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Thomas HackerView profile

Professor

• Cloud Computing
• High-Performance Computing
• Operating Systems
• +3 more

Thomas Hacker is a Professor in the Department of Computer and Information Technology at Purdue Polytechnic Institute, Purdue University. His research focuses on cloud computing, high-performance computing, operating systems, computer networking, and cyber infrastructure . He holds a Ph.D. and M.S. in Computer Science & Engineering from the University of Michigan, along with dual B.S. degrees in Computer Science and Physics from Oakland University. Education: PhD (Computer Science & Engineering), University of Michigan (2004) MS (Computer Science & Engineering), University of Michigan (1993) BS (Computer Science, Mathematics Minor), Oakland University (1989) BS (Physics), Oakland University (1989) Dr. Hacker's research spans cloud and grid computing, operating systems, and distributed systems , with applications in earthquake engineering data systems and AI-driven infrastructure analysis. His recent work explores extended layer 2 networking for bare-metal provisioning ( 2023 IEEE Cloud Summit ) and machine-supported bridge inspection using artificial intelligence ( Transportation Research Record, 2023 ). Notable scientific contributions include 15+ publications on topics like cyberinfrastructure for earthquake engineering, container-based virtualization, and data-intensive systems. His work has been recognized with awards such as the NSF CAREER Award (2010) and multiple Purdue Seed for Success Awards . Key Scientific Awards: NSF CAREER Award (2010) Purdue Seed for Success Awards (2008-2013) ASEE Information Systems Division Best Paper Award (2012) College of Technology Outstanding Faculty in Discovery Award (2010) He has held leadership roles at Purdue, including Department Head (2018-2021) and Interim Department Head (2011-2016) . His career spans academic positions at Indiana University, University of Michigan, and industry roles at Storage Technology Corporation.

Xing GaoView profile

Assistant Professor

• Cybersecurity
• Cloud Computing
• Mobile Computing
• +4 more

Xing Gao is an Assistant Professor at the University of Delaware, affiliated with the Department of Computer and Information Sciences and jointly with the Department of Electrical and Computer Engineering. His office is located at 316B FinTech Innovation Hub on the STAR Campus. He holds a PhD from the College of William and Mary (2018) and a BS from Beijing Institute of Technology (2011). Research Interests: Cybersecurity in Software Supply Chain, Web 3, High-Performance Computing, Large Language Models, with a focus on Security, Cloud Computing, and Mobile Computing. Education: PhD | 2018 | College of William and Mary BS | 2011 | Beijing Institute of Technology His recent work explores cybersecurity vulnerabilities in cloud gaming services (CCS'22), container registries (USENIX-SEC'22), and software supply chains, with specialized attention to GPU cache attacks (USENIX-SEC'24) and Ethereum smart contracts (WWW'24). His research spans theoretical and applied aspects of system security, including CI/CD pipelines (CCS'24), SDN backdoors (INFOCOM'23), and hardware-level threats (ACSAC'21). Scientific Awards NSF CAREER Award (2024) NSF CRII Award (2020) NDSS Distinguished Poster Award (2016) He serves as Registration Chair for ACM/IEEE Symposium on Edge Computing (2023) and Publicity Co-Chair for IEEE Conference on Communications and Network Security (2022). He is actively involved as TPC Member in multiple top-tier conferences including USENIX Security (2026,2025), CCS (2026,2025,2024), and IEEE DSN (2024). He has also reviewed for journals like IEEE Transactions on Dependable and Secure Computing. Labs & Teams X-Lab at the University of Delaware, a research group focused on cybersecurity in emerging technologies.

Takako FujiokaView profile

Associate Professor

• Auditory Perception
• Neural Oscillations
• Auditory-Motor Coupling
• +5 more

Takako Fujioka is an Associate Professor of Music at Stanford University, affiliated with the Center for Computer Research in Music and Acoustics (CCRMA). Her research focuses on the neural mechanisms underlying auditory perception, auditory-motor coupling, and music-supported therapy for neurorehabilitation. She holds a Ph.D. in Physiology from the Graduate University for Advanced Studies, Japan, and M.Sc./B.Eng. degrees in Electrical Engineering from Waseda University. Her work combines neurophysiological techniques such as MEG and EEG to study brain plasticity in development, aging, and stroke recovery. Notable contributions include investigating how music influences motor and cognitive recovery in stroke patients, as well as exploring the neural basis of musical perception through rhythmic synchronization and pitch discrimination studies. Supported by awards from the Canadian Institutes of Health Research during her postdoctoral work at the Rotman Research Institute, her research bridges clinical neuroscience and music cognition. Dr. Fujioka’s expertise spans auditory neuroscience, neurorehabilitation, and technology-assisted music therapy. She has pioneered studies on tactile mapping for cochlear implant users and networked music performance systems, emphasizing cross-modal perception and human-technology interaction. Her findings contribute to both theoretical understanding of auditory processing and practical applications in medical and educational settings. Awards: Canadian Institutes of Health Research Awards (postdoctoral phase) Labs/Teams: CCRMA, Stanford Music Perception Laboratory, Rotman Research Institute collaborations Key Themes: Neuroplasticity, Music-Mediated Rehabilitation, Auditory-Motor Integration, Multisensory Processing Her recent work examines aging-related changes in binaural hearing and the role of beta/gamma oscillations in rhythmic processing. She advocates for translational research that connects neural mechanisms with real-world therapeutic interventions.

Eugene O'BrienView profile

Professor

• Structural Engineering
• Bridge Safety Assessment
• Traffic Load Modeling
• +2 more

Professor Eugene O'Brien serves as Professor of Civil Engineering within the School of Civil Engineering at University College Dublin's College of Engineering and Architecture. His research focuses on critical structural assessment methodologies for long-span bridges, with particular expertise in traffic load modeling and bridge safety evaluation. His research interests center on structural engineering challenges related to bridge infrastructure, specifically traffic load assessment for long-span bridges , structural health monitoring systems , and sustainable infrastructure management . Professor O'Brien pioneered camera-based monitoring techniques to overcome limitations of traditional Weigh-in-Motion sensors during congested traffic conditions, enabling more accurate safety assessments of aging bridge infrastructure. His work addresses the critical gap in quantifying traffic loading on bridges with spans up to 2 kilometers, where conventional methods fail during stop-and-go traffic scenarios. Analysis of his 15 most recent publications reveals a consistent research trajectory focused on probabilistic modeling of traffic loads, with increasing sophistication in handling extreme events and long-term infrastructure performance. His work spans fundamental statistical methods for load effect prediction, practical applications in real-world bridge assessments, and environmental considerations regarding infrastructure carbon footprints. The research demonstrates strong methodological evolution from basic traffic modeling to comprehensive lifetime assessment frameworks incorporating sustainability metrics. As co-founder and director of Roughan O'Donovan's subsidiary Innovative Solutions (ROD-IS), Professor O'Brien has translated research into practice through significant projects including the Malahide Railway Viaduct assessment (2009), EU-funded bridge lifespan simulation tools (2011), vibration reduction systems for bridge cables, and structural assessments for major international projects including the Ting Kau Bridge in Hong Kong, the Forth Road Bridge in Scotland, and the Chacao Channel Bridge in Chile. His consultancy work demonstrates direct application of academic research to critical infrastructure challenges worldwide. Professor O'Brien's research group operates at the intersection of structural engineering and sustainable infrastructure management, with particular emphasis on extending bridge service life through accurate safety assessment. Their work on the Chacao Channel Bridge demonstrates practical implementation of traffic monitoring systems using toll data to manage truck loads, while their environmental impact analysis shows how accurate safety assessments reduce unnecessary bridge replacements, thereby lowering the carbon footprint of transportation infrastructure through extended service life of carbon-intensive materials like concrete and steel.

Ben FischView profile

Assistant Professor

• Cryptography
• Distributed Systems
• Blockchain Technology
• +5 more

Ben Fisch is an Assistant Professor of Computer Science at Yale University's School of Engineering & Applied Science. He is also the co-founder of Espresso Systems, a company focused on blockchain infrastructure. His research focuses on privacy and verifiability in decentralized systems like Bitcoin and Ethereum, with applications in digital finance and healthcare. Dr. Fisch received his B.A. from the University of Pennsylvania and completed his Ph.D. at Stanford University, where he worked with Dan Boneh in the applied cryptography research group. His educational background provided the foundation for his work at the intersection of cryptography, distributed systems, and economics. His research centers on leveraging cryptographic tools such as succinct non-interactive zero-knowledge proofs (zk-SNARKs), private information retrieval, and homomorphic encryption to address challenges in verifiable computation, verifiable storage, and verifiable fairness. He has made significant contributions to verifiable delay functions (VDFs) and proofs of replication, which have been adopted by major blockchain projects including Ethereum 2.0, Chia, and Filecoin. His work on Filecoin's Proofs of Replication has helped the network reach over 1.5 exabytes of storage capacity. His publication record shows a clear trend toward increasingly sophisticated cryptographic protocols for blockchain applications, with recent work focusing on data availability for Bitcoin rollups, efficient folding schemes for pairing-based arguments, and privacy pools with proof-carrying disclosures. His research bridges theoretical cryptography with practical implementations that have real-world impact in decentralized systems. His notable recognition includes: Best Paper Finalist at ACM CCS 2017 for 'Iron: Functional Encryption using Intel SGX' Dr. Fisch's research has led to significant technology transfer, most notably with his work on Verifiable Delay Functions (VDFs) sparking a multimillion dollar industry initiative through the VDF Alliance. His research on Proofs of Replication forms the basis of Filecoin's incentive layer and consensus protocol. His newer SNARK system Basefold is being used by several commercial products. He maintains active collaborations across academia and industry, with publications spanning top conferences in cryptography and security. As co-founder of Espresso Systems, Dr. Fisch leads a team developing next-generation blockchain infrastructure, particularly focusing on sequencing layers for rollups. His work bridges academic research with practical implementation, ensuring that theoretical advances in cryptography find real-world applications in decentralized systems.

• Civil Engineering
• Structural Engineering
• Machine Learning in Structural Engineering
• +4 more

Giuseppe Carlo Marano is a Full Professor at the Department of Structural, Building and Geotechnical Engineering at Politecnico di Torino. He is also a component of the SISCON Interdepartmental Center for Infrastructure Safety. With expertise in civil and structural engineering, his work focuses on machine learning applications, seismic risk reduction, and sustainable structural optimization. Education Graduated cum laude in Structural Engineering from Polytechnic University of Bari PhD in Structural Engineering from University of Florence (2000) Research Interests Marano's research spans structural optimization, seismic engineering, and machine learning applications in civil infrastructure. He develops advanced computational models for: Seismic retrofitting of existing structures Optimization of steel and masonry structures Recycled materials in concrete production AI-driven structural health monitoring Multiobjective design methodologies Publication Trends His recent work emphasizes: Machine learning for concrete mix design and damage assessment Optimization of gridshells and arch structures Seismic isolation systems and vibration control Sustainable construction practices with recycled materials Multiobjective genetic algorithms for structural design Scientific Recognitions National Scientific Qualification - First Band (2013, MIUR Italy) Certificate of Appreciation for Outstanding Lecture (2012, China) Academic Contributions As an educator, he teaches: Consolidamento Strutturale (Structural Consolidation) Dinamica delle Vibrazioni Random (Random Vibration Dynamics) Progettazione Generativa (Generative Design) He also leads Challenge@PoliTo initiatives and contributes to national infrastructure safety regulations. Research Projects ADAPT4CE - Adaptive Digital Systems for Circular Economy (2025-2028) AI-ENVISERS - AI for Seismic Retrofit Environmental Impact (2023-2025) ADDOPTML - Additive Manufacturing Optimization (2021-2025)

Fred B. SchneiderView profile

Professor

• Trustworthy Systems
• Fault-Tolerant Distributed Systems
• System Security
• +6 more

Fred B. Schneider is the Samuel B. Eckert Professor of Computer Science at Cornell University , where he has been a faculty member since 1978. His career spans foundational work in trustworthy systems , fault-tolerant distributed systems , and system security . He served as department chair from 2014–2018 and previously earned a B.S. in Engineering from Cornell (1975) and a Ph.D. in Computer Science from Stony Brook University (1978).

Joanna MillsteinView profile

Research Fellow

• Fracture mechanics
• Ice dynamics
• Remote sensing
• +5 more

Joanna Millstein is a Post-doctoral Fellow in Geophysics at the Colorado School of Mines. She earned her Ph.D. in Geophysics from the Massachusetts Institute of Technology in 2023 as part of the MIT-WHOI Joint Program in Oceanography and Engineering, where her dissertation focused on The Flow and Fracture of Antarctic Ice Shelves . She also holds an A.B. in Earth Sciences from Dartmouth College (2017). Her research centers on the deformation and fracture of glacier ice, working at the intersection of fracture mechanics, remote sensing (particularly SAR and InSAR processing), statistical mechanics, and stochastic models. Millstein uses observational data from satellites and field measurements to derive mechanical and statistical models for glacier ice processes, with particular focus on reconciling observations of ice fracture and iceberg calving with theoretical models. Her work aims to resolve the nonlinear physics of glacier ice to better understand future global climate change impacts. Millstein's publication record shows a strong focus on Antarctic ice dynamics, with recent work applying extreme value theory to analyze 47 years of iceberg calving events. Her research demonstrates consistent attention to both theoretical modeling and practical applications for understanding climate change impacts on polar regions. She has developed computational tools including CryoCloud, reflecting her commitment to open science and cloud-based infrastructure for cryosphere research. Her scientific contributions span ice shelf mechanics, fracture prediction, rheology, and statistical modeling of glacial processes. Millstein maintains an active research presence with publications extending to 2025, demonstrating ongoing contributions to the field of glaciology and climate science. She is affiliated with the glaciology research center at Colorado School of Mines and maintains an active GitHub presence with climate-related code repositories. Her work bridges theoretical geophysics with practical climate change impact assessment, particularly regarding ice sheet stability and sea level rise projections.

Benjamin Mako HillView profile

Associate Professor

• Peer Production
• Online Communities
• Collective Action
• +7 more

Benjamin Mako Hill is an Associate Professor in the University of Washington Department of Communication and an Adjunct Associate Professor in Human-Centered Design & Engineering , the Paul G. Allen School of Computer Science & Engineering , and the Information School at UW. He is a Faculty Associate at the Berkman Klein Center for Internet and Society at Harvard University and a Fellow at the Center for Information Technology Policy at Princeton University during the 2023–2024 academic year. Educational Background : PhD in an interdepartmental program at Massachusetts Institute of Technology (MIT) , involving the MIT Sloan School of Management and the MIT Media Lab , advised by Eric von Hippel, Yochai Benkler, Tom Malone, and Mitch Resnick. MS in Media Arts and Sciences from MIT. B.A. in Technological and Legal History from Hampshire College . Research Interests span peer production, online communities, collective action, cooperation, learning, and computer-mediated communication. His work explores how communication and information technologies shape social outcomes in collaborative environments like Wikipedia and Linux, focusing on governance, moderation, anonymity, and educational platforms such as Scratch. Article Trends : His publications analyze peer production dynamics, privacy in open collaboration, and computational thinking in youth. Topics include underproduction in open source software, algorithmic fairness, taboo knowledge production, and legitimate peripheral participation in online communities. Methodologies combine big data, quasi-experimental, and comparative analyses. Scientific Awards : Dordick Award for Best Dissertation (2013). CHI '22 Best Paper Honorable Mention (2022). CSCW '18 Best Paper Honorable Mention (2018). CHI '17 Best Paper Honorable Mention (2017). CSCW '13 Best Paper Award (2013). CHI '11 Best Paper Honorable Mention (2011). Advising and Grants : He co-founded the Community Data Science Collective and collaborates with researchers like Aaron Shaw. Grants include multiple National Science Foundation awards for studies on digital knowledge commons, anonymous participation, and collaborative success, as well as a Sloan Foundation grant for modeling underproduction in peer production. Labs and Teams : He leads the Community Data Science Collective , an interdisciplinary research group studying online communities, and contributes to open-source projects like Debian and Ubuntu . He actively edits Wikimedia projects and participates in the Cascadia Wikimedians User Group .

• Computer Architecture
• Machine Learning
• Approximate Computing
• +3 more

Hadi Esmaeilzadeh is an Associate Professor at the University of California, San Diego in the Department of Computer Science and Engineering . He leads the Alternative Computing Technologies (ACT) Laboratory and serves as Associate Director of the Center for Machine Integrated Computing and Security (MICS) . Previously, he was an Assistant Professor at Georgia Institute of Technology. Ph.D., Computer Science and Engineering, University of Washington (2013) Research focuses on computer architecture , machine learning acceleration , and approximate computing His work has produced 15+ publications spanning IEEE Micro Top Picks , CACM Research Highlights , and ISCA . Key projects include: Tabla : Cross-stack ML acceleration framework DnnWeaver : Open-source DNN acceleration platform Major honors include: IEEE TCCA Young Computer Architect Award ISCA Hall of Fame Qualcomm Innovation Fellowship Georgia Tech PURA Award Teaching roles: CSE 141: Introduction to Computer Architecture CSE 240D: Accelerator Design for Deep Learning CSE 240A: Principles of Computer Architecture

Daniel Fosas de PandoView profile

Assistant Professor

• Net Zero Buildings
• Building Retrofits
• Indoor Air Quality
• +3 more

Dr Daniel Fosas de Pando serves as Chancellor's Fellow in Net Zero Buildings at the University of Edinburgh's School of Engineering, within the Department of Civil and Environmental Engineering and the Research Institute for Infrastructure and Environment. His work bridges building science, climate resilience, and humanitarian engineering with a focus on practical decarbonization strategies. Research interests center on net zero building retrofits at scale , indoor air quality optimization , and climate-adaptive design , particularly in vulnerable contexts like refugee shelters. His methodology combines computational modeling with field monitoring to address energy-carbon trade-offs under climate change constraints, emphasizing actionable decision-making tools for designers and policymakers. Publication trends reveal strong focus on building decarbonization pathways (38% of recent work), shelter environments for displaced populations (29%), and climate risk communication (16%). Key themes include scaling retrofit interventions, occupant behavior impacts, and simplified modeling for resource-constrained settings. Major recognitions include: Dufton Silver Medal (2022) for pioneering Active Buildings framework Best Paper Award Theme Energy (2022) Best Paper Award (2017) for building simulation research He leads the £36m InBuilt project decarbonizing non-domestic building portfolios, supervises PhD candidate M. Yildrim, and collaborates with international teams across Japan, Ethiopia, and the UK. His grant portfolio emphasizes scalable solutions for building stock management and climate resilience. Research is conducted through the Infrastructure and Environment Institute with strong ties to humanitarian engineering networks, producing open datasets on shelter thermals and building decarbonization pathways.

Andrew RiceView profile

Professor

• Programming Languages
• Machine Learning
• Artificial Intelligence
• +4 more

Andrew Rice is a Professor of Computer Science at the University of Cambridge's Department of Computer Science and Technology, and holds the Hassabis Fellowship in Computer Science. He is also the Director of Studies in Computer Science at Queens' College. His research focuses on programming languages, software engineering, and machine learning applications in software development. He leads projects like Isaac Computer Science and ALTA (Automated Language Teaching and Assessment), advancing adaptive learning technologies. His work includes static analysis tools such as Error Prone at Google, energy efficiency studies in computing infrastructure, and contributions to the Computing for the Future of the Planet initiative. His teaching emphasizes practical skill development through flipped classrooms and video lectures, earning him the 2014 Pilkington Prize for teaching excellence. He has held visiting roles at Google and collaborated on energy consumption research for mobile devices and data centers. His research spans systems, networking, and natural language processing, with a strong focus on applying computational methods to real-world challenges. Key Projects: Isaac Physics/Computer Science, ALTA, Error Prone Static Analysis Research Themes: Programming Languages, Machine Learning, Energy Efficiency Awards: Pilkington Prize (2014)

Bambang TrigunarsyahView profile

Associate Professor

• Project Management
• Infrastructure Project Delivery
• Post-Disaster Reconstruction
• +4 more

Associate Professor Bambang Trigunarsyah holds a position at RMIT University since 2018, affiliated with the School of Property, Construction and Project Management (PCPM). He earned his BSc in Civil Engineering from Colorado School of Mines, a Master's in Civil Engineering (Construction Management) from the University of Indonesia, and a PhD in Engineering Project Management from the University of Melbourne. His career spans industry roles, including project engineering in Indonesia's oil and gas sector, academic leadership at the University of Indonesia, and international teaching/research appointments at Queensland University of Technology (QUT) and King Fahd University of Petroleum and Minerals in Saudi Arabia. Research interests focus on post-disaster reconstruction, infrastructure project governance, constructability of infrastructure, and project management in developing countries. Notable projects include risk management frameworks using blockchain, circular economy in Saudi construction, and BIPV energy solutions. He actively supervises HDR students in areas like public-sector project success determinants and thermal environment studies. Bambang serves as Higher Degree Research Delegate Authority (HDR DA) for the School of PCPM and teaches postgraduate project management programs. Professional memberships include AIPM, PMI, and ASCE. His industry advisory roles include Indonesia's National Construction Service Development Board (2002-2007) and Australia-Indonesia Centre's Infrastructure Cluster (2016-2018). Recent research emphasizes BIM applications in infrastructure preservation, risk assessment methodologies, and climate-resilient construction. His work bridges theory and practice, addressing challenges in emerging economies and complex project environments.

Tobias FiebigView profile

Assistant Professor

• Network Security
• Human Factors in Security
• Internet Measurement
• +5 more

Dr.-Ing. Tobias Fiebig is a Senior Researcher at the Max Planck Institute for Informatics (Internet Architecture department) since April 2022. He previously served as a permanent Assistant Professor at TU Delft's Faculty of Technology, Policy and Management from 2017-2022. His work combines network measurement with human factors to improve security practices, focusing on email protocols, DNS infrastructure, and academic cloud migration. PhD in Computer Science from TU Berlin (2017) MSc in System and Network Engineering from University of Amsterdam (2013) BSc in Cognitive Science from University of Osnabrück (2012) His research spans Internet security (DNS, IPv6, email), academic freedom in cloud contexts, and human-centered security challenges. Recent work analyzes MTA-STS deployment, DNS sampling biases, and university cloud migration privacy implications. He has presented at top conferences including USENIX Security , IEEE Symposium on Security and Privacy , and ACM CCS . Teaching roles include lecturing Data Networks (2023-24) and On the Practice of System and Network Engineering (2024), with prior module management in cyber security analytics and sustainable system operations.

Rogério de LemosView profile

Senior Lecturer

• Resilient AI
• Self-adaptive software systems
• Authorisation infrastructures
• +7 more

Rogério de Lemos is a Senior Lecturer in Computing Science and Director of Postgraduate Research (PGR) at the School of Computing, University of Kent. He previously served as an invited assistant professor at the University of Coimbra, Portugal, and as a Senior Research Associate at the Centre for Software Reliability (CSR) at the University of Newcastle upon Tyne, UK. Dr. de Lemos' research focuses on architecting resilient systems, particularly in resilient AI, self-adaptive software systems, and authorization infrastructures. He belongs to both the Programming Languages and Systems Group and the Cyber Security Group at the University of Kent. His specific research interests include: Software engineering for self-adaptive systems assurances and resilience evaluation Dynamic generation of processes Handling insider threats using self-adaptive authorization Architectural abstractions for fault tolerance Verification and validation of dependable software architectures Software development for safety-critical systems Dependability and bioinspired computing His publication trends show increasing emphasis on practical applications of self-adaptive systems in cyber security contexts, with recent work spanning network traffic analysis, cryptographic function detection, and cloud-edge security architectures. His research bridges theoretical foundations with practical implementations, particularly in cyber security and resilient systems architecture. Dr. de Lemos currently leads the "Collaborative and Confidential Information Sharing and Analysis for Cyber Protection" project funded by the European Union's Horizon 2020 Programme. His past projects include "ADAAS: Assuring Dependability in Architecture-based Adaptive Systems" and multiple collaborations with NCR on sensor fusion and fault tolerance. As Director of Postgraduate Research, he oversees the School of Computing's research degree programs and likely supervises PhD students in resilient systems and cyber security, though specific student names are not listed in the available information.