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Constant HakView profile

Assistant Professor

• Room Acoustics
• Hall Acoustics
• Acoustic Measurement Techniques
• +3 more

Constant Hak is an Assistant Professor with the Building Acoustics research group at the Department of Built Environment, Eindhoven University of Technology (TU/e). His work focuses on reducing adverse health effects caused by human-induced noise while promoting positively perceived sound environments through computational and experimental acoustic methods. Dr. Hak specializes in room and hall acoustics, developing advanced acoustic measurement techniques based on impulse responses. His research includes analyzing how orchestra members influence stage acoustic parameters across multiple concert hall stages and orchestra pits, as well as creating methods for accurate impulse response measurements in large open-air theaters. Software and measuring equipment developed by Hak is used worldwide for research and engineering applications. His recent publications demonstrate expertise spanning building acoustics, plasma physics, and indoor environmental quality measurement. The research shows consistent focus on measurement techniques, with applications in architectural acoustics, concert hall design, and educational tools for environmental quality assessment. Dr. Hak teaches multiple courses including Architectural Acoustics, The Science of Sound, Techniques in Architectural Acoustics, and various Master's projects related to Building Physics and Services. His educational work includes developing the SvS (Senses versus Sensors) device, which helps students understand indoor environmental quality through hands-on measurement of temperature, humidity, light, and sound.

Andrea ArcuriView profile

Professor

• Software Testing
• Software Engineering
• Cloud Computing
• +6 more

Andrea Arcuri is a Professor at the School of Economics, Innovation and Technology within Kristiania University of Applied Sciences . His research focuses on Software Testing , Software Engineering , and Cloud Computing , with a particular emphasis on automated testing techniques for web APIs. Specialized in RESTful, GraphQL, and RPC API fuzzing Developer of the open-source EvoMaster testing tool Pioneer in integrating evolutionary algorithms and symbolic execution for test generation Active in bridging academic research with industrial software testing practices His recent publications show a strong focus on Search-Based Software Testing (SBST) , Automated Test Generation , and Industrial Adoption of Testing Technologies . He has contributed extensively to improving testability through mock generation and database handling in API testing. While no formal scientific awards are listed in the public records analyzed, his work has been consistently published in top-tier software engineering venues since 2013. The articles demonstrate increasing sophistication in fuzzing techniques, with recent extensions to handle complex dependencies like MongoDB and SQL databases.

Li YangView profile

Assistant Professor

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

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

Assela PathiranaView profile

Professor

• Water Infrastructure Asset Management
• Climate Resilience of Small Island Developing States (SIDS)
• Hydrological Modeling
• +5 more

Dr. Assela Pathirana is a Professor at the IHE Delft Institute for Water Education, specializing in water infrastructure asset management (WIAM), climate resilience of Small Island Developing States (SIDS), and sustainable urban water systems. His work bridges academia, policy, and practice, focusing on digitalization, data-driven decision-making, and nature-based solutions. Key roles include Chief Technical Advisor for the Maldives’ water systems and leadership of a MOOC on SIDS climate adaptation. He holds a BSc (First Class Honours) from the University of Peradeniya and advanced degrees from the University of Tokyo, specializing in hydrology and water resources engineering. Education: Bachelor of Science in Civil Engineering (First Class Honours), University of Peradeniya, Sri Lanka Master’s and Doctoral Degrees in Civil Engineering (Hydrology and Water Resources), University of Tokyo, Japan Research Interests: Dr. Pathirana’s work emphasizes climate resilience, SIDS adaptation, urban flood risk management, and sustainable infrastructure. He develops decision-support tools for flood forecasting, evaluates land-use changes in Jakarta, and promotes equity in water rationing systems. His interdisciplinary approach integrates hydrological modeling, open-source software development, and policy analysis. Advising & Capacity Building: He leads training-of-trainers programs and capacity-building initiatives, enhancing postgraduate education in technical disciplines. His efforts focus on didactics and pedagogy, ensuring graduates gain both theoretical knowledge and practical expertise. Key Projects: Developed the WIAM curriculum at IHE Delft MOOC on SIDS climate adaptation and water security Consultancy for the Maldives’ Ministry of Environment and UNDP Labs & Collaborations: Engages in cross-disciplinary teams addressing urban water challenges, including sponge cities in China and flexible adaptation planning in Melbourne and Pune. His work with UNESCO-ICHARM and UNU underscores global water security and disaster risk reduction.

Geoff HollingerView profile

Professor

• Robotics
• Artificial Intelligence
• Autonomous Systems
• +7 more

Geoff Hollinger is a Professor in the Department of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University, and a Ron and Judy Adams Faculty Scholar. His research focuses on robotic decision-making, planning, and coordination for autonomous systems, particularly in underwater and multi-robot environments. He leads the Robotic Decision-Making Laboratory and has expertise in mission planning, control systems, and marine robotics. Dr. Hollinger holds a PhD in Robotics from Carnegie Mellon University (2010), an MS in Robotics (2007), and a BS in General Engineering and BA in Philosophy from Swarthmore College (2005). His work spans theoretical advancements and practical applications, including underwater docking systems, autonomous exploration, and soft robotics for hazardous environments. Research Interests: Autonomous underwater vehicle (AUV) systems and docking Multi-robot coordination and task assignment Probabilistic planning and decision-making Behavior trees and formal grammars for task planning Underwater manipulation and grasping Energy-efficient trajectory planning Key Achievements: Recipient of the 2017 ONR Young Investigator Award 2017 Celebrate Excellence Awards and Engelbrecht Young Faculty Award Developed frameworks like Angler for intervention tasks and Wave for underwater emulation Labs/Teams: Robotic Decision-Making Laboratory, Collaborative Robotics and Intelligent Systems Institute (CRIS).

Matti TedreView profile

Professor

• Computer Science Education
• ICT4D
• Social Studies of Computer Science
• +5 more

Matti Tedre is a Professor at the School of Computing, Faculty of Science, Forestry and Technology, University of Eastern Finland. His research focuses on computer science education, ICT4D, social studies of computer science, and the history and philosophy of computer science. He leads the Technologies for Learning and Development research group and is involved in the Generation AI project (2022–2028), exploring AI education for security mindset development. His work bridges theory and practice, emphasizing educational technology, AI literacy, and participatory design. Recent projects include developing low-cost AI kits for novice learners and co-designing ML-driven apps with children. He collaborates globally on topics like K-12 computing education, data agency, and ethical AI integration in classrooms. Key contributions include studies on scaffolding in ML education, children’s understanding of algorithmic biases, and the role of generative AI in creative learning. His research also addresses challenges in Tanzanian ICT adoption, including financial management systems for informal groups and timetabling software for higher education institutions. Tedre’s interdisciplinary approach spans computer science, education, and sociology, with a focus on democratizing AI access and fostering critical digital literacy among youth and educators.

Anuj PathaniaView profile

Assistant Professor

• Low Power Design
• Sustainable Systems
• Electronic Design Automation
• +4 more

Anuj Pathania serves as an Assistant Professor in the Parallel Computing Systems (PCS) group within the Informatics Institute at the University of Amsterdam's Faculty of Science. His research pioneers sustainable computing systems operating under severe power, thermal, and reliability constraints, with significant contributions to energy-efficient hardware design and embedded systems. Education: PhD in Computer Science (2018), Karlsruhe Institute of Technology MSc in Computer Science (2012), National University of Singapore B.Tech in Computer Science (2009), Maharaja Agrasen Institute of Technology Pathania's research centers on low-power design and sustainable systems for constrained environments, with particular expertise in thermal management of 3D-stacked architectures and energy-efficient machine learning inference . His work bridges electronic design automation with real-world reliability challenges, developing novel power budgeting techniques like T-TSP that incorporate transient temperature effects ignored by conventional methods. Current projects include EU-funded initiatives on energy labeling for digital services, addressing ecological impacts through technological, behavioral, and legal frameworks. His publication trajectory reveals a strategic evolution toward zero-waste computing , with recent work (2023-2025) focusing on hardware-software co-design for edge AI, energy modeling across computing continua, and parameter-efficient neural adaptation. Key themes include thermal-aware scheduling for S-NUCA many-cores, cooperative processor utilization in heterogeneous systems, and sustainability metrics for digital services. Scientific Recognition: Best Paper Award Nomination at IEEE Computer Society Annual Symposium on VLSI 2023 for 3D-TTP power budgeting technique Pathania actively mentors 4 PhD students (Ehsan Aghapour, Saeedeh Baneshi, Sudam Wasala, Yixian Shen) and has successfully supervised 5 Master's theses (including Cum Laude defenses by Joris op ten Berg and Jurre Wolff). His research is supported by major grants including Energy Labels for Ecologically Sustainable Digital Services (2023-2024) and Towards Zero-Waste Computing (2021-2025), developing simulation frameworks like HotSniper and CoMeT for thermal analysis. The PCS group maintains strong industry collaborations with ARM and NVIDIA, particularly through tools like ARM-CO-UP for heterogeneous processor utilization.

Kai R. LarsenView profile

Professor

• Information Systems
• Semantic Theory of Survey Response
• Automated Machine Learning
• +3 more

Kai R. Larsen is a Professor at the Organizational Leadership and Information Analytics division within the Leeds School of Business , University of Colorado Boulder . He holds courtesy faculty appointments in the Department of Information Science at the College of Media, Communication and Information , serves as a Research Advisor to Gallup , and is a Fellow of the Institute of Behavioral Science . Education: Ph.D., Information Science, University at Albany, SUNY Candidatus Magisterii (Software Engineering), The National College for Teachers of Commerce, Norway Adjunkt (Education), The National College for Teachers of Commerce, Norway Diplomkandidat, NHI College of Computer Science, Norway His research focuses on Information Systems , particularly addressing the Jingle Fallacy and developing the Semantic Theory of Survey Response . He leads the Federally Supported Human Behavior Project , creating transdisciplinary frameworks using Large Language Models and Natural Language Processing to predict human behaviors across technology utilization, investor decisions, voter behaviors, and cancer prevention. His scientific awards include INFORMS ISS Design Science Award (2019) Best Prototype Award at WITS (2019) Herbert A. Simon Award (2020) David B. Balkin Innovative Teaching Award (2023) Kolb Teaching Award (2022) National Institutes of Health $355,000 Grant (2022-2023) Larsen's grant funding and mentorship achievements include NIH grant for stress ontology research Outstanding Faculty Mentor Award (2021-2022) Technology Challenge Award (2016) He also maintains the Theories Used in IS Wiki and developed the TheoryOn award-winning ontology-based search engine used by thousands.

Emmanuel LetierView profile

Associate Professor

• Software Engineering
• Requirements Engineering
• Software Architecture
• +8 more

Dr. Emmanuel Letier is an Associate Professor in Software Engineering at University College London (UCL), specializing in requirements engineering and software architecture. His research focuses on stakeholder goal analysis, formal reasoning techniques, and uncertainty management in software development. University College London, Department of Computer Science Research areas: Requirements Engineering, Software Architecture, Formal Methods, Uncertainty Analysis His work explores how to bridge stakeholder goals with software requirements using natural language, formal logic, and mathematical models. Key contributions include model checking, synthesis tools, and Bayesian analysis applications for managing technical debt and software evolution. Recent publications span AI-based systems requirements, app review mining for requirements elicitation, and uncertainty handling in self-adaptive systems. Notable awards include Best Paper Award (ACM SIGSOFT 2004) Best Paper Award (IEE 2003) Distinguished Paper Award (RE'11)

Om P. DamaniView profile

Professor

• Technology for Development
• System Dynamics
• Modeling and Simulation
• +7 more

Om P. Damani is a Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. He serves as Faculty In-Charge of the Sustainable Development unit of the Center for Policy Studies and is also associated with the Centre for Technology Alternatives for Rural Areas (CTARA). His work bridges computer science with social development challenges, focusing on practical applications for rural communities. Dr. Damani's research interests span Technology for Development of the bottom 80%, System Dynamics: Modeling and Simulation for Social Development, System Architecture, and Data Science. His work demonstrates how computational approaches can address complex development challenges through projects like GramDrishti (for detecting rural infrastructure in satellite images), JalTantra (for optimizing water distribution networks), and FAI (Farm Assessment Index for holistic farming practice evaluation). His publications reveal a consistent focus on applying computer science to solve real-world problems in water management, agricultural systems, and rural infrastructure. His research has been recognized with significant awards including the IIT Bombay Industrial Impact Award 2010, IIT Bombay Impactful Research Award 2019, and Best Poster Award at Agriculture Science Congress 2017. Dr. Damani has successfully translated theoretical research into practical tools that address development challenges, particularly in water resource management and agricultural systems. As an educator, he has mentored numerous PhD students including Chintan Tundia, Shreenivas Kunte, Nikhil Hooda, Sivamuthu Prakash Murugan, Dipak L. Chaudhari, Prateek Kapadia, and Manoj K. Chinnakotla. His teaching portfolio includes courses on System Dynamics: Modeling and Simulation for Development (CS 752), Program Derivation (CS 420), and ICT for Development. Dr. Damani's educational background includes a Ph.D. in Computer Sciences from the University of Texas at Austin (1994-1999), B.Tech. in Computer Science and Engineering from IIT Kanpur (1990-1994), and prior professional experience at IBM T J Watson Research Lab and Akamai Technologies.

• Geophysics
• Remote Sensing
• Computer Vision
• +2 more

Scott Staniewicz is a researcher at the University of Texas at Austin in the Department of Aerospace Engineering and Engineering Mechanics. His work focuses on geophysical applications of computer vision and remote sensing, particularly using Interferometric Synthetic Aperture Radar (InSAR) to detect surface deformation and tropospheric noise features. Academic Affiliation: University of Texas at Austin Research Focus: Surface deformation analysis, InSAR data processing, tropospheric noise mitigation Email: scott.stanie@utexas.edu Staniewicz's research employs computer vision techniques like Laplacian of Gaussian (LoG) filtering to identify spatially coherent deformation features (e.g., subsidence/uplift in oil-producing regions). His methods integrate noise spectrum estimation from real data and simulations to distinguish true deformation signals from atmospheric artifacts. Recent work includes software development for automated InSAR analysis and large-scale studies of anthropogenic deformation in the Permian Basin. He has contributed to open-source tools such as Blobsar (2025a) and Troposim (2025b) for deformation detection, and collaborated on studies analyzing seismic sequences (Skoumal et al., 2020), tropospheric delay corrections (Li et al., 2019; Yang et al., 2024), and statewide seismic networks (Savvaidis et al., 2019). His publications demonstrate expertise in combining computer vision with geophysical data analysis.

• Quantum Computing
• Quantum Information Science
• Quantum Simulation
• +3 more

Martin Ringbauer is an Associate Professor at the Department of Experimental Physics , University of Innsbruck . His research focuses on advancing quantum computing and quantum simulation through innovative applications of trapped ion qudits and high-dimensional quantum systems . Affiliation: Department of Experimental Physics, University of Innsbruck Research Areas: Lattice gauge theories, symmetry-protected topological phases, quantum verification protocols, and fidelity estimation Key Contributions: Development of qudit-based quantum processors for simulating complex physics, experimental demonstrations of quantum error correction and joint measurements His recent publications highlight advancements in quantum simulation (lattice gauge theories, Haldane phases), quantum verification (fidelity estimation, classical validation), and qudit engineering (mixed-dimensional frameworks, entanglement optimization). These works leverage trapped ion technology as a platform for scalable and precise quantum operations.

Mila N. KoevaView profile

Associate Professor

• Geospatial Technologies
• Digital Twinning
• 3D Urban Modeling
• +6 more

Mila N. Koeva is a Vice Dean Research and senior Associate Professor at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC), Department of Urban and Regional Planning and Geo-Information Management. Her research focuses on 3D modeling and Digital Twins for land management and urban planning, integrating geospatial technologies, UAV data, and AI/ML methods. PhD in architectural photogrammetry MSc in Engineering (Geodesy) Research Themes: Digital Twinning for urban ecosystems AI-driven cadastral boundary extraction 3D modeling with LiDAR and satellite data Global partnerships in Rwanda, Kenya, and Ethiopia Interoperability standards for local digital twins Scientific Contributions: Geospatial World Innovation Award 2021 Copernicus Masters Competition (3rd place 2016) Editorial roles in Photogrammetric Records and MDPI journals Keynote speaker at 3D GeoInfo, GI Forum, and FIG events Her educational impact includes developing courses, lecturing, and supervising students whose work has received top awards in The Netherlands and international competitions.

• Superconducting Logic
• Bio-based Architectures
• Novel Computing Mediums
• +6 more

Dr. Jennifer Volk is an Assistant Professor at the College of Engineering, University of Wisconsin-Madison, specializing in Electrical & Computer Engineering. Her research focuses on leveraging novel technologies like superconductor electronics and photonics to create efficient systems for datacenters, neuromorphic computing, quantum computing, and space/sensing applications. She employs a holistic approach spanning circuit design, materials science, and computer microarchitecture. PhD (2024), University of California, Santa Barbara BS (2016), University of California, Santa Cruz Her research interests include superconducting logic , bio-based architectures , and novel computing mediums , emphasizing co-optimization of logic and circuit blocks. Her work develops design abstractions to simplify adoption of unconventional technologies. Dr. Volk's publications demonstrate expertise in superconducting circuit design, radiation-hardened CMOS for particle physics, and photonic materials. She has received numerous awards including the 2025 John D. Wiley Assistant Professorship and IEEE fellowships in applied superconductivity. 2025 John D. Wiley Assistant Professorship 2024 UC Santa Barbara President's Dissertation Year Fellowship 2023 IEEE CSC Graduate Study Fellowship in Applied Superconductivity 2022 IEEE Micro Top Picks Honorable Mention 2021 IEEE Micro Top Picks She teaches E C E 340 - Electronic Circuits I (Spring 2025). Her work bridges materials science, circuit design, and system architecture to enable next-generation computing platforms.

• CAD tools
• Digital architectures
• Emerging technologies
• +9 more

Giovanna Turvani is an Associate Professor at the Department of Electronics and Telecommunications (DET) at Politecnico di Torino, with affiliations in both the College of Electronic, Telecommunications and Physics Engineering and the College of Computer, Film, and Mechatronics Engineering. Scientific Branch: IINF-01/A - Electronics ERC Sectors: PE7_4, PE7_11, PE6_1, PE6_14, PE7_3 SDG Goals: Quality Education, Gender Equality, Affordable Energy, Industry Innovation Her research focuses on advanced electronics and quantum technologies, including: Logic-in-memory computing Quantum computing architectures Microwave imaging for medical and agricultural applications CAD tools for emerging nanotechnologies Embedded systems for bee health monitoring IoT solutions for bio-waste valorization Publications show strong expertise in quantum computing, nanocomputing, and microwave imaging, with recent trends emphasizing quantum optimization frameworks, in-memory architectures, and IoT-based agricultural technologies. She supervises PhD students in areas like quantum machine learning algorithms, predictive on-board systems, and quantum hardware design. Collaborations span multiple disciplines, including medical device development and agricultural electronics. Patents include innovations in microwave imaging, racetrack memory logic functions, and in-memory computing devices.