated with researchers like Y. Lin, J. Li, and S. Bao. Projects include the Sustainable Columbus Observatory (SCO) for urban sustainability metrics. Research is supported through academic partnerships and computational initiatives.
Robert Laganière is a Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa, where he has been actively contributing to the fields of computer vision and image analysis. He is a member of the VIVA research laboratory and holds a Ph.D. and M.Sc. from INRS-Telecommunications in Montreal, as well as a bachelor's degree in Electrical Engineering from École Polytechnique de Montréal. Bachelor's in Electrical Engineering: École Polytechnique de Montréal (1987) Master's Degree: INRS-Telecommunications (1990) Doctorate: INRS-Telecommunications (1996) Professor Laganière's research focuses on computer vision, with particular expertise in image and video analysis, visual surveillance, embedded vision systems, and deep learning applications. His work spans fundamental research in feature detection and matching to practical applications in autonomous driving, human recognition, and real-time object tracking. He has made significant contributions to the development of algorithms for pedestrian detection, age and gender recognition, and 3D object localization. His publication trends reveal a consistent focus on practical computer vision applications with a strong emphasis on real-time performance and embedded implementation. Over the past decade, his research has evolved from foundational work in feature matching and homography estimation toward more complex applications in action recognition, human-computer interaction, and intelligent surveillance systems. His work consistently bridges theoretical computer vision with practical engineering constraints, particularly for mobile and embedded platforms. Best Paper Award, IEEE International Conference on Computer and Robot Vision (CRV 2014) Best Paper Award, CVPR Embedded Vision Workshop, Providence, RI, June 2012 Best Real-time Tracker, IEEE International Conference on Computer Vision (ICCV) Workshop on Visual Object Tracking (VOT2015) Professor Laganière has supervised numerous graduate students through the years, with a particular focus on practical applications of computer vision in surveillance, human recognition, and embedded systems. His research has been supported through industry partnerships with companies including CogniVue Corp, NXP, iWatchLife.com, Solink Corp, CBSA Canada, Ross Video, Thales, Habitat Seven, and YouI Labs. He has successfully translated his research into commercial applications through his founding of Visual Cortek (acquired by iWatchLife in 2009) and Tempo Analytics (founded in 2016). As a member of the VIVA research laboratory, Professor Laganière collaborates with colleagues on advanced computer vision projects, particularly those involving intelligent video analytics for security and commerce applications. His work on NAVIRE (Virtual Navigation in Remote Environments) demonstrates his commitment to developing practical solutions for real-world navigation challenges using image-based representations of real environments.
Dr. John G. Hayes is a Senior Lecturer at University College Cork (UCC) in the Department of Electrical & Electronic Engineering . He holds a Ph.D. from UCC (1998), an M.S.E.E. from the University of Minnesota (1989), an M.B.A. from California Lutheran University (1993), and a B.E. from UCC (1986). His academic career began at UCC in 2000, and he directs the Power Electronics Research Laboratory (PERL) , focusing on industrial collaborations with companies like Analog Devices and General Motors. Research Interests : Power electronics, magnetic components, electric vehicles, renewable energy systems, smart grids, and energy storage. Notable Work : Joint author of Electric Powertrain: Energy Systems, Power Electronics and Drives for Electric, Hybrid and Fuel Cell Vehicles (Wiley, 2018) and its Chinese edition (2021). Scientific Awards : 2011 IEEE William M. Portnoy Award for Best Paper/Presentation at IEEE ECCE. Advising : Supervised 10+ Ph.D. students across powertrain modeling, magnetic materials, and converter control. Current advisee: Conor Healy (Doctoral Degree). Labs : Leads PERL, which develops high-power converters for automotive and renewable energy applications, partnering with industry leaders like SMA Magnetics and United Technologies.
Roles and Affiliations: Doina Olaru is a Professor in the Department of Management and Organisations at the University of Western Australia (UWA) Business School. She is affiliated with the Planning and Transport Research Centre and holds a visiting position at the University of Burgos, Spain. Her work focuses on transport planning, urban sustainability, and data-driven decision making. Education: PhD in Transport Engineering (University Politehnica of Bucharest, 2000). Prior industry experience includes roles as a railway engineer and Postdoctoral Research Scientist at CSIRO. Research Interests: Urban transport systems, travel behavior modeling, accessibility analysis, environmental impacts of transport, and applications of artificial intelligence. She emphasizes sustainable solutions integrating land-use and transport policies. Grants and Collaborations: Principal investigator on 31 grants, including ARC Linkage Projects and industry partnerships with iMOVE CRC. Collaborates with institutions like the University of Oxford, University of Leeds, and University of Sydney. Awards: Multiple teaching awards (UWA Business School) and recognition for contributions to transport research, including the Dennis Moore Australian Computer Society Orator honor. Teaching: Courses include Data Analysis and Decision Making, and Quantitative Data Analysis. Over 10 teaching excellence nominations. Current Projects: Focus areas include smart transport technologies, roundabout modeling via drone analytics, and hybrid work impacts on transport demand.
Dr Jonathan Baker is a Senior Lecturer in Strategy at the Adelaide Business School , part of the Faculty of Arts, Business, Law and Economics at the University of Adelaide. He previously served as Director of the Yunus Centre for Business, Sustainability & Social Impact (2022-2023) and has held academic positions at Auckland University of Technology, University of Auckland, and guest professorship at University of Bayreuth. His research focuses on Interdisciplinary intersections of markets, strategy, and social impact Market-shaping strategies Sustainability and circularity transitions UN Sustainable Development Goals (9, 11, 12) Systemic business model perspectives Dr Baker's work appears in top journals including Industrial Marketing Management , Journal of Business Research , and Marketing Theory . He serves on the Editorial Review Board of Industrial Marketing Management (ABDC A*). Scientific Awards Excellence Early Career Researcher Award (ANZAM-European Management Journal, 2023) Emerging Career Researcher Award (Adelaide Business School, 2023) As a principal supervisor, he welcomes PhD/MPhil candidates interested in market shaping, sustainability transitions, or social entrepreneurship. His methodology emphasizes qualitative research and ecosystem-level analysis.
Matthew Price is the George W. Albee Green & Gold Professor of Psychological Science and Director of the Clinical Psychology Training Program at the University of Vermont's College of Arts and Sciences. He holds a B.A. from SUNY Binghamton (2004), an M.A. (2006), and Ph.D. (2011) from Georgia State University. His research focuses on expanding clinical care access for trauma survivors and anxiety disorder patients via technology-driven interventions. Key areas include mobile health applications, wearable sensors, and acute trauma care in Emergency Departments. His interdisciplinary approach involves collaborations with computer science, bioinformatics, and medicine. Current projects explore digital biomarkers (e.g., heart rate variability), technology adoption barriers, and culturally adapted therapies. He leads the Center for Research on Emotion, Stress, and Technology, emphasizing translational frameworks bridging basic research and clinical practice. Recent work includes randomized controlled trials evaluating mobile apps like 'Bounce Back Now' for disaster-related PTSD, and sleep-monitoring studies using wearable devices. Over 150 peer-reviewed articles highlight his focus on trauma mechanisms, symptom networks in veterans, and tech-enabled mental health innovations. His lab actively addresses global mental health disparities through mHealth solutions.
Dr. Michael Stevens is a Senior Lecturer at University of New South Wales (UNSW) Canberra , where he focuses on advanced manufacturing and biomedical device control systems . His work bridges digital manufacturing for SMEs with smart artificial heart technologies , emphasizing industry collaboration and translational research. Specializes in physiological control systems for rotary blood pumps Develops unobtrusive fall detection systems for dementia patients Leads international projects on total artificial heart development Education : B.Eng (Medical - First Class Honours), Queensland University of Technology (2010) PhD in Physiological Control for Biventricular Assist Devices, University of Queensland (2014) Research Trends show consistent focus on: Machine learning for biomedical diagnostics (2018–2025) mmWave radar and thermal sensors in patient monitoring (2021–2024) Computational fluid dynamics in artificial heart modeling (2016–2024) Physiological control algorithms for rotary blood pumps (2011–2025) Scientific Awards : UNSW Scientia Education Award (2021) for contextual teaching Heart Foundation Runner-up for "Smart Artificial Hearts" pitch (2021) ARC PGC Supervisor Award (2017) for mentoring Grants & Supervision : Holds over $6 million in competitive funding including MRFF and ARC grants. Currently supervises 4 PhD students while maintaining industry partnerships with VitalCare and BiVACOR. Labs & Facilities : Works across UNSW Engineering labs and Graduate School of Biomedical Engineering platforms, including mock circulation loops and high-performance computing clusters for CFD simulations.
Yanhua Li is an Associate Professor in the Computer Science Department and Data Science Program at Worcester Polytechnic Institute (WPI), where he has served since 2021 (previously as Assistant Professor from 2015-2021). He is also an affiliated researcher at UMass Transportation Center (UMTC). His educational background includes dual PhDs: Computer Science from University of Minnesota, Twin Cities (2013) and Electrical Engineering from Beijing University of Posts and Telecommunications (2009), along with an MS (2006) and BS (2003) in Electrical Engineering from Sichuan University. Dr. Li's research focuses on artificial intelligence and spatial-temporal data science with applications in smart cities and urban intelligence. His work particularly emphasizes imitation learning and meta learning in AI for understanding and influencing urban human agents' decision-making strategies, such as taxi drivers' passenger-seeking behaviors and urban travelers' transit choices. His laboratory develops advanced computational methods for urban transportation systems, traffic prediction, and spatial-temporal data analytics. His publication record shows a strong trajectory in top AI and data science venues, with recent work bridging foundation models with urban computing, enhancing robustness in spatial-temporal representation learning, and applying generative models to urban traffic estimation. His research spans computer vision, reinforcement learning, generative modeling, and spatio-temporal data analysis with applications in transportation, environmental monitoring, and urban planning. Best Applied Data Science Paper Award at SDM 2019 NSF CAREER Award (2020) Runner-up for the 10-Year Impact Award for SIGSPATIAL Conference (2024, for 2014 paper) Dr. Li has secured significant research funding including an NSF CAREER award ($529k), multiple NSF grants totaling over $2 million, and industry collaborations with DiDi Chuxing Research. He has advised numerous PhD students who have gone on to faculty positions at institutions like San Diego State University and SUNY Binghamton University. His research group maintains active collaborations with industry partners including DiDi Chuxing, Pitney Bowes Inc., and NVIDIA. He leads several research initiatives including the CityLines project for urban transportation systems and has contributed to foundational work in spatial-temporal imitation learning. His laboratory continues to expand into new areas including applying large language models to urban dynamics prediction and developing advanced methods for environmental monitoring.
Dr. Pinon Hermida Victor is a Researcher at the Institute of Electronic Structure and Laser (IESL) under the Foundation for Research and Technology – Hellas (FORTH). He holds a PhD in Physics from the University of A Coruña (2011) and has conducted extensive research on Laser-Induced Breakdown Spectroscopy (LIBS), focusing on femtosecond lasers, double-pulse configurations, and applications in material analysis, archaeology, and environmental science. His career includes roles at Applied Photonics Ltd (UK) as Senior Applications Scientist (2014-2020) and postdoctoral fellowships at FORTH-IESL through the Marie Curie ATLAS program (2006-2008). Research interests span LIBS methodology development, optical fiber systems for high-power lasers, and software for spectral analysis. Notable contributions include portable LIBS instrument design and radiation-resistant optical components for nuclear facilities. Awards include the 2008 LIBS Contest and the 2011 Premio Extraordinario de Doctorado. Recent work focuses on applying LIBS to archaeological mollusc shell analysis for climate and environmental studies. He collaborates internationally on LIBS quantification challenges and instrument durability in harsh environments. Education: PhD in Physics (2011), University of A Coruña; Diploma in Physics (2001), University of Santiago de Compostela Key Roles: Senior Applications Scientist (Applied Photonics), Marie Curie Fellow (FORTH-IESL), Researcher (Laboratory of Industrial Applications of Lasers) Lab Affiliations: IESL-FORTH and University of A Coruña laser labs
Davide Scaramuzza is a Professor and Director of the Robotics and Perception Group at the University of Zurich. He holds a Ph.D. from ETH Zurich and has conducted postdoctoral research at the University of Pennsylvania and Stanford. His research focuses on autonomous drone navigation using visual and event-based sensors, leading to breakthroughs like AI drones outperforming human pilots in racing (Nature 2023). He pioneered algorithms for Mars helicopter navigation and developed the PX4 autopilot system. Key awards include the Kiyo-Tomiyasu IEEE Technical Field Award (2024), ERC Consolidator Grant (2019), and multiple best paper awards. His entrepreneurial ventures include co-founding Zurich-Eye (later Meta Zurich) and SUIND for agricultural drones. He co-authored the textbook Introduction to Autonomous Mobile Robots , widely used in academia. Research spans event camera algorithms, visual-inertial SLAM, and reinforcement learning for agile flight. His lab's work is featured in IEEE Spectrum, The Guardian, and Forbes. He advises UN initiatives on AI for disaster response and nuclear safety. Current projects include Graph-Generating State Space Models (CVPR 2024) and event-based vision for automotive systems (Nature 2024).
