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Jun AllardView profile

Professor

• Mathematical Biology
• Computational Biology
• Cell Mechanics
• +4 more

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
• +11 more

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
• +3 more

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 NorlingView profile

Professor

• Agent-Based Modelling
• Social Simulation
• Cognitive Modelling
• +3 more

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 BowerView profile

Professor

• Technology-Enhanced Learning
• Artificial Intelligence in Education
• Augmented Reality
• +7 more

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 AktulgaView profile

Associate Professor

• High Performance Computing
• Parallel Computing
• Big Data Analytics
• +3 more

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
• +5 more

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 MosseView profile

Professor

• Computer Architecture
• Computer Systems
• Cyber-Physical Systems
• +8 more

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 LiView profile

Assistant Professor

• Computer Architecture
• High-Performance Computing
• Multi-GPU Systems
• +4 more

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 TowlsonView profile

Assistant Professor

• Network Neuroscience
• Brain Networks
• Mental Health
• +3 more

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. CrosbyView profile

Associate Professor

• Internet of Things (IoT)
• Industrial Internet of Things (IIoT)
• Cyber-physical Systems Security
• +5 more

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.

Sajad SaeediView profile

Associate Professor

• Robotics
• Artificial Intelligence
• Simultaneous Localization and Mapping (SLAM)
• +5 more

Dr. Sajad Saeedi is an Associate Professor in the Department of Mechanical, Industrial, and Mechatronics Engineering at Toronto Metropolitan University's Faculty of Engineering and Architectural Science. He holds a PhD from the University of New Brunswick and is a licensed Professional Engineer (PEng), actively contributing to robotics and artificial intelligence research. Education: PhD – University of New Brunswick, 2014 MSc – Tarbiat Modares University, 2004 BSc – KNT University of Technology, 2001 Dr. Saeedi's research focuses on robotic perception and spatial AI, with core expertise in Simultaneous Localization and Mapping (SLAM) and interdisciplinary robotics. His work integrates mechanical, electrical, and computer science principles to develop intelligent systems capable of working alongside humans. He emphasizes innovation and problem-solving in his teaching, instilling confidence in students to tackle emerging engineering challenges. While no publications are listed in the provided text, his research trajectory centers on fast-evolving domains in robotics and AI, where recent advancements have rapidly transformed previously impossible tasks into feasible solutions. Scientific Awards: Dr. Saeedi is available to supervise graduate students and contributes to academic development through teaching core mechanical engineering courses such as Dynamics (MEC 311) and Vibrations (MEC 721). His mentorship approach encourages interdisciplinary thinking and resilience in the face of technological change. He leads research initiatives in robotic perception and is associated with advanced robotics labs at Toronto Metropolitan University, though specific lab names are not mentioned in the text.

• Human-Computer Interaction
• Extended Reality
• Virtual Reality
• +9 more

Dr. Stephen Uzor is a Senior Lecturer in the School of Computing and Engineering at the University of West London. His academic work bridges computer science, engineering, and environmental applications, with a strong focus on interactive technologies and remote sensing. His research interests include: Human-Computer Interaction (HCI) Extended Reality (Virtual and Augmented Reality) Game Design Artificial Intelligence Digital Health Robotics Remote Sensing and Environmental Monitoring Dr. Uzor's recent publications demonstrate a consistent trend in applying emerging technologies such as smartphone LiDAR, Ground-Penetrating Radar, and augmented/virtual reality for environmental and civil infrastructure monitoring. His work often involves low-cost, accessible solutions for visualizing and analyzing tree health, urban green infrastructure, and historical or transportation structures, frequently in collaboration with researchers in geoscience and civil engineering. He teaches on the BSc (Hons) Computer Games Technology program, aligning with his expertise in multimedia and interactive systems. Contact: Email: stephen.uzor@uwl.ac.uk

Doug NobleView profile

Professor

• Building Science
• Facade Tectonics
• Computing in Architecture
• +2 more

Douglas Noble is an Associate Professor and Associate Dean for Academic Affairs at the University of Southern California (USC) School of Architecture. He is a licensed architect with research interests spanning Building Science, Facade Tectonics, Computing in Architecture, and Architectural Education. Noble co-founded the Facade Tectonics Institute (2007) and the CLIPPER Lab (1991) at USC, focusing on computational design and building facade technology. He has received grants such as the 2011 Graham Foundation Grant for research on the Freeman House. Noble is a leader in architecture education, founding USC's Ph.D. program in Architecture and co-developing the 'NotLY' ARE support system. Education: Ph.D. in Design Theories and Methods (UC Berkeley) Research Interests: Active facade systems and sustainable building envelopes Parametric design and computational tools Doctoral education and emerging professional development Climate-responsive material strategies Awards: PCI Foundation Community Engagement Award (2020) Grants & Collaborations: Graham Foundation Grant (2011) ACADIA President (1998) CLIPPER Lab co-founder Facade Tectonics Institute co-founder Labs & Initiatives: CLIPPER Lab (computational design research), Facade Tectonics Institute (building envelope research).

Xiaoyu XiaView profile

Lecturer

• System Privacy and Security
• AI Privacy
• Parallel and Distributed Computing
• +4 more

Dr. Xiaoyu Xia is a Lecturer (equivalent to Assistant Professor in North America) in Cybersecurity & Software Systems at RMIT University's School of Computing Technologies. He received his PhD with the prestigious Alfred Deakin Medal from Deakin University, Australia, and has established himself as a leading researcher in distributed systems and cybersecurity with over 50 peer-reviewed publications in top-tier venues including IEEE S&P, ACM WWW, and IEEE Transactions. Dr. Xia's research spans critical areas at the intersection of computing and security: System Privacy and Security Distributed Systems and Edge Computing AI Privacy and Machine Learning Systems Sustainable Computing Cybersecurity and Privacy-Preserving Technologies His recent work demonstrates a clear trajectory toward developing practical privacy-preserving frameworks for emerging technologies, particularly in edge computing environments and large language models. Dr. Xia has made significant contributions to machine unlearning, secure data management in distributed systems, and energy-efficient edge computing solutions that balance performance with sustainability concerns. Dr. Xia has received notable recognition for his scholarly impact: World's Top 2% Scientists by Stanford University (2022-2024) Alfred Deakin Medal for PhD research excellence (2021) Teaching Excellence Award from Swinburne University of Technology (2021) As an active researcher, Dr. Xia currently leads multiple funded projects including an ARC Discovery Project grant worth over $500,000 for developing privacy-aware intelligent digital twins for secure critical infrastructures. He is open to supervising motivated PhD students with interests in system security and privacy, and distributed ML systems. Dr. Xia serves the academic community through editorial roles as Associate Editor for IEEE Transactions on Dependable and Secure Computing and as a Review Board Member for IEEE Transactions on Parallel and Distributed Systems, and regularly participates in program committees for major conferences including ACM WWW and IEEE ICDCS.