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Will HandleyView profile

Associate Professor

• Cosmology
• Bayesian Statistics
• Machine Learning
• +9 more

Will Handley is an Associate Professor at the Institute of Astronomy , University of Cambridge, and a Royal Society University Research Fellow. His work bridges cosmology , Bayesian statistics , and machine learning to address fundamental questions about the Universe's origin and fate. Faculty member at the University of Cambridge Co-investigator on the REACH radio telescope project Convenor of the GAMBIT cosmology working group Research Interests : Specializing in Bayesian machine learning and nested sampling , Handley develops tools to analyze complex astrophysical datasets. His group's algorithms enable constraints on dark matter , dark energy , and inflationary models , with applications to gravitational wave detection , exoplanet discovery , and even protein folding . Recent Publications highlight a focus on 21cm cosmology , cosmological tensions , and AI-driven inference . His work spans high-dimensional parameter estimation , nonparametric dark energy modeling , and machine learning for parity violation detection in large-scale structure. Scientific Awards : Royal Society University Research Fellowship Advising & Collaborations : PhD student: Wei-Ning Deng Collaborations: REACH , GAMBIT , Flatiron Institute Labs & Teams : Leads the Handley Research Group , which develops open-source tools like PolyChord , anesthetic , and GLOBALEMU . Actively involved in 21cm signal extraction and gravitational wave data analysis .

Andreas HertenView profile

Researcher

• High-Performance Computing (HPC)
• GPU Programming
• Parallel Computing
• +6 more

Andreas Herten is a Researcher at the Jülich Supercomputing Centre (JSC) within Research Center Jülich GmbH. He serves as Co-Lead of the Novel System Architecture Design division and heads the ATML Accelerating Devices group, focusing on GPU programming, parallel computing, and high-performance computing (HPC) optimizations. Key Expertise: GPU programming, parallel algorithms, HPC systems, benchmarking, Python, LaTeX Research Focus: Accelerating scientific applications on GPUs, European exascale initiatives, AI workload evaluation, and heterogeneous computing architectures His recent publications highlight advancements in GPU-accelerated materials science, AI training on HPC systems, and exascale benchmarking. Herten contributes to projects like OpenGPT-X, JUPITER, and CARAML, with work spanning computational physics, environmental science, and machine learning applications.

Brenton WalkerView profile

Researcher

• Parallel Computing
• Multipath Scheduling
• Link and Channel Emulation
• +6 more

Dr.-Ing. Brenton Walker is a postdoctoral researcher at the Institute of Communications Technology , part of the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover. His research spans parallel computing, network coding, and algebraic topology, with a focus on systems like delay-tolerant networks and mobility modeling. Education: Bachelor's, University of Wisconsin-Madison PhD in Mathematics, University of Maryland (2014) Research Interests include: Parallel systems (computing, multipath scheduling) Topological methods in networking Opportunistic/DTN architectures Channel emulation and mobility analysis Teaching: Leads the Computer Networks Laboratory student lab. Awards: ERCIM Postdoctoral Fellowship (2014-2015)

Ayman El MesalamiView profile

Senior Lecturer

• Computer Science
• Image Processing
• Cybersecurity
• +7 more

Ayman El Mesalami is a Master Lecturer & University Distinguished Teacher in the Department of Computer Science at Old Dominion University (ODU) , where he also serves as the Undergraduate Program Director . His career spans multiple institutions in the U.S. and Canada, with a focus on undergraduate education and Raspberry Pi-based projects to enhance learning in engineering and computer science. Ph.D. in Electrical and Computer Engineering from Kansas State University (2004) Dr. El Mesalami’s research bridges practical hardware-software integration and pedagogical innovation , particularly through low-cost, hands-on projects. His work includes applications in image processing , cybersecurity , IoT systems , and student-driven research . He has mentored numerous award-winning undergraduate projects, including Raspberry Pi clusters , flood detection systems , and medical diagnostics . His publications highlight the impact of Raspberry Pi in education , color restoration techniques , and parallel computing pedagogy . Recent projects explore AI in retro gaming , voice-activated assistants , and healthcare technology for visually impaired individuals. University Distinguished Teacher, ODU Teaching with Technology Award, ODU Best Teaching Award, ODU College of Sciences Faculty Innovator Grant, ODU Dr. El Mesalami actively advises student organizations like the Association for Computing Machinery (ACM) and Muslim Students Association at ODU. He has contributed to ABET accreditation and serves on curriculum and strategic planning committees.

• Biostatistics
• Genetics
• Genomics
• +7 more

Dr. Shuangge Steven Ma is the Department Chair and Professor of Biostatistics at the Yale School of Public Health , with affiliations to the Yale Institute for Global Health , Yale Cancer Center , and Yale-BI Biomedical Data Science Fellowship . His research bridges statistical methodology development and biomedical applications in cancer, mental disorders, and cardiovascular diseases. PhD in Statistics (University of Wisconsin, 2004) Postdoctoral Associate (University of Washington, 2006) Dr. Ma's research interests focus on statistical methods for complex biomedical data , including: gene-environment interactions, network analysis of omics datasets, high-dimensional regression, and integrative modeling of multi-source data. Recent work applies these methods to cancer genomics, tumor microenvironment characterization, and spatial transcriptomics. His 2024-2025 publications highlight innovations in Bayesian regression , neural network modeling , and network-based biomarker discovery , with applications spanning pancreatic cancer , melanoma , and hepatocellular carcinoma . Methodological contributions include robust variable selection, heterogeneous data integration, and spatial gene expression analysis. Fellow, American Statistical Association (2013) Elected Member, International Statistical Institute (2007) Dr. Ma provides statistical leadership for biomedical studies and health policy research , including surveys in mainland China and Taiwan examining health insurance utilization. He collaborates with institutions like the SPORE in Lung Cancer and SPORE in Skin Cancer programs.

Gennady PekhimenkoView profile

Associate Professor

• Computer Architecture
• Systems Research
• Applied Machine Learning
• +3 more

Dr. Gennady Pekhimenko is an Associate Professor in the Department of Computer Science and cross-appointed to the Electrical and Computer Engineering department at the University of Toronto. He leads the EcoSystem research group and serves as CEO/Co-Founder of CentML, with affiliations at CIFAR and Vector Institute. PhD in Computer Science from Carnegie Mellon University (2016) His research spans computer architecture, systems optimization, and applied machine learning, with a focus on memory hierarchy efficiency, hardware acceleration, and compiler design. Recent work emphasizes large language model training, GPU virtualization, and processing-in-memory systems. Key article trends include: 1) Memory optimization for transformers and sparse models (2024-2025), 2) GPU resource management (2022-2024), 3) Prompt programming languages (2025), and 4) Deep learning compilation frameworks (2021-2023). Major Awards: NVIDIA Graduate Fellowship, Microsoft Research PhD Fellowship, ISCA Hall of Fame, AWS/Google/VMware research grants Key Collaborations: Onur Mutlu (CMU), Todd Mowry (CMU), Vector Institute researchers

• Signal Processing
• Sensor Engineering
• Graph Neural Networks
• +4 more

G.J.T. Leus is a Professor at Delft University of Technology's Faculty of Electrical Engineering, Mathematics and Computer Science, where he leads research in the Signal Processing Systems department. His work spans foundational algorithms and applied systems across wireless communications, medical imaging, and network analysis. With over 498 research outputs including journal articles, conference papers, and patents, he maintains an active research program in cutting-edge signal processing methodologies. Research interests focus on: Signal Processing Systems : Advanced algorithms for spectral estimation, array design, and sensor optimization Computational Imaging : Ultrasound techniques for medical diagnostics including carotid artery visualization Graph-Based Methods : Graph neural networks for localization and topology identification Wireless Technologies : OTFS modulation, MIMO systems, and phased array design Recent publications (2023-2025) demonstrate strong emphasis on: Integration of deep learning with tensor decompositions for channel estimation Fundamental limits in estimation theory using Cramér-Rao bound frameworks Topological signal processing extensions to simplicial complexes Computational imaging innovations for medical ultrasound Academic leadership includes editorial roles for the Eurasip Journal on Advances in Signal Processing , keynote presentations at major conferences (e.g., Asilomar 2023), and supervision of graduate researchers. Current projects involve multi-sensor systems for network localization, ultrasound imaging with limited transceivers, and robust graph neural architectures.

Samuel DorchuckView profile

Lecturer

• Cybersecurity
• Cyber Operations
• Computer Systems
• +3 more

1stLt Samuel Dorchuck serves as a Cyber Instructor at the Center for Cyber Security Studies (CCSS) within the Cyber Science Department of the United States Naval Academy, reporting to the USNA Marine Detachment in April 2025. As a First Lieutenant in the United States Marine Corps, he contributes to cyber education while maintaining active military service. His academic foundation includes dual Bachelor of Science degrees in Computer Science and Mathematics from MIT (2021), followed by a Master of Engineering in Electrical Engineering and Computer Science with Computer Systems concentration (2021). His military training encompasses The Basic School at Quantico (graduating third in company with Commanding General's Honor Role recognition), Cyberspace Operations Officer Course 23-001 (as Honor Graduate), and operational cyber command experience. Dorchuck's research profile centers on defensive cyber operations, evidenced by his establishment of the Defensive Cyberspace Weapons Platoon (DCWP) as general support unit for cyber weapons system employment and threat emulation training. His operational deployments include Talisman Sabre 23 as Cyber Planner in the Combined Joint Network Security Operations Center and executive leadership of the DCO-IDM Company. His military honors include meritorious career designation at The Basic School and Cyberspace Operations Officer Course Honor Graduate distinction, though no scientific awards are documented. As Cyber Instructor, he leverages frontline cyber warfare experience to train midshipmen in practical cyber defense methodologies within the CCSS framework.

• Biomedical Engineering
• Medical Imaging
• Image Processing
• +5 more

Dr. José Antonio Pérez Carrasco is a Full Professor in the Department of Signal Theory and Communications at the University of Seville. He leads the Signal Processing and Communications research group and has participated in numerous biomedical engineering projects focused on medical imaging, surgical planning, and neuromorphic vision systems. Professional Status: Full Professor Research Group: Signal Processing and Communications His research integrates computer vision, machine learning, and biomedical applications to solve medical challenges such as skin lesion segmentation, thermographic diagnosis of hemangiomas, and 3D CT image analysis. He has developed innovative algorithms for bone/muscle segmentation and retroperitoneal tumor delineation, often using convex relaxation techniques and event-based processing. Dr. Pérez Carrasco has secured multiple research grants including Burn Image Analysis System (PI-1597/29/2016), Mitochondrial segmentation in CT images (PI-1209/2013), and MISSION ALPHA (AEI-010500-2023-46). He has directed the doctoral thesis of Cristina Suárez Mejías on tissue segmentation and mentored numerous projects in intelligent infrared vision sensors. He actively contributes to university teaching innovation, implementing participatory techniques in engineering education and integrating company tasks into practical subjects. His work bridges academia with industry through contracts like the System for bone marrow radiotherapy toxicity analysis (PI-2566/33/2025).

Juan Luis Herrera GonzalezView profile

Researcher

• Computing Continuum
• Microservice Orchestration
• Network Management
• +7 more

Juan Luis Herrera Gonzalez is a Postdoctoral Researcher at the Distributed Systems Group within the Faculty of Informatics at Technische Universität Wien (TU Wien) . Previously affiliated with the University of Extremadura, University of Pisa, and University of Bologna, his research focuses on Computing Continuum systems, microservice orchestration, network optimization, and sustainability in distributed environments. PhD in Computer Science (University of Extremadura, 2023) Collaborator with 8 universities across 4 countries 50+ publications with 270+ citations His work addresses Quality of Service (QoS), economic cost reduction, and sustainability in domains such as IoT, 5G networks, and Digital Twins. Recent publications emphasize machine learning-driven SDN optimization, federated learning applications, and energy-efficient fog computing. He contributes to frameworks for adaptive analytics, xApp development, and latency minimization in hybrid infrastructures. His research portfolio spans from theoretical models using Mixed-Integer Linear Programming to practical implementations in testbeds for O-RAN and SDN-fog scenarios. Current projects include the Marie Skłodowska-Curie Actions fellowship, focusing on real-world deployments and developer-centric tools like EFCC (Emulation Framework for Cloud Continuum) and xSTART (xApp Simulation Environment).

• Machine Learning
• Artificial Intelligence
• Health Informatics
• +3 more

Jens Lundström is a Senior Lecturer at the School of Information Technology, Halmstad University. His research and teaching focus on Machine Learning and Artificial Intelligence, particularly their applications in healthcare, patient experience, and quality of life improvement. Research Area Leader for AI in CAISR Health Coordinator for Halmstad Professionals network (AI, data analytics, cybersecurity, service design) His research integrates applied and theoretical Machine Learning with healthcare domains, covering synthetic data generation, smart home systems, and data privacy. Recent publications highlight his contributions to Explainable AI, Generative Adversarial Networks, and robustness in Deep Learning for health and traffic data. No specific scientific awards or students are mentioned in the provided texts.

• Mathematics of consciousness
• Neuromorphic information processing
• Network theory
• +7 more

Professor Peter Grindrod holds a faculty position at the Mathematical Institute, University of Oxford, where he leads research in applied mathematics with focus on neuromorphic computing and network theory. His affiliations include the Machine Learning and Data Science research group and the Oxford Centre for Industrial and Applied Mathematics. Research interests span mathematics of consciousness, neuromorphic information processing, network theory, and digital marketing. His innovative work on cortex simulations via Kuramoto-type models enables laptop-based simulations of neural columns instead of computationally expensive full-brain models. He investigates AI's inner workings, particularly how layer-by-layer topology explains vulnerability to adversarial attacks. His 15 most recent publications (2018-2025) reveal strong focus on consciousness modeling (27%), network dynamics (33%), and AI/neuromorphic computing (40%). Key trends include mathematical consciousness frameworks, sparse network modeling for brain simulation, and topology-based analysis of neural networks. CBE honor Grindrod leads significant research strategy initiatives, focusing on unconventional and high-risk research funding. He has secured substantial grants through his roles on EPSRC Council and RCUK Digital Economy programme. His commercial ventures include Hare Analytics, GTTA Limited, and CountingLab, demonstrating strong industry-academia knowledge exchange. He directs the Oxford Centre for Industrial and Applied Mathematics, overseeing collaborations between academic researchers and industry partners in energy, telecommunications, and digital marketing sectors.

Vincent LiuView profile

Associate Professor

• Distributed Systems
• Networking
• Programmable Networks
• +7 more

Vincent Liu is an Associate Professor in the Department of Computer and Information Science at the University of Pennsylvania's School of Engineering and Applied Science. He directs the Distributed Systems Lab (DSL) and leads the PennNetworks research group. His research bridges distributed systems and networking, focusing on programmable networks, fault-tolerance, cloud infrastructure, and Internet architecture. Education includes a Ph.D. from the University of Washington and undergraduate research at the University of Texas at Austin in compilers and parallel systems. Research spans distributed systems optimization, cloud computing, sustainable computing, and ML infrastructure. Recent publications emphasize low-latency systems (Paella), cloud multicast (Cloudcast), distributed snapshots (Beaver), and sustainable computing frameworks (Carbon Connect). Network simulation innovations include DONS and NetVision. Awards & Honors: NSF CAREER Award (2019) VMWare Early Career Award (2019) Best Paper Award, USENIX NSDI (2015) Google Fellowship in Networking (2014) Qualcomm Innovation Fellowship (2014) Facebook Faculty Research Award Google Research Award Advises 11+ PhD students, with graduates at Meta, AWS, Microsoft Research, and academia (e.g., Qizhen Zhang, Asst. Prof. at Toronto). Secured grants from NSF, VMWare, Facebook, and Google. Leads the Distributed Systems Lab and PennNetworks group exploring cloud architectures, programmable networks, and sustainable computing. Actively recruiting PhD students.

• Game Studies
• Computer Science Education
• Video Game Ethics
• +6 more

Pawel Grabarczyk serves as Associate Professor at IT University of Copenhagen, leading the Play, Culture, and AI research group within the Games Research Group. He maintains dual affiliations with the Center for Computing Education Research and the Center for Digital Play, reflecting his interdisciplinary work spanning game studies and computing education. His research interests form a unique intersection of game studies, critical theory, and computing education. Grabarczyk applies frameworks like Actor-Network Theory (ANT) and Science & Technology Studies (STS) to analyze video game design, particularly focusing on loot boxes and gambling-like mechanics. His work on gender diversity in computing education has demonstrated that programs emphasizing people rather than technical aspects appeal more to women, with significant implications for recruitment and curriculum design. Analysis of his 41 publications reveals consistent thematic threads across his career. Early work focused on game design and critical theory, while more recent publications address sustainability in gaming through the Nordic Alliance for Sustainability in Gaming projects. His computing education research shows increasing attention to onboarding strategies for students lacking programming confidence, with practical implications for reducing dropout rates. Grabarczyk has secured substantial research funding through multiple projects, including the European Commission-funded MSG (Making Sense of Games) project (2016-2022) and the Nordic Alliance for Sustainability in Gaming series (2021-2024). His work has generated significant media attention in Denmark, with coverage on topics ranging from addressing fake news through games to improving gender balance in the IT industry. As Head of the Play, Culture, and AI research group, he directs a team examining how artificial intelligence intersects with play and cultural practices. His research bridges academic inquiry with practical applications, evidenced by collaborations with game developers and educators seeking to implement his findings on inclusive computing education and ethical game design.

Alefiya HussainView profile

Researcher

• Cyber Security
• Network Measurement
• Distributed Systems
• +3 more

Alefiya Hussain is a Researcher and research lead at the Information Sciences Institute (ISI) of the University of Southern California, specializing in measurement, modeling, and emulation of networked and distributed systems for security and performance optimization. Her educational background includes a Ph.D. in Computer Science from the University of Southern California, an M.S. from USC (field unspecified), and a B.E. from Pune University, India. Research Interests: A recognized authority in Cyber Security Experimentation , her work spans Network Emulation , Distributed Systems Modeling , and Cyber Physical Security . She has developed methodologies for security testing in critical infrastructure and presented tutorials at major venues including the American Control Conference. Scientific Awards: Multiple Best Paper Nominations across ACM SIGCOMM, IEEE INFOCOM, and USENIX NSDI conferences Funding and Leadership: She directs projects funded by the Department of Homeland Security (DHS), Defense Advanced Research Projects Agency (DARPA), National Science Foundation (NSF), and Department of Energy (DoE), focusing on real-world security validation frameworks. Based at ISI's Marina del Rey facility (4676 Admiralty Way), she maintains active research collaboration across government and academic sectors with over fifty peer-reviewed publications in premier computer networking venues.