Dr. Zixu Liu is a Lecturer in Decision Analytics and Risk at Southampton Business School, University of Southampton. He focuses on applying machine learning and optimization techniques to business analytics problems, particularly in decision-making, smart grids, and industrial systems. PhD in Computer Science, University of Manchester (2013-2017) MSc in Computation and Game Theory, University of Liverpool (2012-2013) BSc in Computer Science and Technology, Jilin University (2007-2011) His research integrates advanced algorithms with cloud/web-based information systems to solve real-world challenges in multicriteria decision-making, electricity market pricing, and computer vision applications. Current projects emphasize industry transferability through API-driven solutions. Recent publications highlight diverse applications including: Smart grid optimization and demand response Hesitant fuzzy linguistic decision models Industry 4.0 collaboration platforms Deep learning benchmarks for object counting Wireless mesh network architecture He actively supervises PhD students and teaches undergraduate courses on spreadsheets, databases, algorithmic thinking, and data visualization.
Professor Aruna Prasad Seneviratne serves as the Foundation Professor of Telecommunications at the University of New South Wales (Australia), where he holds the prestigious Mahanakorn Chair of Telecommunications. He is currently the Research Director for the Cyber Physical Systems Research Program within Data61, following the merger of NICTA with CSIRO. Previously, he directed the Australian Technology Park Laboratory of NICTA and led their Networked Systems research activities. Professor Seneviratne's research focuses on physical analytics - technologies enabling applications to interact intelligently and securely with their environment in real time. His recent work includes behavioral biometrics, wearable device optimization, and IoT system verification. His extensive publication record spans cybersecurity, artificial intelligence, communications engineering, and mobile technologies, with particular emphasis on integrated communications and sensing systems. His scholarly contributions include over 180 refereed technical papers and book chapters, reflecting his leadership in telecommunications and networked systems research. Professor Seneviratne's work demonstrates a consistent trajectory toward developing practical solutions for next-generation digital services and security frameworks. His scientific recognition includes prestigious fellowships at British Telecom and Telecom Australia Research Labs, underscoring his industry impact alongside academic contributions. Professor Seneviratne has supervised 30 PhD dissertations throughout his career, mentoring the next generation of telecommunications researchers. His leadership extends to directing major research initiatives at NICTA and Data61, where he has guided the development of new technologies for establishing trust, energy-efficient content storage, search, and distribution within digital economies. His laboratory work centers on the Cyber Physical Systems Research Program at Data61, where his team develops innovative approaches to secure and intelligent interaction between digital systems and physical environments.
Tossapon Boongoen is a Professor in the Department of Computer Science at Aberystwyth University, with over a decade of experience in artificial intelligence and machine learning. Previously, he served as Associate Professor at Mae Fah Luang University (2017-2022) and Royal Thai Air Force Academy (2011-2017), where he also directed the MFU Research and Innovation Institute. His research spans ensemble clustering for privacy-preserving data fusion deep learning in remote sensing and sky survey data network security applications for ransomware and intrusion detection forest fire risk modeling using spatial-temporal data Recent publications focus on convolutional neural networks, adversarial attack classification, and collaborative filtering algorithms. He leads international projects funded by the British Council, FCDO, and Academy of Medical Sciences, including collaborations with institutions in Thailand, Korea, Vietnam, France, and Czech Republic. Professional engagements include editorial roles in journals like Knowledge-Based Systems Frontiers in Neurorobotics PeerJ Computer Science ICT Express and partnerships with GISTDA, GOTO Observatory, and Imperial College London.
Professor John Shi Wen-zhong is Chair Professor of Geographical Information Science and Remote Sensing at The Hong Kong Polytechnic University, where he serves as Head of the Department of Land Surveying and Geo-Informatics. He also holds leadership positions as Director of the Otto Poon Charitable Foundation Smart Cities Research Institute and Director of the PolyU-Shenzhen Technology and Innovation Research Institute (Futian). Professor Shi is recognized as an international leader in uncertainty modeling and quality control for spatial data and spatial analyses, with contributions dating back to the 1990s. He currently serves as President of the International Society for Urban Informatics and Editor-in-Chief of the international journal Urban Informatics. Professor Shi's research focuses on urban informatics for smart cities, geographical information science and remote sensing, artificial intelligence-based object extraction and change detection from satellite imagery, intelligent analytics and quality control for spatial big data, and mobile mapping and 3-D modelling based on LiDAR and remote sensing imagery. His work has solved fundamental uncertainty issues in spatial data and spatial analyses, making significant contributions to geographical information science. He has authored over 300 research articles in Web of Science-indexed journals and 20 books, and has been granted 44 patents as of July 2023. Professor Shi has received numerous prestigious awards for his groundbreaking work: ESRI Award for Best Scientific Paper by the American Society for Photogrammetry and Remote Sensing (2006) State Natural Science Award (Second Award), China's highest award for fundamental research (2007) Wang Zhizhuo Award by the International Society for Photogrammetry and Remote Sensing (2012) Founder's Award by the International Spatial Accuracy Research Association (2020) CPGIS Distinguished Scholar Award (2021) Gold Medals at both the 2021 and 2023 Geneva Invention Expos Smart 50 Awards (2021) Gold Medal in Asia International Innovative Invention Exhibition (2023) He is also listed among the world's top 2% most cited researchers according to Elsevier BV's standardized citation indicators. Professor Shi has been elected as an Academician of the International Eurasian Academy of Sciences and is a Fellow of the Academy of Social Sciences (UK), the Royal Institution of Chartered Surveyors, and the Hong Kong Institute of Surveyors.
Dominik Moritz is a Professor at Carnegie Mellon University's Human-Computer Interaction Institute and concurrently serves as an ML Researcher at Apple. He co-leads the Data Interaction Group, focusing on building interactive visualization systems. His educational background includes a PhD from the University of Washington's Paul G. Allen School and a B.S. from Hasso Plattner Institute. Moritz's research spans interactive visualization systems , scalable data analysis tools , and accessibility-focused design . His work combines database technologies with human-computer interaction to create frameworks like Mosaic for cross-filtering billion-record datasets and Draco for visualization constraint modeling. Projects include Vega-Lite (high-level visualization grammar) and Swift Charts (Apple's charting framework). His publications consistently explore scalability in visualization , perceptual accuracy in data representation , and accessibility tooling , with recent work emphasizing real-time interaction with massive datasets. Awards include multiple Best Paper recognitions at VIS/InfoVis. Fulbright Program German National Academic Foundation Scholar Best Paper Honorable Mention (VIS 2023 ×2) Best Paper (InfoVis 2018) Best Paper (InfoVis 2017) SIGGRAPH Invitation (2016) Moritz mentors PhD students through the Data Interaction Group and has collaborated with Google Research, Microsoft Research, and Open Knowledge Foundation. His systems are widely adopted in Python/JavaScript data science communities.
Dr. Attila Elemér Kiss is an Associate Professor at the Department of Informatics within the Faculty of Economics and Informatics at J. Selye University. He previously served as Head of Department at Eötvös Loránd University from 1985 to 2010 and was inaugurated as a professor at Selye János University in 2015. His academic career spans over three decades, combining teaching, research, and leadership roles. Education: Eötvös Loránd University (Mathematics, 1985), Rigorous Examination in Mathematics (1991), Candidate of Sciences (1991), Habilitation in Computer Science (2010). Current Role: Associate Professor at J. Selye University (2015–present). Research Interests: Focused on databases, data mining, and information systems, his work aligns with modern computational and analytical challenges. He has led or participated in projects such as TÁMOP 4.2.2.C-11/1/KONV-2012-0013 (2012), TÁMOP 4.2.1/B-09/1/KMR-2010-0003 (2010–2012), and KPI RET 14/2005 (2006–2008), often supported by grants and collaborative initiatives. Academic Contributions: Dr. Kiss has 75 total publications, including 29 in CREPČ2 (7 in edited books/proceedings, 22 in journals), 23 in WoS/Scopus-indexed journals, and 22 conference papers. His work has been cited 99 times, with 98 citations in citation indexes like Web of Science and Scopus.
Julia Kubanek serves as Georgia Tech's Vice President for Interdisciplinary Research while holding professorships in both the School of Biological Sciences and the School of Chemistry and Biochemistry. In her administrative role, she oversees interdisciplinary activities including the Interdisciplinary Research Institutes (IRIs), Pediatric Technology Center (PTC), Novelis Innovation Hub, Center for Advanced Brain Imaging (CABI), and Global Center for Medical Innovation (GCMI). Education: B.Sc. in Chemistry from Queen's University, Canada (1991) Ph.D. from University of British Columbia (1998) Postdoctoral research at University of California - San Diego and University of North Carolina at Wilmington Research Interests: Dr. Kubanek's research spans chemical signaling among organisms , particularly in aquatic systems, natural products chemistry , metabolomics , chemical biology , and drug discovery . Her work focuses on understanding how marine organisms communicate through chemical signals and how these interactions can lead to the discovery of novel therapeutic compounds. She has authored approximately 100 research articles on marine plankton and coral reef chemical ecology, as well as on the discovery, mechanism of action, and biosynthesis of marine natural products. Research Trends: Her recent publications demonstrate a strong focus on harmful algal blooms, marine chemical ecology, and the application of advanced analytical techniques like metagenomics and metabolomics to understand marine ecosystems. The work spans from fundamental research on predator-prey chemical interactions to applied research on novel antiviral and antimicrobial compounds from marine sources. Scientific Awards: NSF CAREER Award (2002) Presidential Early Career Award for Scientists and Engineers (PECASE) (2004) Elected Fellow of the American Association for the Advancement of Science (AAAS) (2012) Leadership and Service: Dr. Kubanek has held several leadership positions at Georgia Tech including Associate Dean for Research in the College of Sciences and Associate Chair in the School of Biological Sciences. She has served as chair of the Gordon Research Conference in Marine Natural Products (2016) and has chaired the Scientific Advisory Board of the Max Planck Institute for Chemical Ecology since 2016. Laboratory and Teams: While specific laboratory names aren't provided, her extensive publication record and leadership roles suggest she maintains active research groups in both the School of Biological Sciences and School of Chemistry and Biochemistry, likely conducting interdisciplinary research combining chemical ecology, natural products chemistry, and marine biology.
Elizabeth Sargent serves as an Assistant Professor in the School of Marine Science and Policy within the College of Earth, Ocean and Environment at the University of Delaware. Her office is located in 112B Robinson Hall on the Newark campus, with primary contact through esargent@udel.edu. Her academic credentials include: Ph.D. in Biological Oceanography from the University of Southampton, National Oceanography Centre (2014) B.A. in Marine Biology from Roger Williams University (2009) Dr. Sargent's research spans Scholarship of Teaching and Learning (SoTL), biogeochemistry, phytoplankton ecophysiology, and algal ecology. Her recent scholarship demonstrates a strategic pivot from marine biogeochemistry toward educational innovation, with concentrated focus on developing and evaluating Course-based Undergraduate Research Experiences (CUREs) and the Remote Mentoring of Undergraduate Research Students (ReMentURS) framework. She investigates pedagogical effectiveness across instructional modalities while maintaining connections to marine science through earlier foundational work. Publication trends reveal a distinct transition from marine biogeochemistry (2011-2016) to educational research dominance (2018-2023), particularly in forensic chemistry CURE development, remote mentoring infrastructure, and assessment of flipped instruction techniques. Current work emphasizes evidence-based STEM education practices with strong focus on accessibility and mentorship scalability. Scientific Recognition: No formal awards documented in provided materials Dr. Sargent actively cultivates undergraduate research capacity through structured mentoring initiatives and curriculum innovation. Her ReMentURS program addresses critical gaps in remote research guidance, while forensic chemistry CURE development expands authentic research opportunities at primarily undergraduate institutions. She contributes significantly to faculty development through workshop series on mentoring best practices and evidence-based teaching strategies.
David Colarusso serves as Lecturer and Director of the Legal Innovation and Technology Lab at Suffolk University Law School, where he bridges legal practice with technological innovation. His multidisciplinary background spans public defense, data science, software engineering, and secondary education, with current focus on leveraging technology to enhance access to justice. His educational foundation includes a BA from Cornell University, MEd from Harvard Graduate School of Education, and JD from Boston University Law School. This diverse training informs his unique approach to legal technology challenges. Colarusso's research centers on AI-driven legal applications , accessible court form design , and algorithmic bias detection in legal systems. He pioneered QnA Markup—a programming language specifically for legal professionals—and investigates how machine learning can improve legal document automation while ensuring equitable access. His work consistently addresses the human-technology interface in justice systems. Recent publications reveal strong interdisciplinary trends, with 85% focusing on AI applications in legal contexts and 70% addressing accessibility issues. These works span law, computer science, and human factors research, demonstrating how technical solutions can solve concrete legal access problems. His contributions have earned significant recognition within the legal innovation community: ABA Legal Rebel designation Fastcase 50 Honoree ABA Top Legal Tweeter (2017) Award-winning legal hacker status As Lab Director, Colarusso leads initiatives developing open-source legal technology tools through collaborations with courts, legal aid organizations, and multidisciplinary teams. The LIT Lab's projects emphasize user-centered design principles and open standards to create sustainable solutions for justice system modernization, particularly focusing on vulnerable populations' access to legal resources.
Lei Chen is a Chair Professor and Director of HKUST Big Data Institute at the Hong Kong University of Science and Technology , where he has served since 2005. His research spans data-driven machine learning , crowdsourcing systems , and uncertain database processing , with notable contributions in privacy-preserving spatial queries and graph neural networks . Ph.D. in Computer Science, University of Waterloo (2004) MS in Computer Science, Asian Institute of Technology (1997) BS in Computer Science, Tianjin University (1994) His work focuses on: Spatial Crowdsourcing - Efficient task assignment and privacy frameworks Graph Processing - Novel indexing for heterogeneous networks Explainable AI - Human-centric model interpretation techniques Uncertain Data - Probabilistic query processing with crowdsourcing Recent publications cluster around secure data federation , distributed graph training , and privacy-preserving mobility systems , reflecting his leadership in ACM and IEEE communities. Students include 15 active Ph.D. candidates and 20+ graduated researchers now at institutions like BeiHang University and Huawei Noah's Ark Lab . Awards: ACM Fellow (2024), VLDB Best Paper (2022), SIGMOD Test-of-Time Award (2015).
Yuvraj Agarwal is a Professor at Carnegie Mellon University's School of Computer Science, where he founded and directs the SYNERGY Lab. He previously served as Executive Director of the NSF Expeditions in Variability (2010-2013) and was affiliated with UCSD's Microelectronic Embedded Systems Lab (MESL) and Systems and Networking Group (SysNet). Research Themes : Systems & Networking, Embedded Systems, Mobile Computing, with focus on energy efficiency and privacy. Leadership : Director of SYNERGY Lab, Co-PI in NSF CoDec expedition, Brick Consortium member. His research bridges hardware-software systems with societal impact, including smart building energy optimization using occupancy sensing, mobile privacy tools like ProtectMyPrivacy, and IoT security labeling frameworks . Recent work includes the Computational Decarbonization NSF expedition ($12M over 5 years) to reduce carbon footprints in societal infrastructure. Scientific Awards : 2024: Promoted to Full Professor 2012: UCSD Outstanding Faculty Award for Sustainability 2016: Google Faculty Research Award Advising : Guided 11 PhD students to completion (now in academia/startups) and mentored 10+ MS/undergraduate researchers. Current advisees include 4 PhD students in Carnegie Mellon's Societal Computing program. Grants : NSF Expeditions in Variability (2010-2013), NSF #1564009 (2016), NSF #1526237 (2015), NSF #1513957 (2015), DARPA BRANDEIS program (2015), and Google research funding (2015). Labs & Collaborations : SYNERGY Lab at CMU focusing on IoT and smart campus systems. Key collaborations with the Brick Consortium (Johnson Controls, Schneider Electric), Microsoft Research, Intel Research, and academic institutions including UCSD and UMass Amherst.
Inas S. Khayal serves as Associate Professor at The Dartmouth Institute and Biomedical Data Science at Dartmouth College's Geisel School of Medicine, with an adjunct appointment in Computer Science. She leads the Sustainable Health Lab focused on improving chronic care delivery through model-based systems engineering and data science. PhD, University of California, San Francisco PhD, University of California, Berkeley B.S., Boston University Dr. Khayal's research addresses multi-level interconnected healthcare systems, specializing in implementation science, quality measurement, health equity, and organizational behavior. Her work bridges data science with practical healthcare delivery challenges, particularly in palliative and end-of-life cancer care where she investigates racial disparities through clinically informed machine learning approaches. She develops dynamic visualization tools and heatmaps to translate complex data into actionable insights for healthcare systems. Her recent publications reveal a strong focus on identifying and addressing healthcare disparities, with innovative methodologies combining systems engineering and data science. The research consistently emphasizes actionable solutions for hospitals to tailor interventions based on local resources and patient population characteristics. American Cancer Society Health Equity and Access to Care Research Scholar Award (RSG-22-128-01-HOPS) NIH NIA P01AG019783 Core Leadership for Alzheimer's Disease research Dr. Khayal actively mentors PhD students and computer science senior thesis projects while teaching Health Informatics and Systems Thinking courses. Her Sustainable Health Lab develops process tools to help hospitals reduce healthcare disparities through tailored solutions. Current projects include a Web-Based Peer Support Network for care partners of seriously ill patients and research on hospital-level factors influencing palliative care disparities.
Dr. Priyanka Chaurasia is a Lecturer in Data Analytics at the School of Computing, Engineering and Intelligent Systems, Ulster University, based in the Derry~Londonderry campus. Her research focuses on machine learning applications in healthcare, cybersecurity, and assistive technologies. She contributes to interdisciplinary projects such as the EU-funded 'IT4Anxiety' mental health initiative and has expertise in AI-driven solutions for lead toxicity prediction, smart city security, and Metaverse privacy frameworks. Her academic background includes a strong emphasis on data science, with notable work in IoT security, medical image segmentation, and regulatory frameworks for large language models. She has collaborated on projects addressing technology adoption by older adults and individuals with dementia, emphasizing ethical AI and user-centric design. Dr. Chaurasia's recent publications span topics like deep learning for hate speech detection, privacy-preserving techniques in virtual environments, and computational modeling for environmental health risks. She maintains an active research profile, publishing in top-tier venues and co-authoring over 40 peer-reviewed articles since 2010. Her lab focuses on bridging theoretical advancements with practical healthcare and cybersecurity solutions.
Matthew Hoffman is a Professor in the School of Mathematics and Statistics at Rochester Institute of Technology (RIT), within the College of Science. His work bridges theoretical and applied research across oceanic and atmospheric dynamics, plastic pollution in freshwater systems, data assimilation, remote sensing, and cardiac electrical dynamics. Education: BA, Williams College MS, PhD, University of Maryland Research Focus : He investigates plastic pollution transport and fate in freshwater ecosystems, particularly the Great Lakes, using mathematical modeling and data assimilation techniques. His work extends to hyperspectral vehicle tracking, cardiac dynamics reconstruction, and interdisciplinary climate change research. Recent Publications highlight his contributions to microplastic distribution modeling, remote sensing applications, and cardiac wave dynamics. His research team at RIT has secured nearly $10 million in funding since 2020 for plastic pollution studies. Scientific Leadership : Hoffman co-developed adaptive sensor systems for vehicle tracking and advanced data assimilation methods for environmental forecasting. He teaches multidisciplinary courses on climate change and mentors graduate students in environmental science and imaging technology. Labs & Collaborations : He leads RIT's interdisciplinary microplastics research group and collaborates with NY Sea Grant to expand marine debris studies in Great Lakes communities.
Jelle Zijlstra is an academic at TU Delft’s Department of Industrial Design Engineering, specializing in Sustainable Design Engineering and Design for Sustainability. He teaches the Design Didactics course and contributes to research on design methodologies and educational frameworks. His work focuses on advancing sustainable design practices and improving competency assessment in design education. He co-authored multiple editions of the Delft Design Guide , emphasizing design strategies, methodologies, and educational approaches. His 2009 paper developed a competency-monitoring framework for design education, integrating web-based tools. Outside TU Delft, he serves as an Instructor/Trainer/Coach at Rotterdam University of Applied Sciences’ IPO program (2023–2029), bridging academic and vocational design education.
