Dr David Walker is a Senior Lecturer in Computer Science at the University of Exeter and a member of the Institute for Data Science and Artificial Intelligence . He also contributes to the Environmental Intelligence @Exeter research network. Education: PhD in Computer Science, University of Exeter (2008–2013) BSc (Hons) in Computer Science, University of Exeter (2004–2007) Research Interests Dr Walker’s work sits at the intersection of multi-objective optimisation , evolutionary computation , explainable AI and hyper-heuristics . He develops algorithms and visual analytics that help engineers and scientists understand complex optimisation landscapes, with recent emphasis on renewable-energy planning (especially offshore wind farms) and trustworthy AI systems. Publication Trends Between 2022 and 2025 he produced a prolific stream of articles on explainable optimisation , many-objective wind-farm design and visual analytics for evolutionary algorithms . These works combine rigorous algorithmic innovation with real-world case studies, demonstrating a clear trajectory toward transparent, human-centred AI for engineering decision-making. Scientific Awards No specific awards or fellowships are mentioned in the provided material. Advising & Funding No explicit list of PhD students, post-docs or grant awards is supplied. Laboratory & Teams Dr Walker is affiliated with the Institute for Data Science and Artificial Intelligence and the Environmental Intelligence @Exeter network, indicating collaborative, interdisciplinary research environments.
Dr. James N. Gilmore is an Associate Professor of Media and Technology Studies and Graduate Coordinator in the Department of Communication at Clemson University's College of Behavioral, Social and Health Sciences. He joined Clemson in 2018 after completing his PhD at Indiana University and has established himself as a leading scholar in media technology studies, with expertise in wearable technologies, datafication, and media infrastructure. Dr. Gilmore's educational background includes: Ph.D. in Communication and Culture from Indiana University (2018) M.A. in Film and Television from University of California, Los Angeles (2013) B.A. in Film and Media Studies from University of South Carolina (2011) His research focuses on the cultural politics of media and communication technologies, particularly how computational technologies convert human behavior to data (datafication). Dr. Gilmore examines how everyday devices like smartwatches, fitness trackers, and body cameras reinforce systems of normalcy, surveillance, and solutionism across health, labor, accessibility, law enforcement, and other domains. His work bridges theoretical frameworks from media studies, cultural studies, and science and technology studies to analyze the social implications of emerging technologies. Dr. Gilmore's publications demonstrate consistent engagement with emerging technologies across multiple domains. His recent work spans wearable technologies, virtual reality, AI platforms like ChatGPT, streaming services, and smart home devices, revealing patterns in how technologies mediate everyday life while raising critical questions about privacy, surveillance, accessibility, and corporate power. His scholarship consistently connects technological developments to broader social, political, and cultural contexts. Dr. Gilmore has received numerous honors and awards for his research and teaching: Top Paper Award, Popular Communication Division, Southern States Communication Association (2024) Outstanding Teaching of the Year (Junior Tenure-Track), College of Behavioral, Social, and Health Sciences (2022-2023) Outstanding research publication award for 'Securing the kids' (2022) Research Faculty Spotlight (Spring 2021) Ray Camp Award for Most Outstanding Research Paper (2018) As Graduate Coordinator, Dr. Gilmore actively mentors students, with numerous co-authored publications featuring graduate and undergraduate researchers. His students have contributed to research on AI adoption, virtual reality, wearable technologies, and platform politics. Dr. Gilmore has secured internal research funding at Clemson University, including recognition through the university's research reporting system. His book projects, including the forthcoming DeGruyter Handbook of Wearable Technologies and Society, represent significant scholarly contributions that bring together international researchers. Dr. Gilmore leads research initiatives focused on wearable technologies and media infrastructure, with his recent book 'Bringers of Order' establishing him as a leading voice in wearable technology studies. He is currently editing a comprehensive handbook that will expand this research area significantly.
Julianne Scamardo serves as Assistant Professor in the Department of Watershed Sciences at Utah State University, appointed in August 2024. Her research bridges fluvial geomorphology and ecosystem resilience, focusing on river-floodplain interactions in disturbance-prone environments. Education: PhD in Fluvial Geomorphology (Geosciences), Colorado State University, 2023 MS in Geosciences, Colorado State University, 2019 BS in Environmental Science (Emphasis: Geosciences), The University of Texas, 2017 Research Focus: Dr. Scamardo investigates form-function relationships in fluvial systems to predict resilience against floods, fires, and droughts. Her work centers on temporary storage mechanisms for water, sediment, and organic matter across floodplains, wetlands, and non-perennial streams. She pioneers field-measurement techniques , open-access modeling tools , and low-cost remote sensing applications for real-world implementation beyond academic settings. Publication Trends: Her 2025 publications reveal converging expertise in floodplain classification using topographic data, river-flood dynamics modeling, and policy analysis of rangeland restoration. These works demonstrate methodological integration of high-resolution geospatial analysis with practical restoration frameworks for western U.S. ecosystems. Academic Engagement: Actively recruiting graduate and undergraduate researchers for her laboratory, Dr. Scamardo teaches WATS 3700 (Fundamentals of Watershed Science) while developing community-focused restoration approaches. She emphasizes accessible science translation for land managers and policymakers through low-tech process-based restoration initiatives.
Amael Poulain is a hydrogeology researcher at the University of Namur specializing in karst systems and groundwater dynamics. With a PhD completed in 2017 under supervisor Hallet V., Poulain has established a strong research profile focusing on vadose zone processes, tracer testing, and hydrological monitoring in karst environments. Their work combines field measurements with computational modeling to understand complex groundwater systems in Belgian karst regions. PhD in Geology (2017), University of Namur Principal Investigator on 6 research projects (2017-2023) 16 research outputs including journal articles and conference contributions Recipient of Young Karst Researcher Prize (2015) Active contributor to international karst research conferences Poulain's research focuses on understanding groundwater recharge processes in karst systems through innovative monitoring techniques. Their work examines solute transport, breakthrough curve analysis, and the impact of flash flood events on groundwater systems. Key contributions include developing ultra-portable fluorometry for dye tracing in remote karst environments and investigating the relationship between surface water features and underground flow paths in Belgian karst regions. Analysis of Poulain's 16 research outputs reveals consistent focus on experimental hydrogeology in karst environments, particularly using tracer tests and novel monitoring technologies. The research spans vadose zone processes, breakthrough curve analysis, and the development of field instrumentation for hydrological monitoring. Recent work (2020-2023) shows increasing emphasis on technological applications including fluorimeter industrialization and gravity monitoring techniques. Young Karst Researcher Prize (2015) awarded at conference in Birmingham, UK Recognition for contributions to groundwater research and karst hydrology Active participation in international karst research community Poulain leads multiple research projects including STREAM fluorimeter industrialization and eco-village construction expertise. Their work bridges academic research and practical applications through spin-off development for hydrological monitoring equipment. As Principal Investigator on projects like 'Expertise of tracing test at the ponds of Villeneuve,' Poulain demonstrates strong grant acquisition and project management capabilities. The research involves collaboration with multiple institutions across Belgium's karst regions. Poulain's laboratory work focuses on hydrological monitoring in karst environments, particularly through the STREAM project which develops fluorometric solutions for groundwater monitoring. Their research utilizes cave percolation monitoring, gravity measurements, and electrical resistivity tomography to study water movement through vadose zones. The work is conducted primarily in Belgian karst regions including Rochefort and Furfooz, with emphasis on practical applications for water resource management.
Roie Levin is an Assistant Professor at Rutgers University's Department of Computer Science. He received his PhD in Algorithms, Combinatorics and Optimization from Carnegie Mellon University in 2022, advised by Anupam Gupta. Prior to that, he worked at the Allen Institute for Artificial Intelligence (2015-2017) and earned dual BSc degrees in Computer Science/Applied Mathematics and Mathematics from Brown University (2015). Before joining Rutgers, he was a Fulbright Postdoctoral Fellow at Tel Aviv University under Niv Buchbinder. Current Role: Assistant Professor in Computer Science Academic Training: PhD (2022) CMU, BSc (2015) Brown University Postdoctoral: Fulbright Fellow at Tel Aviv University Levin's research focuses on approximation algorithms for uncertain environments (online/dynamic/streaming models) and submodular function optimization. His work spans theoretical foundations and practical implementations across distributed systems, geometric constraints, and reinforcement learning paradigms. Teaching includes graduate and undergraduate algorithms courses (CS 344, CS 513) with emphasis on problem-solving techniques, computational complexity, and modern algorithmic trends. His publications showcase expertise in online algorithms, submodular optimization, and approximation theory with applications in clustering, caching, and machine learning. The 2025 articles demonstrate continued exploration of online consistency and contention resolution, while 2023-2024 works focus on submodular optimization under uncertainty and dynamic environments. Earlier publications (2015-2017) cover semantic parsing, geometric approximation, and planar graph optimization. Fulbright Postdoctoral Fellow Levin's research connects theoretical guarantees with practical implementations, bridging classical algorithm design with modern machine learning applications. His recent work explores primal-dual methods in online settings and robust subspace approximation techniques for streaming data environments.
Vitaveska Lanfranchi is a Senior Research Fellow at the University of Sheffield , School of Computer Science, focusing on Human-Computer Interaction , Social Media , and Visual Analytics . Her work addresses real-time data analysis for emergency response and knowledge management, with projects funded by EPSRC, UK/SBRI, and EU Framework 6. Research Interests : Human-Computer Interaction Social Media for Emergency Response Visual Analytics Knowledge Management Mobile Interaction Recent publications (2008–2012) explore semantic user networks, knowledge dashboards, hybrid search techniques, and AI usability, particularly in aerospace engineering and emergency response. Projects like Randms and WeKnowIt emphasize collective intelligence and web-scale data analysis. Contact : v.lanfranchi@dcs.shef.ac.uk
Larry P. Heck is a Professor with a joint appointment in the School of Electrical and Computer Engineering and School of Interactive Computing at the Georgia Institute of Technology. He holds the Rhesa S. Farmer Advanced Computing Concepts Chair and is a Georgia Research Alliance Eminent Scholar . Education: BSEE, Texas Tech University (1986) MSEE, Georgia Institute of Technology (1989) PhD EE, Georgia Institute of Technology (1991) His research focuses on conversational AI , dialogue systems , and machine learning applied to natural language processing and speech recognition . He pioneered early industrial applications of deep learning in speech processing and has contributed to advancements in multimodal interaction, knowledge distillation, and real-time question answering systems. Recent publications emphasize moral reasoning in AI , multimodal dialogue , and large-scale dataset creation for conversational systems. His work bridges language modeling , sensor fusion , and ethical AI through innovations in contextual reasoning and interface masking. Scientific Distinctions: IEEE Fellow (2020) IEEE Signal Processing Society Best Paper Award Academy of Distinguished Engineering Alumni, Georgia Tech (2017) Distinguished Engineer Award, Texas Tech University (2017) Fellow, National Academy of Inventors (2025) He has secured significant funding from DARPA and NSA for speaker recognition systems and has led cutting-edge research at institutions including Microsoft, Google, and Samsung. His lab focuses on conversational systems and deep learning for speech and multimodal data.
Professor Iain Suthers is a Professor at the University of New South Wales in the School of Biological, Earth & Environmental Sciences . He is based at the Sydney Institute of Marine Science , a collaborative hub involving Sydney-based universities and government agencies. His career spans 34 years at UNSW since 1991, following a PhD in Canada and postdoctoral work in Norway and Australia. Key Research Themes Marine ecosystem dynamics influenced by the East Australian Current Larval fish ecology and connectivity Zooplankton size spectra and carbon transport Artificial reef ecology and fish passage solutions Climate change impacts on marine and estuarine systems Leadership Inaugural Chair of NSW-IMOS (2007–2012) Currently leads the IMOS Larval Fish Monitoring subfacility Methodology Oceanographic field campaigns Long-term biodiversity databases Ecological modelling Collaborative research with 6 PhD students and colleagues Recent Publications emphasize biophysical interactions in western boundary currents, larval fish recruitment, and innovative fish passage designs like the Tube Fishway. His team contributes to global databases (e.g., BioTIME 2.0) and conservation-focused studies on fish migration fragmentation and crab ecology.
Rafail Ostrovsky is a Distinguished Professor of Computer Science and Mathematics (by courtesy) at UCLA's Henry Samueli School of Engineering and Applied Science. He holds the Norman E. Friedman Chair in Knowledge Sciences and serves as Director of the Center for Information and Computation Security. With over 350 refereed publications and 15 issued USPTO patents, he is one of the most influential researchers in theoretical computer science and cryptography. Professor Ostrovsky's research spans cryptography, network algorithms, and search and classification of large-scale, high-dimensional data. His work focuses on foundational aspects of secure computation including zero-knowledge proofs, secure multi-party computation, private information retrieval, and privacy-preserving data analysis. His contributions to streaming algorithms, metric embedding, and clustering for high-dimensional data have established important theoretical frameworks with practical applications. He has pioneered techniques for secure computation that maintain privacy while enabling collaborative data analysis. His recent publications demonstrate continued leadership in advancing secure computation protocols, with emphasis on efficiency improvements, practical implementations, and novel applications in blockchain technology and distributed systems. His work consistently addresses fundamental theoretical challenges while maintaining relevance to real-world security problems, bridging the gap between theoretical cryptography and practical security solutions. Selected Honors: 1993 Henry Taub Prize 2017 IEEE Computer Society Edward J. McCluskey Technical Achievement Award 2018 RSA Award for Excellence in Mathematics 2022 W. Wallace McDowell Award (the highest award given by the IEEE Computer Society) Professor Ostrovsky has served in significant leadership roles including chair of the IEEE Technical Committee on Mathematical Foundations of Computing (2015-2018) and chair of the IEEE FOCS 2011 Program Committee. He has served on over 40 international conference program committees and currently serves on the editorial boards of the Journal of ACM and Algorithmica Journal. As a Fellow of the National Academy of Inventors, AAAS, ACM, IEEE, and IACR, and as a foreign member of Academia Europaea, his contributions have been widely recognized across multiple disciplines. He actively teaches advanced courses including Introduction to Cryptography (CS183), Foundations of Cryptography (CS282A/M209A), and Cryptographic Protocols (CS282B/M209B), mentoring the next generation of security researchers while continuing to push the boundaries of secure computation through his research.
Asier Perallos Ruiz is a Professor in the Faculty of Engineering at the University of Deusto, specializing in the Department of Computing, Electronics and Communication Technologies. His research focuses on RFID technology, wireless sensor networks, and computational intelligence applications with significant contributions to intelligent transport systems and antenna design. Dr. Perallos Ruiz's research interests span multiple domains with a focus on RFID technology , Wireless sensor networks , Internet of Things (IoT) , Computational intelligence , Evolutionary algorithms , and Intelligent transport systems . His work bridges theoretical advancements with practical applications, particularly in transportation systems, healthcare, and industrial automation. His research often involves interdisciplinary collaboration across engineering disciplines. His publication portfolio shows a consistent trend toward improving RFID systems, developing efficient anti-collision protocols, and applying computational intelligence to real-world problems. Recent work has focused on polarization-diversity rotation sensing, customizable RFID platforms, and the integration of RFID with IoT applications. His research demonstrates a progression from foundational RFID technology to more complex system integration and application-specific solutions. Dr. Perallos Ruiz has supervised several graduate students including Muralter Florian (2021), Arjona Aguilera Laura (2018), Cmiljanic Nikola (2018), Lopez Garcia Pedro (2016), and Moreno Emborujo Asier (2016). His research has been supported by various projects focusing on RFID technology, intelligent transportation systems, and wireless communication applications. He leads research teams focused on RFID systems development, wireless sensor networks, and computational intelligence applications. Current work appears to be advancing RFID sensing capabilities, energy-efficient protocols, and system integration for practical applications in transportation and industry.
Robb W Lindgren is a Professor at the University of Illinois at Urbana-Champaign with appointments in Curriculum and Instruction and Educational Psychology . He serves as Associate Dean for Research in the College of Education and holds affiliations with the National Center for Supercomputing Applications (NCSA) , Beckman Institute for Advanced Science and Technology , and Center for Social & Behavioral Science . His research focuses on Embodied learning through gesture and physical interaction Design of mixed/augmented reality educational systems Collaborative STEM education with immersive technologies Recent publications highlight his work in: Biochemistry simulations using haptic feedback (2024) VR-based spatial reasoning for astronomy education (2023) Metaverse learning environments with theory-driven design (2023) Climate change simulations with full-body tracking (2022) His research group explores how physical movement and gestural interfaces shape scientific understanding and conceptual change. Key collaborations include work with Jee Hyang Park , Jun Kang , and Thomas Kim , focusing on Gesture-mediated collaboration XR learning analytics Agency in embodied design
Robert Brunner serves as Professor of Astronomy at the University of Illinois at Urbana-Champaign, where he bridges astrophysical research with computational innovation. His work focuses on extracting knowledge from massive astronomical datasets through advanced statistical and machine learning techniques, while also extending methodologies to finance and agricultural applications. Research interests center on developing machine learning algorithms (random forests, deep neural networks, Bayesian estimation) for astronomical data analysis, cosmological parameter constraints via n-point clustering measurements, and hardware acceleration using GPUs/cloud systems. His interdisciplinary approach spans source classification, transient phenomena detection in surveys like SDSS and DES, and applications in financial time-series analysis and agricultural remote sensing. Recent publications (2019-2025) reveal strong cross-domain expertise: astronomical catalogs for Rubin Observatory and Spitzer surveys coexist with financial market analysis using community detection methods and agricultural computer vision systems. Key methodological threads include spatio-temporal forecasting, multimodal learning for earnings calls, and anomaly detection via extended isolation forests, demonstrating consistent innovation in handling petascale datasets across scientific boundaries.
Rebecca Yang is a Visiting Professor at RMIT University's School of Property, Construction and Project Management, specializing in building, construction, and distributed renewable energy research. She integrates theoretical knowledge with cutting-edge technologies to advance sustainable urban development. Her research focuses on solar energy applications in buildings, construction innovation, and international energy policy frameworks through her leadership roles in the International Energy Agency's Photovoltaic Power Systems Programme (PVPS) Task 15 and Solar Heating and Cooling Programme (SHC) Task 66. She established RMIT's Solar Energy Application Lab and has 8 years of BIPV expertise. Notable achievements include: Australian representative in international BIPV standardization (IEC 63092) 2019 Facilitator Prize for BIPV Tool development She supervises research projects related to: Solar building envelope optimization Machine learning for energy systems Fire safety in BIPV installations Blockchain-enabled energy trading Circular economy for PV waste
Dr. Fei Chiang is an Associate Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. Her research focuses on data management , with emphasis on data quality, data privacy, information extraction , and contextual data cleaning . She has collaborated with IBM Global Services and Microsoft Research on improving data quality in enterprise systems. Key research themes include graph databases , temporal data analysis , and privacy-aware data processing Recent publications explore federated learning , SQL understanding in LLMs , and temporal graph constraints Industry collaborations with IBM Toronto Lab and Microsoft Research have led to innovations in data cleaning automation and semantic analysis. Her work bridges database theory with machine learning applications in healthcare inventory optimization and flight reliability prediction.
Lei Bu is a Professor and Vice Dean at the Software Institute , Nanjing University . He leads research in formal verification, cyber-physical systems, and software engineering, with a focus on bounded model checking and hybrid system analysis. B.Sc. and Ph.D. in Computer Science from Nanjing University (2004, 2010) Visiting student at Carnegie Mellon University and University of Texas at Dallas His research integrates formal methods and machine learning for verifying complex systems like IoT and software with real-time constraints. Key projects include BACH Toolset and BRICK for reachability analysis. Recent publications demonstrate expertise in hybrid system verification , cache side-channel detection , and parallel code analysis frameworks . His work bridges theoretical advancements with practical applications in safety-critical systems. Zhongchuang Software Talent Award (2023) CCF-IEEE CS Young Computer Scientist Award (2022) High-Tech Software Innovation Awards (2019-2023) As Principal Investigator, he leads major projects funded by National Science Foundation of China and Jiangsu Natural Science Foundation (2020-2027). Current tools include BACH for hybrid systems and MLB for Java symbolic execution.
