Find Academic Supervisors

• Decentralized Collaboration
• Blockchain
• Decentralized Autonomous Organizations
• +5 more

Samer Hassan is an Associate Professor at Complutense University of Madrid and Faculty Associate at Harvard University's Berkman Klein Center for Internet and Society, with a multidisciplinary background spanning Computer Science, Social Sciences, and Artificial Intelligence. His work bridges academic research with grassroots activism to advance community-driven technological solutions. His research centers on decentralized collaboration systems including blockchain, DAOs, and fediverse platforms, specifically examining how open-source decentralized architectures can sustain the Collaborative Economy through Commons-based models. Notable projects include ERC-funded research on Blockchain-based DAOs and development of practical infrastructure like SwellRT (adopted by Apache Foundation) and Decentralized Science's peer review system. Scientific recognition includes: ERC Starting Grant (1.5M€) for DAO research in the Collaborative Economy Hassan secures substantial project funding (300K€ for Decentralized Science) while applying participatory teaching methods in cyber-ethics courses. His activist work spans grassroots initiatives in Madrid and Beirut where he operates as an accredited facilitator, connecting technical development with community organizing principles. Key technical contributions include founding the interoperable open peer review system for Decentralized Science and creating SwellRT—a federated backend-as-a-service adopted by the Apache Foundation—demonstrating his commitment to building practical decentralized infrastructure.

• Programming Languages
• Functional Programming
• Type Systems
• +5 more

Ningning Xie is an Assistant Professor in the Department of Computer Science at the University of Toronto. She holds a part-time Research Scientist position at Google DeepMind and is a Faculty Affiliate at the Schwartz Reisman Institute. Previously, she was a Research Associate at the University of Cambridge and earned her Ph.D. from the University of Hong Kong and B.S. from Zhejiang University. Her research focuses on foundational aspects of programming languages, including functional programming, type systems, logics, and their applications in broader domains. Key areas include algebraic effect handlers, staged compilation, type inference, and parallel computing. She has contributed to systems like MacoCaml and Perceus, and her work has been recognized with ACM SIGPLAN Distinguished Paper Awards and the Cambridge Hall of Fame Award. Dr. Xie co-chairs the Haskell Symposium 2025 and serves on committees for major programming language conferences (PLDI, ICFP, etc.). She actively organizes workshops and tutorials, including invited keynotes at Lambda Days and ZuriHac 2024. Her service roles include moderating the Types Forum and steering committees for Haskell and PLMW. Her academic contributions span over 25 peer-reviewed publications, with a focus on practical implementations and formal proofs. She advises students through her research group and emphasizes generative programming techniques in her teaching.

• Software Engineering
• IT Security
• Realtime Communication Systems
• +6 more

Jürg Nietlispach is a Senior Research Associate at Lucerne School of Computer Science and Information Technology (HSLU). His work focuses on software engineering, IT security, and distributed systems. He holds a BSc in Computer Science from University of Bern with minors in Mathematics and Philosophy of Science. Education: Matura, Gymnasium Hofwil (Müchenbuchsee) BSc Computer Science, University of Bern (Minors: Mathematics & Philosophy of Science) Research Focus: App Development for iOS/Android (native and platform-independent) App Backend/Server Development CI/CD Implementation on Linux/Docker Quantum-safe Hardware Security Module Research Security conceptualization for distributed computation systems Professional Experience: Senior Software & Security Engineer at g&o embedded systems GmbH Senior Software Engineer at Admia Solutions AG Lecturer at GIBZ Freelance Software Developer and ZEND Certified Engineer Key Skills: Realtime communication protocols (PCSC, RS485) Embedded database systems Virtualization/container technologies Security architecture for distributed systems Projects: Quantum-safe Hardware Security Module Secure distributed computation system National network for MINT education development Engagements: Member of Swiss-Army Cryptology-Section (2003-2012) Musician playing Double-Bass, Guitar, and Cittern

• Computer Adaptive Testing
• Information Systems
• E-learning Platforms
• +5 more

Svetlana Anđelić is a Professor at Singidunum University's Faculty of Informatics and Computing, specializing in Information Systems and Educational Technology. She holds a PhD from Union University (2010) focusing on Computer Adaptive Testing (CAT) methodologies. Her academic career includes extensive work in software development, e-learning platforms, and IT applications in education and business. Education: PhD in Management Information Systems (Union University, 2008-2010) MSc in E-Business (University of Belgrade, 2002-2007) BSc in Information Systems (University of Belgrade, 1996-2001) Research focuses on: Computer Adaptive Testing algorithms for education and HR Machine Learning applications in education and energy systems E-learning platforms and remote teaching strategies Cybersecurity in information systems IT-driven business process optimization Rural tourism digitalization Recent work highlights: Developed photovoltaic production forecasting models using GRU networks (2025) Authored books on C# programming, database applications, and software design patterns Lead multiple EU-funded projects on edtech and rural development Labs/Teams: Active in Singidunum's Department of Informatics and Computing, collaborating with Universities of Belgrade and Novi Sad on IT education initiatives.

• Cybersecurity
• Information Security
• IoT Security
• +6 more

Martina Lindorfer is an Associate Professor at the Department of Security and Privacy, Faculty of Informatics, Technische Universität Wien (TU Wien). Her primary roles include academic research and teaching in cybersecurity, privacy engineering, and IoT security. She coordinates the Women in Informatics initiative and leads research projects addressing critical security challenges across mobile, IoT, and cloud ecosystems. Dr. Lindorfer holds a Dipl.-Ing. (BSc) and a PhD in Technical Informatics from TU Wien (2011 and 2015, respectively). Her research focuses on malware analysis, mobile security, and privacy-preserving technologies. Notable projects include the WWTF-funded IoTIO initiative analyzing IoT device vulnerabilities and the W4MP project exploring cross-platform malware threats. Key research interests span: Cybersecurity frameworks for IoT ecosystems Privacy implications of smart TV protocols (HbbTV) Mobile app vulnerability analysis APT campaign attribution through file forensics Academic cloud migration risks Her work bridges technical analysis with societal impacts, addressing topics like surveillance technology and academic freedom in cloud environments. Lindorfer has supervised over 20 graduate students, with recent theses focusing on rootkit detection, ART-based app diffing, and privacy in configuration repositories. Current grants include: IoTIO (2020–2025): Securing IoT ecosystems W4MP (2023–2027): Cross-platform malware research Browsec (2018–2024): Browser security analysis Her lab develops tools like C2Miner (C2 server detection) and FlowPrint (encrypted network fingerprinting), contributing to both academic and industry standards. Lindorfer actively collaborates with organizations like the European Commission and FFG on cybersecurity policy and threat mitigation strategies.

• Data Engineering
• Database Systems
• High-Performance Computing
• +3 more

Carlos Alonso Pérez is an Adjunct Professor at IE University, Spain. He holds academic ties with Salamanca Pontifical University and Pontifical Bolivarian University (Colombia), where he also served as Adjunct Professor. His professional career spans over 15 years in tech, specializing in backend engineering, data systems, and cloud technologies. Currently, he works as a Software Development Engineer at AWS, focusing on databases and high-scale systems. Education: Engineer degree in Computer Science, Salamanca University, 2012 Masters in Security and ECommerce, Salamanca University, 2008 Bachelor in Computer Science, Salamanca University, Spain, 2008 His research and professional interests emphasize scalable software architectures, data-driven systems, and cloud-native solutions. Beyond academia, he actively contributes to tech communities through public speaking, mentoring, and open-source initiatives.

Geoffrey MainlandView profile

Associate Professor

• Programming Languages
• Systems
• High-level Programming Languages
• +12 more

Geoffrey Mainland is an Associate Professor in the Department of Computer Science at the College of Computing and Informatics, Drexel University. His research bridges programming languages and systems, with a focus on enabling high-level, efficient programming of specialized hardware such as GPUs, FPGAs, and software-defined radios. He has developed domain-specific languages and runtime systems to simplify and optimize non-general-purpose computation. PhD in Computer Science, Harvard University, 2011 AB in Physics, Harvard University, Magna Cum Laude, 2000 His research interests include high-level programming languages, runtime support for specialized devices, functional programming (particularly in Haskell), stream fusion, SIMD vectorization, and domain-specific languages for systems programming. He investigates how to make it easier to exploit the performance of GPUs, sensor networks, and FPGAs without sacrificing abstraction or safety. The recent publications highlight a consistent theme: enhancing performance in functional languages through language design, compiler optimizations, and runtime systems. Key areas include SIMD support in Haskell, GPU programming via Nikola and MetaHaskell, staged programming for sensor networks (Flask), and domain-specific languages like Ziria for software-defined radio. These works demonstrate a strong focus on bridging the gap between high-level abstractions and low-level efficiency. Geoffrey Mainland has not been mentioned as receiving any scientific awards in the provided material. He advises current PhD student Dresden Feitzinger and has previously advised Mahshid Shahmohammadian, now at Intel. His research has been supported through academic and possibly federal funding, though specific grants are not detailed. His work is implemented in open-source projects hosted on GitHub, including contributions to the Haskell vector library and the development of Ziria and DragonRadio. He leads a research group focused on programming systems, with active projects in software-defined radio (Ziria, DragonRadio), high-performance numerics in Haskell (HSpiral), and language support for heterogeneous computing. His team develops tools that enable researchers and developers to write efficient, correct code for specialized hardware using high-level functional abstractions.

Hartwig AnztView profile

Professor

• High-Performance Computing
• Sparse Linear Algebra
• Iterative Methods
• +6 more

Prof. Hartwig Anzt is a Professor at TU Munich, leading the Chair of Computational Mathematics within the TUM School of Computation, Information, and Technology. He also holds a professorship at the University of Tennessee and directs the Innovative Computing Lab (ICL). His research focuses on high-performance computing, particularly in sparse linear algebra, iterative methods, Krylov solvers, and preconditioning. He emphasizes sustainable software development and leads the Ginkgo open-source library for scientific computing. Academically, Anzt earned his PhD in 2012 from the Karlsruhe Institute of Technology (KIT) and led a Helmholtz junior research group there. He has extensive collaborations with institutions like Sandia National Laboratories, Argonne National Laboratory, and the University of Tennessee. His software projects include Ginkgo and MAGMA-sparse, both part of the xSDK ecosystem. Recent talks highlight his work on exascale computing, GPU optimization, and software sustainability. He advocates for platform-portable numerical libraries and has contributed to the Exascale Computing Project (ECP). His research addresses challenges in energy efficiency, fault tolerance, and algorithm design for multi/manycore architectures.

Christoph StampferView profile

Professor

• Condensed Matter Physics
• Graphene and 2D Materials
• Quantum Devices
• +5 more

Prof. Dr. Christoph Stampfer is a full professor and director of the II. Institute of Physics (Institute 2A) at RWTH Aachen University, affiliated with the Department of Physics and the Materials Science & Engineering (MatSE) profile area. He leads the 2D Materials and Quantum Devices Group, focusing on experimental physics in graphene and 2D materials. He is also a key developer of the educational app phyphox , promoting innovative physics education. His research interests include condensed matter physics , quantum devices , spintronics , and nanoelectronics , with a focus on transport properties in graphene-boron nitride heterostructures and spin dynamics. He also pioneers smartphone-based physics experiments for education, leveraging mobile sensors for accessible, hands-on learning. His recent publications reflect a dual focus: cutting-edge research in Physical Review B and educational innovations in journals like Physics Education and European Journal of Physics . Themes include quantum phenomena in 2D materials, DIY sensor integration, and collaborative classroom experiments using mobile technology. Georg-Kerschensteiner-Preis (2023) Ars-legendi-Fakultätenpreis (2020) Falling Walls Winner (2020) RWTH Lecturer Award (2021) Lehrpreis der DPG (2019) Archimedes-Preis (2019) Lehrpreis Physik (2018) Fellowship für digitale Hochschullehre (2016) Stampfer actively supervises a large group of PhD and master’s students, including Hubert Dulisch, David Emmerich, and Katrin Hecker. His group collaborates on both fundamental research and educational outreach. He has received multiple grants supporting digital teaching and experimental physics. The phyphox project, in particular, has been widely adopted in schools and universities, supported by workshops and teacher trainings he co-organizes. The group operates advanced nanofabrication and low-temperature measurement facilities for quantum device research.

Noel Ruault MartinezView profile

Associate Professor

• Cybersecurity
• Software Engineering
• Golang
• +4 more

Noël Ruault Martinez is an Associate Professor at the University of the Balearic Islands (UIB), affiliated with the College of Engineering. He teaches courses in Cybersecurity and Project Management for Telematics Engineering degrees, including dual programs with Mathematics. His technical expertise spans backend development, distributed systems, and algorithm optimization across global institutions. Current Roles : Professor of Cybersecurity (2023–present) at UIB; Teacher of Computer Science (2022–present) at IES Politecnic. Research Interests : Focus on secure software architecture, Go programming language applications, and performance optimization in distributed environments. Projects include PromQL benchmarking tools, callback services with Zipkin tracing, and mathematical/algorithmic challenges like the Flea Circus problem. Technical Leadership : Demonstrates proficiency in designing scalable systems with technologies like Kubernetes, Docker, AWS, and PostgreSQL, while emphasizing rigorous testing and code quality.

• Artificial Intelligence
• Cloud Computing
• Internet of Things
• +7 more

Aamir Akbar serves as an Assistant Professor in the Department of Computer Science & Information Systems at Abdul Wali Khan University Mardan (AWKUM), where he also co-directs both the AWKUM AI Lab and AWKUM Robotics initiatives while coordinating final year projects. His academic journey culminated in a PhD from Aston University, Birmingham, UK, with research focused on energy-efficient methods for hybrid mobile cloud computing. His educational background includes a PhD in Computer Science from Aston University (2015-2019, awarded February 2020), where his dissertation explored energy-efficient approaches for hybrid mobile cloud computing systems. Dr. Akbar's research spans multiple cutting-edge domains in computer science, with particular emphasis on Artificial Intelligence , Cloud and Fog Computing , Internet of Things , and Software Defined Networks . His multidisciplinary approach combines evolutionary computation, multi-objective optimization, and machine learning to develop resource-efficient intelligent systems. His work frequently addresses challenges in Cyber-Physical Systems, Mobile-Cloud Computing, and IoT/IoV applications, demonstrating strong practical relevance to real-world problems. Analysis of his recent publications (2021-2024) reveals a clear research trajectory toward increasingly sophisticated AI applications in networking and distributed systems. His work shows strong focus on reliability, energy efficiency, and security across multiple domains including medical IoT, smart cities, and industrial automation. The growing citation impact (612 total citations, h-index: 14) demonstrates increasing recognition of his contributions to these fields. Dr. Akbar maintains active presence in the research community with 19 total publications showing accelerating output in recent years (6 in 2021, 2 in 2022, 5 in 2023, and 2 in 2024). His Google Scholar profile reflects substantial impact with an h-index of 14 and i10-index of 16. As an educator and researcher, Dr. Akbar brings both academic rigor and industry experience to his role. His technical expertise spans the full stack of modern computing systems, from frontend development (HTML, CSS, Angular, React) through backend frameworks (Flask, Django, Node.js) to database systems (MySQL, PostgreSQL, MongoDB) and cloud infrastructure (AWS, Kubernetes, Docker). This comprehensive skill set enables him to bridge theoretical research with practical implementation. He leads research initiatives through the AWKUM AI Lab and AWKUM Robotics, providing students with opportunities to engage in cutting-edge projects that combine theoretical foundations with real-world applications. His GitHub activity shows ongoing engagement with AI and systems development projects, including repositories focused on neural networks, Python programming, and network simulation.

Alice Evelyn Mateus MartinsView profile

Research Fellow

• Computer Vision
• Deep Learning
• Robotics
• +3 more

Alice Evelyn Mateus Martins is a PhD Fellow in the Department of Architecture, Design and Media Technology at Aalborg University's Faculty of IT and Design, specializing in visual analysis and perception for robotic systems. Education Master of Science in Robotics (2019–2021): Thesis on 3D Volumetric and Semantic Reconstruction of a Robotic Workspace Using Deep Learning Bachelor of Science in Robotics (2016–2019): Thesis on Little Helper 7+: Disassembly of Mobile Phones Her research integrates computer vision and deep learning to solve robotic perception challenges, evidenced by her focus on 3D workspace reconstruction and semantic segmentation. This work bridges academic theory with industrial applications through her dual expertise in robotic disassembly systems and real-time vision processing. Professional Experience Machine Vision Engineer at Aivero A/S (Jan 2022–Jul 2024) Backend Software Developer at OnRobot A/S (Jul 2021–Dec 2021) Computer Vision Student Worker at OnRobot A/S (Nov 2019–Jul 2021)

Daniela MarghituView profile

Professor

• STEM Education
• Inclusive Computing
• Assistive Technology
• +7 more

Daniela Marghitu is a Professor in the Department of Computer Science and Software Engineering at Auburn University's Samuel Ginn College of Engineering, where she has been a faculty member since 1996. Her work bridges computing, education, and accessibility, with a strong commitment to equity and inclusion. She is based in Auburn, Alabama, and actively contributes to both academic and national initiatives focused on broadening participation in STEM. B.S. in Automation and Computing, Polytechnic University of Bucharest Ph.D. in Automation and Computing, University of Craiova Dr. Marghitu’s research centers on inclusive computing , assistive technology , and STEM education , particularly for K–12 students, underserved communities, women, and people with disabilities. Her teaching spans web development, software engineering, and accessible computing. She has led and co-led numerous NSF-funded projects aimed at increasing access and equity in computer science education. The recent publications reflect a strong focus on accessible curriculum design , values-driven engineering education , and community-based STEM outreach . Themes include inclusive pedagogy, assistive technologies, and project-based learning, especially in rural and underrepresented settings. Her work consistently emphasizes usability, accessibility, and social impact across computing disciplines. Among her notable honors are: 2011 AccessComputing Capacity Building Award 2012 Auburn University Access Award 2012 Society for Design and Process Science Outstanding Achievement Award 2013 Microsoft Fuse Research Award 2015 DO-IT Trailblazer Award 2017 International Academy, Research, and Industry Association Fellowship 2017 Society for Design and Process Science Fellowship 2019 Samuel Ginn College of Engineering 100+ Women Strong Leadership in Diversity Faculty Award Dr. Marghitu has mentored over 50 K–12, undergraduate, and graduate students, with a focus on diversity and inclusion. She has secured significant research funding from the National Science Foundation (NSF) , ACM SIGCSE , AccessComputing Alliance , Microsoft Fuse Research , and other organizations. Her leadership extends to national advisory roles, including the NSF Committee on Equal Opportunities in Science and Engineering and the CSforAll Accessibility Board. She founded and directs the Auburn University Laboratory for Education and Assistive Technology , a hub for research and development in inclusive computing and educational technologies. She also plays key administrative roles at Auburn, such as Faculty Representative to the Board of Trustees and chair of the Persons with Disabilities Committee.

• Electronics Engineering
• Metrology
• Detector Systems
• +3 more

Anna Kozioł is a Lecturer at the Department of Metrology and Electronics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków. She holds a PhD and Eng. degree and is based in room 203, building B-1, with contact via email ankoziol@agh.edu.pl or phone +48 12 617 32 99. Her research centers on electronics and metrology for scientific instrumentation, specializing in high-speed detector systems for synchrotron radiation and X-ray applications. Key domains include hardware accelerators for neural networks, photon-counting detectors, and real-time data acquisition systems, with emphasis on ultra-fast measurements and energy-discriminating capabilities. Analysis of her publications (2014-2023) reveals a cohesive research trajectory focused on hardware solutions for time-resolved experiments. Her work consistently addresses challenges in pixel array detector design, zero dead-time operation, and high-frame-rate readout systems for synchrotron facilities, demonstrating expertise from chip-level components to full camera implementations.

• Bayesian Statistics
• Category Theory
• Compiler Construction
• +4 more

Matthijs Vákár is an Assistant Professor at the Department of Information and Computing Sciences , Utrecht University , focusing on the software foundations of machine learning . He actively develops the Stan language , a state-of-the-art probabilistic programming language. Areas of Expertise: Bayesian Statistics, Category Theory, Compiler Construction, Machine Learning, Programming Languages. Research Themes: Probabilistic programming languages, differential programming languages, separation of modeling from algorithmic tasks, automatic differentiation in ML-family languages. His research bridges theoretical computer science and practical machine learning, emphasizing logical relations, monoidal structures, and efficient compiler designs for differentiable programming. His recent publications explore correctness proofs, category-theoretic models, and optimization techniques in automatic differentiation. Scientific Awards: ERC Starting Grant NWO Veni Fellowship Marie Sklodowska-Curie Fellowship Academic Journey: PhD from the University of Oxford (dependent types and computational effects), MSc in Pure Mathematics (University of Cambridge), and BScs in Mathematics and Physics (Utrecht University). Prior roles include postdoctoral research at Columbia University and the University of Oxford. Industrial Experience: Build systems at Microsoft Research, NLP at Linguamatics, and compiler design for Stan.