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Chunming QiaoView profile

Professor

• Cyber-Physical Systems
• Optical Networks
• Wireless Networks
• +6 more

Dr. Chunming Qiao is a SUNY Distinguished Professor and Chair of the Department of Computer Science and Engineering at the University at Buffalo (SUNY) , leading the Lab for Advanced Network Design, Evaluation and Research (LANDR) since 1993. His work spans cyber-physical systems , optical networks , and Internet of Things (IoT) , with a focus on safety, reliability, and protocol design. Education: PhD in Computer Science from the University of Pittsburgh (1993) BS in Computer Science and Engineering from the University of Science and Technology of China (1985) Dr. Qiao’s research interests combine theoretical and applied network design, including autonomous vehicles , quantum computing , and cloud services . He pioneered optical burst switching (OBS) and iCAR systems for wireless convergence, cited in BusinessWeek and Wireless Europe . His recent publications emphasize quantum networking , federated learning , and autonomous driving security , with projects on entanglement routing , edge inference optimization , and LiDAR adversarial attacks . Articles span IEEE and ACM venues , and include best paper awards . Scientific Awards: TC-CSR Distinguished Technical Achievement Award (2015) SUNY Chancellor's Award for Excellence (2013) IEEE Fellow (2009) UB Exceptional Scholar-Sustained Achievement Award (2005) Dr. Qiao has secured over two dozen NSF grants and collaborations with Google , Cisco , and NEC Labs . His 7 US patents and consulting experience highlight his industry impact, while his editorial roles and conference leadership underscore academic influence. He actively contributes to multi-disciplinary research through the New York State Center of Excellence in Bioinformatics and Life Sciences and CEDAR , advancing high-performance computing and document analysis .

Omar AlamView profile

Associate Professor

• Software Engineering
• Model-Driven Software Engineering
• Aspect-Oriented Modelling
• +3 more

Professor Omar Alam is an Associate Professor in the Department of Computer Science at Trent University. His research focuses on software engineering, particularly Model-Driven Software Engineering, Aspect-Oriented Modelling, and Mining Software Repositories. Prior to Trent, he earned his PhD at McGill University, specializing in Model-Driven Engineering. He has received notable awards such as the ACM SIGSOFT Distinguished Paper Award (2019) and the Merit Award for Excellence in Research (2022). His teaching includes courses like Software Specification (COIS 3030), Software Design and Modeling (COIS 2240), and Software Architecture (COIS 3040). Key grants include the NSERC Discovery Grant (2017-2024) and past fellowships from NSERC and FRQNT. His work spans collaborative modeling, automated grading systems, and empirical studies on developer practices. Research often intersects software development methodologies, tool integration, and socio-technical aspects of computing. His recent publications explore topics like developer workplace communication, transit schedule deviations using real-time data, and three-way domain-specific model differencing. He actively contributes to journals like SoSyM and conferences such as SLE and ICSM. His teaching excellence is recognized through student awards and nominations, reflecting his commitment to pedagogy in computer science education.

Viji AhanathapillaiView profile

Assistant Professor

• Biomedical Signal and Image Processing
• Wearable Technology for Health Monitoring
• Women's Health
• +3 more

Dr. Viji Ahanathapillai is an Assistant Professor in Biomedical Engineering at the University of Warwick's School of Engineering, specializing in the Systems and Information Engineering stream. She holds a PhD in biomedical signal and image processing from the University of Strathclyde and has extensive industry experience in roles such as Image Processing Algorithms Engineer at Lucid Software Ltd and Development Scientist at Malvern Panalytical Ltd. Her academic career includes post-doctoral research at Warwick's Institute of Digital Healthcare and a Senior Lecturer position at Birmingham City University. Education: B.Eng (India) → PhD (University of Strathclyde). Research focuses on Biomedical Signal/Image Processing , Wearable Health Monitoring , Women's Health , and AI in Healthcare . Recent work includes developing algorithms for venous dislodgement detection, AI-driven healthcare data analysis, and wearable devices for real-time health monitoring. Teaching: Course leader for MSc Diagnostics Data and Digital Health, and module leader for Research Project modules. Provides weekly math support to first-year students. Labs/Teams: Active contributor to the Systems & Information Engineering team and the Institute of Digital Healthcare at Warwick. Editor of IET Healthcare Technology Letters.

• Experimental astroparticle physics
• Dark matter detection
• WIMP detection
• +4 more

Matthew Szydagis is an Associate Professor in the Department of Physics at the University at Albany, State University of New York, where he conducts cutting-edge research in experimental astroparticle physics with a focus on dark matter detection. Education: PhD, University of Chicago, 2010 Postdoctoral Associate, University of California Davis, 2010-2014 Dr. Szydagis leads research efforts centered around the LZ (LUX-ZEPLIN) Dark Matter Experiment, the world's largest direct dark matter search project operating at the Sanford Underground Research Facility. His expertise lies in the physics of two-phase Xenon time-projection chambers and the development of sophisticated Monte Carlo simulation techniques to understand detector responses. In 2011, he created the NEST (Noble Element Simulation Technique) software package, which has become an essential tool for the broader scientific community working with noble element detectors. His research spans multiple disciplines including particle physics, astrophysics, and computational physics, with applications extending beyond dark matter research into neutrino physics and medical physics. Dr. Szydagis is an active member of the international LZ collaboration and leads the Dark Matter Research Group at the University at Albany. His work contributes significantly to establishing the world's most sensitive limits on dark matter interactions across a wide range of particle masses.

António Nestor RibeiroView profile

Assistant Professor

• Software Engineering
• Object-Oriented Modeling
• Program Analysis
• +4 more

António Nestor Ribeiro is an Assistant Professor at the Department of Informatics, University of Minho, Portugal, and holds the role of Senior Researcher at the High-Assurance Software Centre (INESC TEC) since 2011. He earned both his MSc (1998) and PhD (2008) in Computer Science from the University of Minho. His research focuses on object-oriented modeling, program analysis, and requirements engineering for large-scale systems. He is affiliated with the High Assurance Software Laboratory Research Group and the Large Scale Distributed Systems Group. His work emphasizes software architecture reengineering, middleware development, and low-code platforms. He teaches model-driven engineering and has supervised numerous theses on microservices, distributed systems, and API platforms. Key research contributions include studies on HCI integration in software education, performance evaluation of microservices, cognitive models for usability in low-code platforms, and entrepreneurship education for informatics students. He has published in venues like HUMAN FACTORS and the EUROPEAN JOURNAL OF ENGINEERING EDUCATION. Education: PhD in Computer Science (University of Minho, 2008) Research Groups: High Assurance Software Lab, Large Scale Distributed Systems Group Teaching: Model-Driven Engineering courses His recent supervised theses address topics like microservices architecture principles, middleware integration, and API democratization platforms. He actively collaborates on industry projects, including Bosch process-support applications and telemonitoring systems for chronic diseases.

Rashid AliView profile

Assistant Professor

• Autonomous Systems
• Control Theory
• Aircraft Design
• +4 more

Rashid Ali is an Assistant Professor at CEES School of Engineering, specializing in Autonomous Systems and Control Theory with a focus on Unmanned Aerial Vehicles (UAVs). His research integrates advanced control systems, energy storage solutions, and aerodynamics to enhance UAV performance and safety. He holds a Doctorate in Aeronautical Engineering from Loughborough University and a Postgraduate Certificate in Teaching from the University of Hertfordshire. Education/Academic Qualifications: Doctorate in Aeronautical Engineering (1983–1987), Loughborough University Postgraduate Certificate in Teaching & Learning (2006), University of Hertfordshire Bachelor's in Aeronautical Engineering (1978–1982), Loughborough University Research Interests include: Autonomous Systems and UAV Flight Control Propulsion and Energy Storage for Unmanned Aircraft Advanced Kalman Filter Applications in DSP Aerodynamics of Sniper Bullets and Wind Turbines His work emphasizes interdisciplinary collaboration across propulsion, avionics, and structural engineering to advance autonomous aviation technology. Key Research Trends: Recent articles focus on high-altitude UAV fuel systems, parametric cost models for aircraft design, and multi-point angle-of-attack sensing for flight safety. Collaborations span energy storage, environmental impact analysis, and mobile technology for rural applications. Scientific Awards: 2018 Faculty of Engineering and Computing & Maths Intellectual Property Competition Advising & Grants: Currently accepting PhD students and leading projects like the Skyfarer IUK Project (2020) on UAV technology. Active in the IMechE UAS Steering Committee, promoting standards for unmanned aerial systems. Labs/Teams: Engaged in cross-disciplinary research groups focusing on UAV design, control systems, and renewable energy integration. His work bridges academic innovation with industry applications in aerospace and energy sectors.

• Materials Science
• Corrosion Engineering
• Electrochemistry
• +5 more

Prof. Robert Meißner is a Professor at the Department of Surface Physics and Technology at TUHH. His research focuses on molecular simulation techniques applied to corrosion processes, energy storage systems, and nanomaterials. He develops computational tools like ELECTRODE and i-PI for electrochemical and advanced molecular dynamics simulations. His work addresses challenges in magnesium battery performance, structural health monitoring of composite materials, and interfacial phenomena in nanoscale systems. Education details are not explicitly provided in the text, but his professional trajectory reflects extensive academic and industrial experience in materials science. Research interests span from fundamental studies (e.g., water imbibition in nanopores, magnetite oxidation dynamics) to applied innovations (e.g., corrosion protection via layered double hydroxides, data-driven electrolyte design). His recent publications highlight trends in data-driven materials discovery, structural health monitoring via vibro-acoustic methods, and computational prediction of corrosion inhibitors. He collaborates on projects involving graphene-based supercapacitors, epoxy resin curing dynamics, and peptide-surface interactions. Advising and grants: While student names are not listed, his research group actively explores corrosion engineering, battery technology, and nanomaterials. Projects include EU-funded initiatives and industry partnerships. Technical expertise includes ATR-FTIR spectroscopy, molecular dynamics, and machine learning for sparse data scenarios. He leads teams focused on surface science and energy storage, maintaining lab facilities for in situ electrochemical analysis and advanced computational modeling. His work bridges theoretical insights with practical applications in materials durability and energy systems.

• Computational Neuroscience
• Neural Network Simulation
• Large-Scale Simulation
• +3 more

Hans Ekkehard Plesser is a Professor at the Department of Data Science, Norwegian University of Life Sciences (NMBU). His work focuses on computational neuroscience, large-scale neural network simulations, and advancing reproducibility in computational research. He is a key contributor to the NEST simulator, a widely used open-source tool for modeling spiking neural networks. His research spans theoretical and applied aspects of neuroscience, including neuron-astrocyte interactions, connectivity patterns in neural networks, and high-performance computing strategies for brain-scale simulations. He emphasizes reproducible computational practices through initiatives like the ReScience project, promoting transparency and validation in scientific software. His publications highlight advancements in simulation methodologies, algorithm optimization, and the integration of supercomputing resources for neuroscience. He has contributed to foundational work on spiking neuron dynamics, firing-rate models, and the theoretical underpinnings of neural network behavior.

• Object-Oriented Programming
• Software Engineering
• Formal Methods
• +5 more

Bertrand Meyer is a renowned academic and software engineering expert affiliated with Constructor University in Switzerland. He previously held positions at ETH Zurich (2001-2016), the University of Toulouse (2015-2016), and Monash University. His research focuses on object-oriented programming, software engineering, formal methods, and programming languages. He is best known for developing the Eiffel programming language and pioneering the 'Design by Contract' paradigm. Meyer earned his PhD from the University of Nancy, France. His contributions include seminal textbooks like *Object-Oriented Software Construction* (1988, 1997), *Touch of Class* (2009), and *Agile!* (2014). He has received the ACM Software System Award (2006) for his work on Eiffel. His research emphasizes rigorous software design principles, formal verification, and practical software engineering practices. Key innovations include: Design by Contract methodology Advancements in object-oriented design patterns Contributions to component-based development Work on software testing and validation techniques Meyer has authored over 374 publications spanning journals, conferences, and books. His work bridges theoretical foundations and practical software development methodologies.

Thaleia Dimitra DoudaliView profile

Assistant Professor

• Operating Systems
• Machine Learning
• Computer Vision
• +4 more

Thaleia Dimitra Doudali is an Assistant Professor at the IMDEA Software Institute in Madrid, Spain, leading the Muse research lab. She holds a PhD in Computer Science from Georgia Institute of Technology (2021), advised by Ada Gavrilovska, focusing on hybrid memory management with machine learning. Prior to her PhD, she earned a Diploma in Electrical and Computer Engineering from the National Technical University of Athens (2015). Her research interests span systems for machine learning, machine learning for systems, and computer vision applications in resource management. Her work has been recognized with awards including the 'César Nombela' (2024), 'Juan de la Cierva' (2021), and Rising Star in EECS (2020). She serves on program committees for top conferences (ASPLOS, EuroSys) and organizes workshops. Her lab's projects address cloud resource management, carbon efficiency, and sustainable computing. She advises multiple PhD and intern researchers, contributing to impactful publications in SIGMOD, EuroSys, and other venues. Notable contributions include Cronus (CV-based memory management), CaRE (carbon-efficient cloud-edge orchestration), and foundational work on ML-driven resource forecasting. Her research bridges systems and AI, aiming to optimize data center efficiency and sustainability. She actively promotes diversity in STEM through mentorship roles in ACM-W Greece and Women in HPC initiatives.

• Climate Modelling
• Paleoclimate Modelling
• Earth System Modelling
• +3 more

Dr. Jan Streffing is a Scientific Programmer in the Climate Dynamics department at the Alfred Wegener Institute (AWI) in Bremerhaven, Germany. His work focuses on advancing Earth System Models (ESMs) with an emphasis on coupled climate modeling, paleoclimate simulations, and ensuring model scalability while preserving mass and energy conservation. He coordinates Earth System Model development efforts, particularly with the AWI-CM3 climate model framework. His research interests include high-resolution climate projections, atmosphere-ocean coupling mechanisms, and improving model physics through numerical methods. Streffing contributes to global kilometer-scale simulations using frameworks like IFS-FESOM, addressing challenges in resolving ocean eddies and cloud processes. He has developed ESM-Tools infrastructure to modularize climate modeling workflows and enhance computational efficiency. Key projects involve the MOSAiC expedition evaluation, where nudging techniques were applied to align model outputs with in-situ observations, revealing model deficiencies in cloud dynamics and snowpack representation. His work also explores deep-water formation impacts on climate sensitivity and integrates data assimilation techniques to improve sea ice forecasts in the AWI coupled prediction system. Streffing's contributions bridge climate science and computational practices, supporting advancements in model resolution, scalability, and accuracy for understanding future climate scenarios.

Lutz PrecheltView profile

Professor

• Software Engineering
• Empirical Software Engineering
• Agile Processes
• +5 more

Lutz Prechelt is Professor of Informatics at Freie Universität Berlin where he heads the Software Engineering research group (AG SE). His academic journey spans theoretical foundations, industry experience, and extensive empirical research in software engineering. He has held significant administrative positions including Executive Director of the Institute of Informatics and member of various academic senates. Prechelt's research interests have evolved from artificial intelligence and neural networks to empirical software engineering, with a recent focus on qualitative approaches to Agile processes and Pair Programming. His work has consistently emphasized methodological rigor, having conducted pioneering controlled experiments on topics like type-checking, inheritance depth, design patterns, and the Personal Software Process. His research has also ventured into plagiarism detection (JPlag), melody recognition, and qualitative studies of pair programming dynamics. His publication record shows a clear transition from quantitative to qualitative approaches in empirical software engineering. Early work featured controlled experiments on specific technical aspects of software development, while more recent publications focus on qualitative analysis of team dynamics, agile methodologies, and research methodology itself. A notable thread throughout his career has been platform comparison studies (Plat_Forms) examining how different technologies affect development outcomes. Ernst Denert Software Engineering Award 2020 Prechelt has served extensively as reviewer for major funding agencies including DFG, EU, ERC, and BMBF, and as editor for journals like Journal of Universal Computer Science and Transactions on Pattern Languages of Programming. He founded the Forum for Negative Results (FNR) to address publication bias in scientific research. His research group has developed several notable software tools including Saros for distributed pair programming, JPlag for plagiarism detection, and tools for maintainable lecture videos.

Moharram ChallengerView profile

Assistant Professor

• Cyber-physical Systems
• Multi-agent Systems
• Domain-specific Modeling Languages
• +5 more

Moharram Challenger is a tenure-track Assistant Professor in the Department of Computer Science at the University of Antwerp's Faculty of Sciences. Previously, he served as an assistant professor at Ege University (2017-2018) and as a post-doctoral researcher at the University of Antwerp (2019-2020) working on Flanders Make projects PACo and DTDesign. His academic journey includes R&D leadership roles at UNIT IT Ltd. (2012-2016), post-doctoral research at Wageningen University (2016-2017), and tenure-track faculty positions at IAU-Shabestar University (2005-2009). His research spans Cyber-physical Systems , Multi-agent Systems , and Domain-specific Modeling Languages , with recent publications focusing on quantum machine learning, digital twinning, and IoT optimization. Key projects include ITEA ModelWriter, ITEA Assume, and Flanders Make initiatives. His work demonstrates strong integration of model-driven engineering with emerging technologies like quantum computing and reinforcement learning. Challenger actively contributes to the academic community as a member of IEEE and ACM . His publication record shows consistent output across top venues, with 2025 featuring significant work in quantum-enhanced learning and CPS security. Current research emphasizes practical applications in drone energy modeling, medical diagnostics, and industrial IoT systems. His advising activities focus on cyber-physical systems and agent-based modeling, supported by grants from TUBITAK and Flanders Innovation & Entrepreneurship. Key collaborations include European ITEA projects and partnerships with industrial entities through UNIT IT Ltd. Challenger maintains active development through GitHub repositories related to code refactoring, model-driven engineering, and legacy system modernization, reflecting his commitment to practical software engineering solutions.

• Quantum Computing
• Edge Computing
• Distributed Systems
• +2 more

Dr. Vincenzo De Maio is a PostDoc Researcher at the Department of Computational Sustainability, Faculty of Informatics, Technische Universität Wien. His research spans quantum computing, edge computing, distributed systems, and sustainable computing, with a focus on hybrid quantum-classical systems and edge AI applications. Current projects: HPQC (2023–2025), ThEMIS FWF (2024–2027), TRITON FWF (2023–2027) Previous projects: RUCON (2016–2023), SWAIN (2021–2024) His research explores the integration of quantum computing with classical systems, particularly in software engineering, workflow decomposition, and hyperparameter optimization. He also works on edge computing for smart cities, environmental monitoring, and traffic safety applications. Recent publications analyze quantum compilation bottlenecks, hybrid quantum-classical workflow orchestration, and quantum neural network optimization. He supervises master's theses on topics like quantum edge benchmarking and hyperparameter tuning. Key collaborations with Prof. Ivona Brandic and others Active in IEEE/ACM conferences and Springer publications

• Software Composition
• Web 2.0 Mashups
• Cloud Computing
• +6 more

Cesare Pautasso is a Full Professor at the Software Institute within the Faculty of Informatics at the Università della Svizzera italiana (USI) in Lugano, Switzerland. His research focuses on software composition techniques, Web 2.0 mashups, cloud computing, business process management, and RESTful API design. He has led projects like JOpera, a service composition tool, and contributed to frameworks such as Liquid Software for adaptive distributed systems. Education: PhD in Computer Science from ETH Zurich (2004) and a Computer Science Engineering Degree (cum laude) from Politecnico di Milano (2000). Research Interests include model-driven engineering, service-oriented architectures, and API analytics. He has authored over 200 publications and serves on numerous program committees, including IEEE and ACM. His work has been funded by grants from Swiss National Science Foundation (SNSF), EU projects like S-CUBE, and industry collaborations. Teaching and Training: Focuses on Web Development, Enterprise Architecture, and emerging technologies. Active in conferences as general chair of ECOWS 2011 and ICWE 2016. Labs/Teams: Leads research groups exploring API design, blockchain applications, and adaptive systems. Collaborates with institutions like HPI Potsdam and ETH Zurich on projects like FC4MC and API-ACE.