جست‌وجوی استاد و پژوهشگر

Shachar Karivمشاهده پروفایل

استاد

• Economic theory
• Experimental economics
• Behavioral economics
• +۷ مورد دیگر

Shachar Kariv is the Benjamin N. Ward Professor of Economics at the University of California, Berkeley. He earned his Ph.D. in Economics from New York University in 2003 and has been a faculty member at UC Berkeley since joining that year. His academic career includes leadership roles as Department Chair (2014-17, 2021-22) and Director of the UC Berkeley Experimental Social Science Laboratory (Xlab) from 2008 to 2014. He co-founded Xmobile, a smartphone-based platform for social science experiments. Ph.D., Economics, New York University (2003) M.A., Economics, New York University (2000) B.A., Economics, Tel Aviv University (1998) Kariv's research focuses on economic theory, experimental economics, and behavioral economics, with particular emphasis on social networks, personal and social preferences, decision-making under uncertainty, and network architecture. His work often combines theoretical models with laboratory experiments to analyze individual and collective economic behavior. Kariv's recent publications explore topics such as social learning , transfer performance of predictive models , and choice under risk and uncertainty . These works employ experimental data to investigate how individuals process information, make spending decisions, and interact within networked environments. UC Berkeley Haas School of Business Cheit Award for Excellence in Teaching (2012) UC Berkeley Division of Social Sciences Distinguished Teaching Award (2008) NYU College of Arts and Science Outstanding Teaching Award (Golden Dozen) (2002) Sloan Research Fellowship (2009-10) Outstanding Dissertation Award, NYU Graduate School of Arts and Science (2003) Kariv has received major grants from institutions like the Alfred P. Sloan Foundation , National Science Foundation , and Center on the Economics and Demography of Aging (CEDA) . His professional activities include editorial roles at prestigious journals such as the Review of Economics and Statistics and Games and Economic Behavior . He has also held visiting professorships at institutions including Stanford University, University of Oxford, and NHH Norwegian School of Economics.

Sean Ahlquistمشاهده پروفایل

دانشیار

• Material Computation and Design
• Sensory-responsive Environments
• Inclusive Architecture
• +۷ مورد دیگر

Sean Ahlquist is an Associate Professor of Architecture at the University of Michigan's Taubman College of Architecture and Urban Planning, where he serves as Director of the Master of Science in Digital Material Technologies (DMT) program. He leads the Lab for Socio-material Architectures and is a member of the Cluster in Computational Media and Interactive Systems, connecting architecture with material science, computer science, and performing arts technology. His research centers on developing malleable, sensory-responsive environments that foster social behavior for individuals with disabilities, particularly children with autism spectrum disorder. This work, inspired by his autistic daughter Ara, employs industrial knitting technologies and involves collaborations across disciplines including materials science, civil engineering, kinesiology, psychiatry, and behavioral science. His installations have been featured at the Venice Architecture Biennale, Lincoln Center's Big Umbrella Festival, and various educational and therapeutic settings. Ahlquist's publications and projects explore themes of inclusive design, computational material systems, and neurodiverse spatial experiences. His work demonstrates how architecture can leverage computational design and material technologies to create more inclusive spaces for underserved communities. ACADIA Innovative Research Award of Excellence (2020) Featured in ARCHITECT Magazine as Game Changer (2022) Recipient of U-M Sustainability Catalyst Grants (2024) Ahlquist teaches across all academic programs at Taubman College, from undergraduate to PhD levels. His students engage in multi-year collaborations with the Ann Arbor Center for Independent Living (AACIL), developing design methodologies that integrate disability theory with technical material fabrication skills. His work with the local Ann Arbor community includes partnerships with public schools, children's museums, and disability organizations to create inclusive environments that address real-world challenges.

Claudia Taitمشاهده پروفایل

پژوهشگر ارشد

• Photovoltaics
• Electron Spin Resonance Spectroscopy
• Spin Dynamics
• +۳ مورد دیگر

Dr. Claudia Tait is a Royal Society University Research Fellow at the Chemistry Department of the University of Oxford . Her research focuses on advancing Electron Spin Resonance (ESR) spectroscopy to investigate fundamental photophysical processes in photovoltaic devices, particularly spin-dependent phenomena in organic solar cells and emerging solar technologies. Education: Summa cum laude graduate from the University of Padova; DPhil from the University of Oxford under Prof. Christiane R. Timmel. Prior affiliations: Postdoctoral researcher at the University of Washington (2015-2017) and Freie Universität Berlin (2017-2020) with a Marie Curie Fellowship. Her work leverages pulse ESR and pEDMR to study charge-transfer states, triplet states, and spin interactions in photovoltaic materials. She has pioneered shaped microwave pulse techniques to enhance resolution and selectivity in ESR measurements. Current research includes CO2 photoreduction catalysts, organic semiconductor doping, and energy transfer mechanisms in bio-inspired systems. Recent publications highlight her expertise in spin dynamics , charge transport , and supramolecular systems . Notable themes include photovoltaic efficiency optimization , quantum coherence in spin systems , and innovative measurement methodologies . Scientific Awards: Bruker Thesis Prize (Royal Society of Chemistry), John Weil Young Investigator Award (International ESR Society), Marie Curie Individual Fellowship. Dr. Tait leads the Tait Group at Oxford, focusing on interdisciplinary research bridging chemistry , physics , and materials science to address challenges in sustainable energy conversion.

Justus-Jonas Erkerمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Representation Learning
• Dialogue Systems
• +۳ مورد دیگر

Justus-Jonas Erker is a PhD Candidate in Natural Language Processing at the UKP Lab, Technische Universität Darmstadt , supervised by Dr. Nils Reimers and Prof. Dr. Iryna Gurevych. His research focuses on distributed representation learning , particularly in dialogue systems and retrieval-augmented generation. Key areas include sentence-transformers, emergent properties via cosine similarity, and efficient NLP techniques. Research Interests: Representation Learning Dialogue Modeling Retrieval Augmentation Efficient NLP Algorithms Recent Work: His 2024 ACL paper introduced Triple-Encoders for efficient dialogue representation, while his 2023 work on Curved Contrastive Learning demonstrated novel approaches to dialogue planning. In 2022, he contributed a foundational cancel culture corpus for sociolinguistic NLP analysis. Affiliations: Active contributor to open-source projects (GitHub: 15 repos), including libraries for sentence-transformers and dialogue modeling. Engaged in academic outreach via Twitter/X and LinkedIn.

Jun Allardمشاهده پروفایل

استاد

• Mathematical Biology
• Computational Biology
• Cell Mechanics
• +۴ مورد دیگر

Jun Allard is a Professor at the University of California, Irvine, with joint appointments in the Department of Mathematics and Department of Physics and Astronomy. He is affiliated with the Center for Complex Biological Systems and the NSF-Simons Center for Multiscale Cell Fate Research. Education includes: Ph.D. Applied Mathematics, University of British Columbia (2011) M.Sc. Physics, Dalhousie University (2007) B.Sc. Mathematical Physics, Queen's University (2005) His research specializes in mathematical and computational modeling of cellular and biomolecular mechanics. Key interests include how cells utilize force, space, and time to solve problems, with applications in immune cell signaling, cytoskeletal dynamics, and intracellular transport. His work combines theoretical models with experimental collaborations to uncover fundamental biological mechanisms. Recent publications (2021-2025) predominantly focus on computational approaches to cellular processes, including molecular transport mechanisms, immune receptor dynamics, and cytoskeletal organization. These studies employ advanced stochastic modeling, biophysical simulations, and quantitative experimental methods to reveal principles governing cellular behavior. Scientific awards include: UCI Chancellor's Award for Distinguished Fostering of Undergraduate Research (2015) Emerging Diversity Scholar, National Center for Institutional Diversity (2016) Honorable Mention, NSF Graduate Research Fellowship (2012) He has advised over 12 doctoral students and leads the Allard Lab, which develops computational models for cell mechanics. Major grants include NSF awards for research on molecular-tether reactions (DMS-2052668), nanoparticle adhesion (CBET-1929565), and multiscale cell fate (DMS-1763272). The lab collaborates internationally with experimental groups and participates in interdisciplinary initiatives including the Chemical and Materials Physics program.

• Artificial Intelligence
• Machine Vision
• Distributed Computing
• +۱۱ مورد دیگر

Dr. Dan Ionescu is a Professor at the University of Ottawa's School of Electrical Engineering and Computer Science, Department of Electrical and Computer Engineering. He has been affiliated with the university since 1985, contributing extensively to teaching and research. His career includes visiting professorships at École Nationale Supérieure de Télécommunications (Paris) and Universitat Politècnica de Catalunya (Barcelona). He founded the Machine Intelligence Research Laboratory (1988) and the Network Computing and Control Research Laboratory (NCCT, 1999), which he currently directs. His research spans Artificial Intelligence, Machine Vision, Distributed Computing, Network Control, and Formal Methods. Notable contributions include methodologies in Expert Systems, Image Processing, Temporal Logic, and Network Management. His work has received industrial and governmental grants from CITO, Nortel, NSERC, and others. Recent research focuses on Web-based collaborative platforms (e.g., UC-IC, Watch-Together), Autonomic Computing, and AI applications in gesture control and 3D IR camera systems. Dr. Ionescu’s technical leadership includes pioneering the first distributed network management platform with industry partners and designing the NCIT*net 2 network architecture. His current interests include AI-driven solutions for cybersecurity, medical imaging, and IoT-enabled disaster response systems. He has advised numerous projects in AI ethics, quantum computing, and real-time control systems. His research trends emphasize interdisciplinary innovation, combining AI with healthcare (e.g., MRI analysis, deepfake detection), cybersecurity (GAN-based intrusion detection), and IoT (Salv AIoT platform). Collaborations with IBM CAS and Diatem Networks highlight his industry-academia integration. His legacy includes over 40 years of impactful contributions to computing and engineering education.

• Network Engineering
• Internet Infrastructure
• Data Analysis
• +۳ مورد دیگر

Zachary Bischof is a Researcher at Georgia Tech's School of Computer Science within the College of Computing. His work focuses on internet infrastructure, network reliability, and broadband analysis. He investigates topics such as outage detection, submarine cable networks, and the geographic and technical aspects of internet systems. His research spans from foundational studies on IPv4 utilization to applied projects like the iGDB platform integrating physical/logical network layers. Key areas of interest include internet measurement methodologies, infrastructure resilience, and the societal impact of telecommunications policies. He has contributed to improving outage detection algorithms, analyzing AS relationships, and evaluating consumer broadband experiences across diverse regions. His work often bridges technical and policy dimensions, emphasizing real-world applications. Notably, his publications explore undersea cable criticality, Google's AMP project's impact, and the utility of service-level agreements (SLAs) for broadband providers. While no formal awards are listed, his consistent output reflects sustained engagement with high-impact networking challenges. Zachary collaborates on projects like the Dasu platform for edge-based ISP measurements and has advised on submarine cable vulnerability assessments. His research integrates machine learning (e.g., hostname geolocation extraction) with traditional networking analysis, demonstrating interdisciplinary strengths. Future directions include expanding measurement frameworks and addressing emerging infrastructure challenges.

Emma Norlingمشاهده پروفایل

استاد

• Agent-Based Modelling
• Social Simulation
• Cognitive Modelling
• +۳ مورد دیگر

Professor Emma Norling is a Professor of Engineering Education and Director of Education in the School of Computer Science at the University of Sheffield. She holds a BEng (Hons) from the University of Melbourne and a PhD in Computer Science from the University of Sheffield. Her career includes postdoctoral work at Manchester Metropolitan University's Centre for Policy Modelling and a lecturing role at its School of Mathematics, Computing and Digital Technology. Her research focuses on agent-based systems, particularly cognitive and social simulations, with an emphasis on integrating social intelligence into computational models. She leads the Teaching Specialists group and oversees accreditation and professional institution relations. Key roles include directing educational strategy and promoting pedagogical innovation in engineering and computing education. Her publications highlight contributions to agent-based modelling methodologies, emergency response systems, and social simulation frameworks. Notable works include studies on food web evolution, morphogenetic network growth for emergency teams, and the application of BDI agents in human behavior modelling. She actively engages with interdisciplinary approaches, bridging computer science with education and social sciences. Professional service includes leading educational accreditation efforts and fostering collaboration between academia and industry. She is a sought-after expert in computational models of human behavior and their implications for educational technology and societal systems.

Matt Bowerمشاهده پروفایل

استاد

• Technology-Enhanced Learning
• Artificial Intelligence in Education
• Augmented Reality
• +۷ مورد دیگر

Professor Matt Bower is a leading academic in educational technology at Macquarie University's School of Education. Specialising in technology-enhanced learning, his work explores AI, AR, VR, and other tools to improve cognitive and collaborative learning. He has published over 100 peer-reviewed articles, led over 30 funded projects (totaling $3M+), and advised educational policymakers. His research spans teacher education, computing education, and learning design frameworks. Notable contributions include the Design of Technology-Enhanced Learning textbook (2018 AECT Award winner) and leadership in the Australian Technologies Teacher Educators Network (2019–2024). Research interests include AI in education, blended synchronous learning, and the impact of emerging technologies like wearable devices and generative AI on pedagogy. He collaborates with industry and education sectors to develop innovative learning solutions. Awards include the 2021 Australian Teaching Excellence Award and multiple Macquarie Vice-Chancellor awards. Current projects focus on screen use in education, teacher attitudes toward AI, and post-pandemic learning strategies. Professional activities include roles on ACARA’s Technologies Panel and NSW Educational Standards Authority committees. His work bridges research and practice, emphasizing teacher training and policy engagement. Projects like the ChatGPT survey and analyses of remote learning during the pandemic highlight his focus on real-world educational challenges.

H. Metin Aktulgaمشاهده پروفایل

دانشیار

• High Performance Computing
• Parallel Computing
• Big Data Analytics
• +۳ مورد دیگر

H. Metin Aktulga is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University's College of Engineering. His research focuses on high-performance computing, parallel algorithms, and numerical methods for large-scale scientific applications. He leads interdisciplinary projects involving collaborations with computational physicists and materials scientists to develop scalable software systems. His work includes the development of PuReMD, a reactive molecular dynamics code, and DOoC+LAF, a task-based middleware for data analytics. He explores parallel computing on emerging architectures, emphasizing energy efficiency and performance optimization. His research spans applications in molecular modeling, nuclear physics, and computational biology. Awards and grants are not explicitly listed, but his contributions are highlighted through collaborations with projects like MFDn (nuclear structure) and SHINES (electronic structure computations). He advises students in computational methods and leads efforts to automate force field optimization using machine learning and big data analytics. Labs and teams include the High-Performance Computing group at MSU, with active participation in interdisciplinary initiatives to bridge simulation and data-driven discovery in materials science and quantum systems.

• Visual Media Compression
• Machine Learning
• End-to-End Optimization
• +۵ مورد دیگر

Jona Ballé is an Associate Professor in the Department of Electrical and Computer Engineering at New York University Tandon School of Engineering. His research focuses on visual media compression, leveraging machine learning and end-to-end optimization to advance compression techniques for traditional and emerging modalities (e.g., AR, plenoptic imaging). He holds a PhD in signal processing from RWTH Aachen University (2012), followed by postdoctoral work at NYU’s Center for Neural Science and a Research Scientist role at Google (2017–2024). His contributions include foundational work on JPEG AI and leadership in conferences such as CLIC and DCC. Education: PhD in Signal Processing, RWTH Aachen University (2012) Master’s in Signal Processing, RWTH Aachen University (2007) Research: Ballé bridges machine learning and perceptual science to improve compression efficiency. Key areas include perceptual metrics, end-to-end optimization, and distributed coding. His work on Wasserstein distortion and Fourier basis models reflects cutting-edge advancements in compression theory. Impact: As co-organizer of the Challenge on Learned Image Compression (CLIC) and program committee member of the Data Compression Conference (DCC), he drives community progress. His industry collaborations and leadership in the JPEG AI standard highlight his translational research.

Daniel Mosseمشاهده پروفایل

استاد

• Computer Architecture
• Computer Systems
• Cyber-Physical Systems
• +۸ مورد دیگر

Dr. Daniel Mosse is a Professor in the Department of Computer Science at the University of Pittsburgh. He holds a PhD from the University of Maryland, College Park, and has been a faculty member since 1993. His research focuses on distributed systems, real-time systems, power management, security, and fault tolerance, bridging operating systems and networking research. He has held leadership roles, including Chair of the Department of Computer Science since 2009 and Visiting Professorships in Brazil. His work spans grants totaling millions, addressing energy-efficient computing, secure infrastructure, and embedded systems. Education: PhD (1993), MS (1990), and BS (1985) in Mathematics and Computer Science. Research interests include distributed real-time systems, multicore systems, embedded systems, and wireless networks. Notable awards include the 2007 Provost's Innovation in Education Award and the 2006 Bellet Teaching Award. Key grants include NSF-funded projects on energy-efficient data centers, secure emergency management systems, and power-aware scheduling. He advises numerous students and teaches courses on operating systems and distributed systems. His contributions to real-time systems, fault tolerance, and energy management have been recognized through over 150 publications and international collaborations.

Bingyao Liمشاهده پروفایل

استادیار

• Computer Architecture
• High-Performance Computing
• Multi-GPU Systems
• +۴ مورد دیگر

Bingyao Li is an incoming tenure-track Assistant Professor at the University of California, Riverside's Computer Science and Engineering Department, starting Fall 2025. She is currently a fourth-year Ph.D. student at the University of Pittsburgh, advised by Dr. Xulong Tang. Her research focuses on computer architecture, particularly multi-GPU systems, virtual memory management, and address translation for high-performance computing. Educational Background: She holds a B.E. (2017) and M.S. (2020) from Tianjin University's College of Intelligence and Computing. Her Ph.D. work at Pitt emphasizes GPU architecture and system-level optimizations for large-scale applications. Research Interests: Her work spans advanced computer architectures, multi-GPU optimization, and parallel computing systems. She explores solutions like object-aware page management (OASIS), TLB enhancements (STAR), and dynamic page placement (GRIT) to improve multi-GPU performance. She also investigates system-level optimizations for large language models and GPU ecosystems from hardware to applications. Awards: She has received the CS50 Outstanding Research Fellowship (2022, 2023) and the SCI Fellowship from the University of Pittsburgh. Her contributions include internships at NVIDIA's Architecture Research Group and talks on multi-GPU computing at NVIDIA and Tianjin University. Future Work: As a faculty member, she plans to mentor PhD students in Winter/Spring/Fall 2026, focusing on next-generation GPU systems and high-performance computing challenges. Her lab will address scalability, efficiency, and emerging applications in parallel computing.

Emma Towlsonمشاهده پروفایل

استادیار

• Network Neuroscience
• Brain Networks
• Mental Health
• +۳ مورد دیگر

Dr. Emma Towlson is an Assistant Professor in the Department of Computer Science at the University of Calgary's Faculty of Science, serving as Assistant Head of Undergraduate Curriculum. She holds a Full Member position at the Hotchkiss Brain Institute and is a Child Health & Wellness Researcher at the Alberta Children's Hospital Research Institute. Her research focuses on network neuroscience, exploring how brain networks' structure-function relationships underpin health and disease. Key areas include network control theory, mental illness vulnerability, and brain connectivity analysis across species. Dr. Towlson's work bridges computer science, physics, neuroscience, and biology. She investigates structural brain networks' topological features (e.g., rich clubs, modules) and their spatial constraints, applying these insights to disorders like schizophrenia, depression, and Alzheimer's. Her lab uses network control principles to identify therapeutic targets for brain stimulation therapies and personalized medicine approaches. Recent grants include a $250,000 New Frontiers in Research Fund (NFRF) Explorations grant (2022) to study preterm birth's impact on brain networks and mental illness risk. She teaches courses on social network analysis (CPSC 572/672) and data visualization (DATA 601). Collaborative efforts include partnerships with Harvard Medical School and Monash University's Turner Institute. Her team’s interdisciplinary projects include analyzing mouse brain connectomes, simulating connectome perturbations, and developing open-source network neuroscience tools. Ongoing work emphasizes translating network science insights into clinical applications for mental health interventions.

Garth V. Crosbyمشاهده پروفایل

دانشیار

• Internet of Things (IoT)
• Industrial Internet of Things (IIoT)
• Cyber-physical Systems Security
• +۵ مورد دیگر

Garth V. Crosby is an Associate Professor at Texas A&M University's Department of Engineering Technology and Industrial Distribution within the College of Engineering. He is also affiliated with the Multidisciplinary Engineering program. His research focuses on IoT and IIoT security, cyber-physical systems, and STEM education innovation. Crosby holds a Ph.D. in Electrical Engineering from Florida International University (2007), an M.S. in Computer Engineering, and a B.S. in Electronics (Applied Physics) from the University of the West Indies. His work spans cybersecurity frameworks for emerging technologies, including blockchain-based federated learning, post-quantum cryptography, and IoT threat mitigation. He has contributed to educational advancements through online lab design and faculty efficacy studies in hybrid learning environments. Crosby's recent publications emphasize securing robotic IoT systems, supply chain blockchain applications, and ransomware evasion techniques using generative AI. His research portfolio includes over 40 peer-reviewed articles in journals like IEEE Transactions and conferences such as ASEE and FiCloud. Key themes include volunteer cloud reliability models (ProTrust), edge computing security, and educational technology evaluation. Crosby's interdisciplinary approach bridges engineering systems with pedagogical innovation, addressing both technical and human factors in modern technological challenges.