Teresa Hirzle is a Tenure Track Assistant Professor at the Department of Computer Science , University of Copenhagen , specializing in Human-Centred Computing . Her research focuses on Human-Computer Interaction (HCI) , Virtual Reality (VR) , Extended Reality (XR) , and Gaze-Based Interaction . Research Interests: Designing interaction techniques for immersive environments Eye movement analysis for educational applications Addressing digital eye strain in interactive systems Evaluating user experience in VR/AR Recent Research Trends: Her recent publications examine AI representation in VR co-creation, VR sickness in locomotion, eye strain in gaze-driven systems, and hybrid applications of comics/AR. She also explores pedagogical implications of eye tracking in remote learning. Contact: Email: tehi@di.ku.dk Office: Sigurdsgade 41, 2200 København N.
Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data
Gina Bloom is a Professor of English at the University of California, Davis, with affiliations in the PhD programs in Education and Performance Studies. Her research spans Shakespeare, early modern drama, gender theory, and digital humanities, focusing on games, performance, and educational technologies. PhD, MA, and Certificate in Women's Studies from the University of Michigan BA from the University of Pennsylvania Her work includes the award-winning digital game Play the Knave and a decolonial pedagogy curriculum for teaching Shakespeare. She collaborates with UC Davis’s ModLab and DataLab, emphasizing social justice and immersive learning. Awards include Best AR/VR Game (2022) and Shakespeare Publics Award (2025). Her publications blend game studies, theater history, and feminist theory, with recent articles addressing decolonial education and digital embodiment. Winner, Shakespeare Publics Award (2025) Finalist, GEE! Learning Game Award (2023) Winner, Best AR/VR Game Award (2022)
Giacomo Chiesa is a Full Professor at the Department of Architecture and Design (DAD) at Politecnico di Torino. He is a member of the Interdepartmental Center Ec-L - Energy Center Lab. His research focuses on Architectural Technology , Bioclimatic Design , Building Performance , and Urban Climate . Research Interests : Building Simulation, Passive Cooling, Smart Buildings, Digital Twin, Climate Change Adaptation Recent publications analyze urban weather datasets for energy simulations, shading control thresholds , and ventilation strategies in educational buildings. His work covers energy renovation roadmaps , thermal comfort , and climate-resilient building systems . Teaching : PhD courses in Human-Centric Methodologies and MSc courses in ICT in Building Design Research Leadership : Scientific Director for projects like Urban Generation and Prelude , EU-funded initiatives
Doug Bowman is the Frank J. Maher Professor in the Department of Computer Science at Virginia Tech and Director of the Center for Human-Computer Interaction. His work focuses on advancing virtual reality (VR), augmented reality (AR), and 3D user interfaces, with a strong emphasis on human-computer interaction and immersive environments. Education: Ph.D., Computer Science, Georgia Institute of Technology (1999) M.S., Computer Science, Georgia Institute of Technology (1997) B.S., Mathematics and Computer Science, Emory University (1994) Research Interests: Bowman explores the design and evaluation of immersive technologies, including VR/AR interfaces, 3D interaction techniques, and the application of these technologies in fields like healthcare, education, and collaborative work. His work often addresses challenges in spatial awareness, gaze-driven systems, and context-aware interfaces. Recent publications highlight trends in collaborative AR/VR systems, glanceable interfaces, and adaptive techniques for immersive analytics. His research emphasizes real-world applications, such as medical training through AR and improving productivity in virtual workspaces. Lab Affiliation: Director of Virginia Tech’s Center for Human-Computer Interaction, which focuses on interdisciplinary research in interactive technologies.
Kimberly Harry is an Assistant Professor at the School of Systems Science and Industrial Engineering, Binghamton University, State University of New York. She specializes in healthcare systems engineering, focusing on continuous improvement, quality engineering, and healthcare equity. Her research emphasizes critical success factors for Kaizen events in hospitals, leveraging process mining and empirical surveys. She leads the Systems Performance Excellence and Equity Lab (SPEEL), exploring data-driven healthcare optimization strategies. Education: PhD and MS in Industrial and Systems Engineering – Virginia Tech BS in Industrial Engineering – California Polytechnic State University, San Luis Obispo Research Focus: Her work integrates healthcare systems engineering with performance measurement, aiming to enhance equity through structured improvement methodologies. Key themes include Kaizen event efficacy, process mining applications, and interdisciplinary collaboration in healthcare settings. Key Contributions: Over 15 peer-reviewed articles since 2020, focusing on Kaizen event analysis, critical success factors, and healthcare system optimization. Recent work (2023–2025) emphasizes meta-synthesis evaluation and expert-driven frameworks for continuous improvement. Recipient of ASEM Merl Baker Best Student Paper Award (2020, 2022) IISE SEMS Best Student Paper Award (2021) Lab/Teams: Directs the Systems Performance Excellence and Equity Lab (SPEEL), which develops innovative tools for healthcare process improvement and equity assessment.
Geoffrey Nelissen is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology. He holds additional roles as a Research Scientist and Investigador Auxiliar at INESC TEC (Portugal), contributing to interdisciplinary research in real-time systems. His work focuses on schedulability analysis, parallel task execution, and real-time communication protocols, with applications in embedded systems and multicore architectures. Research Interests: Real-Time Scheduling Response Time Analysis Multi-core and Parallel Systems Time-Sensitive Networking (TSN) Formal Verification Recent work emphasizes schedule abstraction frameworks, memory contention analysis, and deterministic communication protocols. His research has received recognition through multiple best paper awards including ICESS 2021 and RTAS 2022. He actively contributes to conferences like RTSS and ECRTS while teaching courses on Real-Time Systems and Operating Systems. Collaborations span European institutions with focus on embedded systems, autonomous driving, and safety-critical applications. Current projects explore holistic approaches to WCRT analysis and resilient real-time communication architectures.
Marcelo M. Wanderley is a Professor and Director of the Centre for Interdisciplinary Research in Music Media and Technology (CIRMMT) at McGill University's Schulich School of Music. His academic roles include Area Coordinator for Music Technology and membership on the Executive Committee. He holds a PhD in acoustics, signal processing, and computer science from Université Pierre et Marie Curie (Paris VI). Wanderley's research focuses on novel interfaces for music performance, digital musical instruments (DMIs), and human-computer interaction. He has authored influential works such as New Digital Musical Instruments: Control and Interaction Beyond the Keyboard (2006) and pioneered research in gestural control of music. His work integrates engineering, computer science, and musicology to create innovative performance tools, including the T-Stick and Karlax instruments. He has held visiting professorships at Université de Bretagne Sud, Universidade Federal de Minas Gerais (Brazil), and the University of Mons (Belgium), where he was awarded prestigious chairs. Wanderley's awards include the Inria International Chair (2016–2020) and the Distinguished Visitor Award from the University of Auckland. His research has been widely cited in the International Conference on New Interfaces for Musical Expression (NIME), and he actively contributes to editorial boards (e.g., Computer Music Journal ) and academic leadership roles. Wanderley's lab, the Input Devices and Music Interaction Lab (IDMIL), develops open-source frameworks like Puara and Probatio for DMI design and mapping. Key research areas include haptic feedback systems, motion capture of musical performances, and accessibility in music technology. He emphasizes interdisciplinary collaboration, bridging engineering, art, and cognitive science to advance musical expression and performance practices.
Dr. Yongjie Jessica Zhang is a Professor at Carnegie Mellon University, holding appointments in both the Department of Mechanical Engineering and the Department of Biomedical Engineering . She received her B.S. and M.S. in Engineering Mechanics from Tsinghua University, followed by an M.S. in Aerospace Engineering and a Ph.D. in Computational Engineering and Sciences from the University of Texas at Austin. After a postdoctoral fellowship at ICES, she joined CMU in 2007, advancing from assistant to full professor by 2016. Research Interests : Image-based geometric modeling, mesh generation, finite element analysis (FEA), isogeometric analysis, and applications in computational biomedicine, materials science, and computer-assisted surgery. Leadership Roles : Chair of Solid Modeling Association (2019-2020), USACM Executive Committee Member-at-Large (2017-2021), and ELATE Fellow (2017-2018). Her work addresses the critical challenge of automating high-fidelity geometric modeling and mesh generation for complex domains (e.g., human anatomy), which traditionally consumes ~80% of FEA time. Her group develops AI-driven methods for multiscale modeling (molecular to organ), with applications in neuroscience , biomechanics , and 4D printing . Notable awards include the Presidential Early Career Award (PECASE) , NSF CAREER Award , and ASME Van C. Mow Medal (2025) . Dr. Zhang’s publications span over 170 peer-reviewed articles, focusing on truncated hierarchical B-splines , polycube meshing , and neurite transport modeling . She has advised more than 40 students, including PhD candidates and postdoctoral fellows. Her editorial roles include Associate Editor of Computer Aided Geometric Design and editorial board memberships in Computer-Aided Design and Engineering with Computers .
Dr. Lijun Chang is an Associate Professor in the School of Computer Science at the University of Sydney. He holds an ARC Future Fellowship (2019–2022) and an ARC DECRA Fellowship (2015–2017). Previously, he was at the University of New South Wales. His research focuses on graph analytics, mining, algorithms, and network science. He teaches courses like INFO5011 (Competitive Programming), COMP5313 (Large Scale Networks), and COMP9120 (Database Management Systems), and coaches the USYD Programming Competition Teams. Education: B.Eng. in Computer Science & Technology from Renmin University of China; PhD from the Chinese University of Hong Kong. Research highlights include scalable graph processing systems (e.g., ScaleG), densest subgraph detection, and graph similarity search. He leads projects funded by ARC grants such as 'Advanced Search of Cohesive Subgraphs in Big Graphs' (2018) and 'Directionality-Aware Cohesive Subgraph Search' (2022). His work emphasizes efficient algorithms for large-scale networks and graph databases. Awards : ARC Future Fellow, ARC DECRA Fellow Students : Yu KONG, Rashmika MATHTHAKA GAMAGE, Mouyi XU Labs/Teams : Focuses on graph algorithms and systems research, contributing to open-source tools and large-scale network analysis.
David Konisky serves as Associate Dean for Research and Lynton K. Caldwell Professor at Indiana University's Paul H. O'Neill School of Public and Environmental Affairs. His expertise spans environmental/energy justice, regulatory policy, and public opinion on climate issues, with research appearing in top journals including Nature Energy and PNAS. Education: Ph.D. in Political Science, Massachusetts Institute of Technology, 2006 M.E.M. and M.A., Yale University, 1998 A.B. in History and Environmental Studies, Washington University in St. Louis, 1995 Research Focus: Konisky pioneers energy justice frameworks examining how environmental policies impact marginalized communities. His work connects federalism with regulatory compliance , analyzes public attitudes on energy transitions, and measures equity dimensions in climate solutions through interdisciplinary methods spanning political science and environmental health. Publication Trends: Recent work (2020-2025) reveals persistent energy insecurity disparities during crises like the pandemic, quantifies health impacts from excess emissions , and exposes environmental racism in regulatory enforcement. His research increasingly integrates extreme heat vulnerability with energy policy, highlighting utility disconnection risks for vulnerable populations. Scientific Recognition: Elected to National Academy of Public Administration (2023) Lynton K. Caldwell Professorship appointment (2022) World Citizen Prize in Environmental Performance (2022) Don K. Price Book Award for Failed Promises (2015) Editor-in-Chief of Environmental Politics (2024) Grants and Leadership: Konisky directs the Energy Justice Lab with University of Pennsylvania, securing major funding from NSF, EPA, DOE, and Sloan Foundation. His seven books include Power Lines: The Human Costs of American Energy in Transition (2024) and foundational work on environmental justice policy. Research Infrastructure: As co-director of the Energy Justice Lab, he leads interdisciplinary teams developing metrics for equitable energy transitions, with current projects tracking utility disconnections during extreme heat events and solar adoption barriers for low-income households.
Dr. Brian Y. Chen is an Associate Professor and Doctoral Program Director in the Department of Computer Science & Engineering at Lehigh University. His research focuses on bioinformatics, structural biology, and machine learning applications in computational biology. He holds a Ph.D. in Computer Science from Rice University and B.A. degrees in Mathematics and Computer Science from Rutgers University. Dr. Chen's work emphasizes developing algorithms to analyze protein structures, protein-protein interactions, and ligand binding mechanisms. He has contributed to tools like DeepVASP-S and MechPPI, which explain molecular interactions and predict binding specificity. His recent projects include Alzheimer’s disease diagnosis using multimodal data and containerization frameworks for bioinformatics software. He previously served as a postdoctoral researcher in Barry Honig's Lab at Columbia University, where he contributed to the Center for Computational Biology and Bioinformatics. His research spans structural bioinformatics, computational methods for protein function prediction, and interdisciplinary applications in medicine and materials science. Key achievements include a nomination for Outstanding Mentorship (2017) and collaborative projects funded by the Army Research Lab and Lehigh University. His lab explores cutting-edge AI techniques for biomedical problems, including interpretable machine learning models and scalable bioinformatics pipelines.
Prof. Karsten Urban is a Full Professor of Numerical Mathematics at the University of Ulm, leading the Institute for Numerical Mathematics. He holds roles such as Dean of Studies in Computational Science and Engineering (CSE) and Deputy Spokesman for the Research Association for Scientific Computing in Baden-Württemberg. He is an active member of prestigious societies including the Deutsche Mathematikervereinigung (DMV) and SIAM. His academic journey includes a PhD from RWTH Aachen (1995), Habilitation (2001), and a full professorship at Ulm since 2005. Research focuses on numerical methods for PDEs, reduced basis techniques, multiscale simulations in fluid mechanics, biomechanics, quantum sciences, and financial mathematics. He has pioneered wavelet-based methods and collaborated with industries on ship propulsion and energy trading models. His work integrates mathematical rigor with real-world applications, emphasizing model reduction and computational efficiency. Editorial Roles: Managing Editor of Advances in Computational Mathematics , Editor of SN Partial Differential Equations and Applications . Awards: Teaching award of Baden-Württemberg (2005), Science-Economy Cooperation Awards (2004, 2008). Administrative Roles: Member of the University Council and ASIIN expert committee. Supervises doctoral students in numerical analysis, quantum simulations, and biomechanics. Active in interdisciplinary projects, including quantum systems (IQST) and fracture healing modeling in collaboration with biomechanics experts. His contributions bridge academia and industry, driving innovation in computational methods.
Fahim Khan is an Assistant Professor in the Department of Computer Science and Software Engineering at California Polytechnic State University’s College of Engineering. He specializes in computer graphics, data visualization, computer vision, and machine learning, with a focus on applying these technologies to education, environmental monitoring, and public safety. His research emphasizes making complex data accessible through advanced tools, bridging the gap between raw data and actionable insights. He is deeply committed to inclusive education and fostering interdisciplinary collaboration. His work often integrates citizen science initiatives, empowering communities through mobile applications and machine learning. Notable projects include real-time rip current detection systems and platforms for high school students to engage in research. Khan advocates for equity in technology, designing inclusive learning environments and promoting diversity in STEM. He actively supports the university’s Learn by Doing philosophy, blending practical education with theoretical rigor. Professionally, he contributes to coastal observation networks and autonomous vehicle datasets while maintaining a balance through outdoor activities like exploring Pismo Beach. His research trends reflect a strong focus on mobile computing, environmental applications, and education technology, with recent efforts emphasizing citizen science and data-driven solutions. While no formal grants or advising records are detailed, his projects implicitly involve collaborative efforts. He is affiliated with labs focused on environmental monitoring and mobile technology development, though specific lab names are not mentioned.
Dr. Kidambi Sreenivas is an Associate Professor in Mechanical Engineering at the University of Tennessee at Chattanooga (UTC), affiliated with the College of Engineering and Computer Science. He holds a PhD in Mechanical Engineering and specializes in computational fluid dynamics (CFD), with a focus on unstructured multi-physics flow solvers and applications in aerospace, environmental systems, and biomedical engineering. His research bridges academia and industry, collaborating with NASA, the U.S. Navy, Department of Energy, and private companies. Dr. Sreenivas' research interests include rotating machinery simulations, pre-conditioners for non-ideal fluids, and real-world applications such as submarine hydrodynamics, wind farm optimization, aerodynamic efficiency of vehicles, and contaminant dispersal modeling. He has pioneered methods for simulating complex geometries and physics, including high-fidelity simulations of hypersonic vehicles, weapons bay cavities, and shock-wave interactions. Recent work emphasizes advanced CFD methodologies for high-speed flows, thermal effects on turbulence, and aerothermal characteristics of hypersonic test articles. His collaborations have led to practical solutions for drag reduction on Class 8 trucks and improved accuracy in wind turbine modeling. Dr. Sreenivas also contributes to educational initiatives, such as developing PIV systems for undergraduate fluid mechanics labs. His advising and grants reflect partnerships with federal agencies and private sectors, focusing on projects like microplastic sampling devices for stormwater management. These projects highlight his interdisciplinary approach to solving real-world engineering challenges through cutting-edge computational methods.
