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Stefan TaiView profile

Professor

• Distributed Systems
• Decentralized Architectures
• Data Management
• +6 more

Prof. Stefan Tai is a full professor and Chair of Information Systems Engineering at Technische Universität Berlin (Germany) since 2014. Previously, he held a full professorship at Karlsruhe Institute of Technology (KIT) and worked as a Research Staff Member at IBM's Thomas J. Watson Research Center. His research focuses on distributed systems, decentralized architectures, cloud service engineering, and privacy-preserving blockchain systems, emphasizing off-chain solutions and scalable technologies. Tai's work bridges academic research with industry applications, particularly in serverless computing, energy-efficient cloud-native systems, and blockchain-based solutions for supply chains and energy grids. He has authored numerous peer-reviewed publications in top-tier conferences and journals, including IEEE ICSA, Future Generation Computer Systems, and IEEE Blockchain. His contributions address challenges in software systems engineering, federated learning, and sustainable computing. Research Interests: Next-generation distributed software systems Decentralized architectures and blockchain systems Cloud and serverless computing Energy-efficient design Data management and privacy-preserving technologies Smart energy grids and IoT integration Key Publications Trends: Tai's recent work explores the intersection of blockchain and federated learning, serverless architectures for big data, and energy-efficient cloud-native applications. His 2025 paper introduced a framework for optimizing cloud-native energy efficiency, while 2024 contributions advanced verifiable decentralized systems and serverless data processing. Earlier research (2020–2021) focused on privacy in local energy grids and serverless computing scalability. Grants & Labs: While specific grants are not detailed, his leadership in TU Berlin's Information Systems Engineering group indicates involvement in EU-funded or industrial projects. Collaborations with institutions like TU Wien and KIT suggest multi-institutional efforts in distributed systems and blockchain. Labs/Teams: Leads the Information Systems Engineering research group at TU Berlin, focusing on software systems engineering, cloud architectures, and blockchain applications.

Björn AnnighöferView profile

Professor

• Avionics Systems
• Self-Adaptive Systems
• Cybersecurity
• +5 more

Björn Annighöfer is a Professor at the Institute of Aviation Systems (ILS) at the University of Stuttgart, where he serves as Managing Director. His work focuses on complex, digital, and safety-critical avionics systems, including self-adaptive platforms, cybersecurity, and AI-supported aerospace systems. Research interests include: Self-adaptive avionics platforms Model-based cybersecurity frameworks Integrated Modular Avionics (IMA) development Virtualization and middleware for safety-critical systems AI applications in aerospace Automated development and certification processes Recent publications highlight advancements in PLUG-AND-FLY avionics, security assessment using large language models, and domain-specific modeling tools. He leads a team of ~25 scientists at ILS, which operates modern labs, flight simulators, and research aircraft for testing.

Frauke LiersView profile

Professor

• Optimization under Uncertainty
• Distributionally Robust Optimization
• Quantum Computing
• +5 more

Prof. Dr. Frauke Liers holds the Professorship of Optimization under Uncertainty & Data Analysis at the Department of Data Science (DDS), Friedrich-Alexander-University Erlangen-Nürnberg. Her research focuses on robust and distributionally robust optimization, mathematical programming, and applications in energy systems, healthcare logistics, and quantum computing. Email: frauke.liers@fau.de ResearchGate: Frauke Liers Research Interests span optimization under uncertainty, data-driven mathematical programming, and interdisciplinary applications. Key areas include: Distributionally robust optimization with scenario reduction and chance constraints Quantum computing optimization for gate routing and noise suppression Energy system modeling (photovoltaics, gas networks, electricity networks) Healthcare logistics (patient transport scheduling under uncertainty) Nanoparticle technology and chemical process optimization Recent Publications emphasize: Advancements in quantum circuit optimization (2025) Explainable optimization methods (2024) Robust approaches for particle precipitation control (2024) Dynamic trajectory optimization (2023) Time-expanded models for network flows (2022)

Jürgen BrehmView profile

Adjunct Professor

• Computer Architecture
• Parallel Processing
• E-Learning
• +6 more

Jürgen Brehm is an Adjunct Professor at the Faculty of Electrical Engineering and Computer Science of Leibniz University Hannover . He holds a venia legendi in Computer Engineering after completing his habilitation in 2000. Education: Diploma in Computer Science (1986), Doctorate in Engineering (1991), Habilitation (2000) Research interests span computer architecture , parallel processing , performance analysis , and e-learning . His work explores ubiquitous computing , communication architectures , and optimization algorithms . Recent publications highlight trends in parallel computing , optimization , and interactive systems , including works on swarm intelligence , particle swarm optimization , and open content integration. Scientific award : Feodor Lynen Fellowship (1994) Teaching includes core courses like Basics of Computer Architecture , Operating Systems , and Parallel Processing . He also designed two multimedia-equipped computer science lecture halls and managed large-scale DFG projects for e-learning and HPC computing.

Andreas PolzeView profile

Professor

• Operating Systems
• Middleware
• Distributed Computing
• +9 more

Prof. Dr. Andreas Polze is a full Professor in the Operating Systems and Middleware group at the Hasso Plattner Institute (HPI) for Digital Engineering, University of Potsdam, Germany. He has held this position since October 2001 and also serves as the speaker of the HPI Research School, a PhD program in Service-Oriented Systems Engineering, since 2005. He is a member of the steering committee of the Future SOC Lab at HPI. His research focuses on the architecture of operating systems, component-based middleware, and predictable distributed and cloud computing. Current research interests include predictable service computing, adaptive system configuration, and end-to-end service availability on standard middleware platforms. He has led collaborative projects with industry and medical partners such as SAP, Deutsche Telekom, GETEMED, and Charité, including the Fontane telemedicine project and research on porting SAP HANA to new processor architectures. Andreas Polze conducted research visits at the Software Engineering Institute, Carnegie Mellon University, and the Real-Time Systems Laboratory at the University of Illinois, Urbana-Champaign. His academic background includes a PhD from Freie Universität Berlin (1994) and a habilitation from Humboldt University Berlin (2001), both in Computer Science. Scientific Awards: Fellow of DFG-graduate college "Communication-based Systems" (1991–1994) He has supervised PhD and master's students through his leadership in the HPI Research School and has been involved in multiple collaborative research grants, particularly in cloud, middleware, and telemedicine systems. He leads research in system predictability and reliability, especially in service-oriented and cloud environments. He is affiliated with the Operating Systems and Middleware group at HPI, which conducts cutting-edge research in system software, distributed systems, and middleware platforms, with strong industry partnerships and interdisciplinary applications in healthcare and enterprise computing.

• Political Philosophy
• Ethics
• International Political Theory
• +6 more

Prof. Dr. Frank Dietrich is a W3 Professor of Practical Philosophy at the Heinrich Heine University Düsseldorf since 2012. He serves as Spokesperson of ELSA-AG and Board Member of Stem Cell Network NRW , and acts as Commissioner for Students with Disabilities since 2022. His research spans political philosophy , ethics , and medical ethics , with particular focus on distributive justice , secession , and AI ethics . Education : Diploma in Social Sciences (Political Science), Gerhard Mercator University Duisburg (1994) Doctorate in Philosophy, Gerhard Mercator University Duisburg (2000) Habilitation in Philosophy, University of Leipzig (2008) Research Interests include: Political Philosophy : Territorial rights, democratic boundary problems, collective self-determination Ethics : Autonomy, parental authority, freedom of expression in digital networks Medical Ethics : Organ allocation, Xenotransplantation, disability rights Migration/Climate : Ethical implications of climate-induced migration, asylum rights Publications (selected) cover AI & Ethics , Journal of Social Philosophy , Migration and Climate Change , and Medical Resource Rationing . Scientific Awards : Fellowship at Alfried Krupp Wissenschaftskolleg Greifswald (2007/08) Board member of Stem Cell Network NRW (since 2021) Commissioner for students with disabilities (2022) Grants & Projects include DFG-funded research on Bioethics (2012/13), MLP Corporate University CFP training (2010-2020), and University of Mainz Medical Ethics program.

Christopher WiebuschView profile

Professor

• Particle Physics
• Astroparticle Physics
• Neutrino Astronomy
• +1 more

Prof. Dr. rer. nat. Christopher Wiebusch is a University Professor at the III. Physikalisches Institut B (Experimental Physics III B) at RWTH Aachen University. His research focuses on Particle and Astroparticle Physics , with active involvement in major experiments: IceCube, Double Chooz, EnEx-RANGE, and JUNO. His work spans neutrino astronomy, dark matter searches, cosmic ray anisotropy studies, and detector development.

• Signal Processing
• Machine Learning
• Artificial Intelligence
• +12 more

Arash Mohammadi is an Assistant Professor in the Department of Electrical and Computer Engineering at Concordia University, Montreal, Canada. He holds a PhD from the University of Toronto (2015) and was formerly affiliated with Amirkabir University of Technology, Iran. His research bridges signal processing, artificial intelligence, and biomedical applications. Research Interests: Signal and image processing for healthcare (e.g., lung cancer detection, ECG analysis) Machine learning for smart grids and cyber-physical systems AI in mobile edge computing and 6G networks Transformer and diffusion models for medical and motion data Federated and efficient deep learning for edge devices His recent publications (2021–2025) in top venues like IEEE TSP, ICASSP, and AAAI demonstrate a strong focus on applying cutting-edge AI—especially vision transformers, Mamba architectures, and diffusion models—to critical domains such as medical diagnostics, gesture recognition, and network security. Trends include multimodal fusion, uncertainty quantification, and efficient model design. Scientific Contributions: Developed novel frameworks like NYCTALE and MIXCAPS for lung nodule malignancy prediction Introduced CacheMamba and TEDGE-Caching for edge network optimization Advanced EMG-based gesture recognition using hybrid and transformer models Contributed to cybersecurity in smart grids via attack detection models He actively advises students and collaborates with researchers such as Konstantinos N. Plataniotis and Jamshid Abouei. He has contributed to special issues on neurorehabilitation and AI for COVID-19 diagnosis. His work often involves interdisciplinary teams and real-world applications in healthcare and smart infrastructure.

Yassine El MaazouzView profile

Lecturer

• Algebraic Geometry
• Non-Archimedean Geometry
• Commutative Algebra
• +2 more

Yassine El Maazouz is a Harry Bateman Postdoctoral Scholar in the Division of Physics, Mathematics and Astronomy at the California Institute of Technology (Caltech), with a faculty mentor appointment under Professor Matilde Marcolli. He holds instructor positions for graduate mathematics courses including MA132C (Topics in Algebraic Geometry) and MA140B (Probability). Previously, he completed his PhD in Statistics at UC Berkeley after studying pure and applied mathematics at École Polytechnique. Education: PhD in Statistics, UC Berkeley (2019-2023) Master's in Pure and Applied Mathematics, École Polytechnique (2016-2019) Research Interests: His work bridges algebraic/non-Archimedean geometry, commutative algebra, combinatorics, and mathematical physics. Primary investigations include: p-adic algebraic manifolds, isotropic vector gram matrices, tropical invariants, spinor-helicity varieties, and combinatorial probability models. Research consistently demonstrates innovative applications of algebraic methods to problems in theoretical physics and statistical mechanics. Publication Trends: Recent articles (2019-2025) show strong focus on: (1) Algebraic structures in high-energy physics (scattering amplitudes, Coulomb branches), (2) Computational methods for p-adic manifolds and tropical geometry, (3) Combinatorial probability models (Bernoulli polynomials, stochastic processes), and (4) Matrix algebras derived from valuation theory. Work frequently appears in top journals including SIAM Journal on Applied Algebra, Selecta Mathematica, and Combinatorics/PROBABILITY Computing. Awards: Harry Bateman Postdoctoral Scholarship (Simons Foundation) Teaching & Academic Service: At Caltech, teaches graduate courses in algebraic geometry and probability theory. Previously instructed statistics courses at UC Berkeley (2019-2022). Co-organizes the Information, Geometry & Physics Seminar featuring cutting-edge interdisciplinary research. Maintains extensive lecture notes on number theory, probability, and representation theory.

Christoph LenzenView profile

Professor

• Distributed Computing
• Clock Synchronization
• Randomized Load Balancing
• +5 more

Christoph Lenzen is a Professor at CISPA Helmholtz Center for Information Security since July 2021. Previously, he served as a Group Leader at the Max Planck Institute for Informatics (2014-2021), and held postdoctoral positions at MIT CSAIL (2013-2014), Weizmann Institute (2012), and Hebrew University (2011). Research Interests Design and analysis of distributed algorithms Clock synchronization and adversarial fault tolerance Randomized and self-stabilizing systems Hardware algorithms for fault-tolerant systems Grants and Awards ERC Proof-of-Concept Grant (2021) ERC Starting Grant (2017-2022) ETH Zurich Medal for Outstanding Thesis (2011) Education Ph.D. in Computer Science (2011), ETH Zurich Diploma in Mathematics (2007), University of Bonn Teaching Clock Synchronization and Adversarial Fault Tolerance (2022 winter) How To Clock Your Computer (2022 summer) Theory of Distributed Systems (2019 winter, 2020 winter, 2018 winter, 2017 winter, 2016 winter, 2015 winter)

• Microelectronics
• Circuit Design
• Analog-to-Digital Converters
• +3 more

Zhangming Zhu is a Professor at Xidian University in the School of Microelectronics . He specializes in Microelectronics and Circuit Design , with a focus on Analog-to-Digital Converters (ADCs) , CMOS Technology , and Low-Power Electronics . His work addresses challenges in high-speed, high-precision, and energy-efficient circuit design. Research Interests: His publications highlight expertise in ADCs, PLLs, energy harvesting, biomedical sensors, and RF systems. Recent Publications: 2025 papers include a 12-bit 1.5-GS/s ADC , a 5-18-GHz Quadrature Receiver , and 20-bit SAR ADC with thermal error suppression. Collaborations: Frequently co-authors with Shubin Liu, Yi Shen, Ruixue Ding, and others. Applications: Work spans consumer electronics, IoT, biomedical devices, and energy-efficient systems.

• Explainable Artificial Intelligence
• Type-2 Fuzzy Logic Systems
• Computational Intelligence
• +12 more

Hani Hagras is a Professor in the School of Computer Science and Electronic Engineering at the University of Essex, UK , where he leads pioneering research in type-2 fuzzy logic systems and explainable artificial intelligence (XAI) . His work bridges theoretical advances with real-world applications in smart infrastructure, healthcare, telecommunications, and ambient intelligence. His research interests include explainable AI, type-2 fuzzy logic, computational intelligence, machine learning, human-computer interaction, and intelligent systems. He investigates how fuzzy systems can enhance the transparency, robustness, and adaptability of AI models, particularly in uncertain and dynamic environments. His recent work explores applications in genomics, predictive maintenance, and smart grid optimization. The publication trends show a strong focus on integrating fuzzy logic with deep learning and optimization techniques to create interpretable models. His work frequently appears in top-tier journals such as IEEE Transactions on Fuzzy Systems , IEEE Transactions on Artificial Intelligence , and Neurocomputing . He emphasizes real-world applicability, often collaborating with industry partners like BT. ORCID: 0000-0002-2818-5292 He has advised numerous PhD and Master’s students, including Mehrin Kiani, Ashish Bhatia, and Hugo Leon-Garza, many of whose research projects focus on workforce optimization, healthcare AI, and intelligent systems. His research has been supported by major grants, particularly in smart environments and telecommunications. Hani Hagras is actively involved in leading research labs and teams at the University of Essex, including work on augmented reality for field service support, georeferenced data visualization , and ambient-assisted living systems. His team develops fuzzy logic frameworks for real-time decision-making in complex environments.

Qian LiView profile

Researcher

• Database Systems
• Operating Systems
• Distributed Systems
• +3 more

Qian Li is a researcher working at the intersection of database systems and operating systems, with primary affiliation at DBOS Inc. and academic connections to Stanford University's School of Engineering, Department of Computer Science, and Peking University in Beijing, China. The research focuses on developing the Database Operating System (DBOS) concept, which reimagines operating systems with database technology at their core. Research interests center on database systems, operating systems integration, transaction processing, and serverless computing. The work explores how database principles like ACID transactions can improve system reliability, debugging, and application development, particularly in cloud environments. Key projects include DBOS, Epoxy for cross-data store transactions, and Apiary for transactional serverless computing. The publication record shows a strong trend toward integrating database transaction semantics with modern computing paradigms, particularly serverless architectures. Recent work demonstrates how transactional guarantees can simplify application development, improve debugging, and enable new approaches to cloud-native application design. The research bridges theoretical database concepts with practical systems implementation. As a core contributor to the DBOS project, Qian Li has collaborated extensively with leading researchers including Michael Stonebraker, Matei Zaharia, Christos Kozyrakis, and Peter Kraft. The work has been published consistently in top-tier venues including VLDB, USENIX ATC, and CIDR, reflecting significant impact in the systems research community.

Emilija PerkovicView profile

Assistant Professor

• Causal Inference
• Graphical Models
• Probabilistic Graphical Models
• +3 more

Emilija Perkovic serves as the Dorothy Gilford Early Career Endowed Professor in Mathematical Statistics within the Department of Statistics at the University of Washington. She joined the department in Autumn 2018 as an Acting Assistant Professor and advanced to a tenure-track Assistant Professor position in Autumn 2020, establishing herself as a core faculty member in statistical methodology. Her academic foundation includes: B.Sc. in Mathematics from the University of Belgrade (2012) M.Sc. in Statistics from ETH Zürich (2014) Ph.D. in Statistics from ETH Zürich (2018) under Professor Marloes Maathuis Perkovic's research pioneers causal inference methodologies through probabilistic graphical models, focusing on intuitive frameworks for causal identification and estimation from observational data. Her work bridges theoretical statistics with practical applications, particularly in covariate adjustment techniques and Markov equivalence class analysis. She actively integrates expert knowledge to refine causal models, making complex inference accessible for real-world data challenges where experimental intervention is impossible. Her publication record reveals a concentrated evolution in causal graph theory, with recent preprints advancing adjustment criteria for diverse graph structures (MPDAGs, MAGs, ancestral graphs). Key trends include developing sound/complete identification rules, efficient estimation techniques under linearity, and minimal effect enumeration in equivalence classes—collectively enhancing robustness in observational causal analysis. Her scientific recognition includes: Best Poster Award, Semantic Statistics (SEMSTAT), Statistical Network Science Workshop (2017) While specific advising details and grant histories remain unreported in source materials, Perkovic's research trajectory indicates active mentorship through co-authored preprints with junior collaborators like Sara LaPlante and F. Richard Guo. Her Dorothy Gilford Endowed Professorship likely supports ongoing methodological innovation in causal statistics. No laboratory or team structures are explicitly referenced in her professional profile, suggesting independent or collaborator-driven research within the Statistics Department framework.

• Internet of Things (IoT)
• Fog Computing
• Digital Twins
• +3 more

Dimitrios Georgakopoulos is a researcher at Swinburne University of Technology and National Measurement Institute, focusing on Internet of Things (IoT), digital twins, fog computing, and smart manufacturing. His work bridges theoretical advancements with real-world applications in urban infrastructure, precision agriculture, and industrial IoT. Research Areas: IoT, Digital Twins, Fog Computing, Smart Cities, Precision Agriculture Key Contributions: Sensor sharing marketplaces, 5G-enabled smart city frameworks, metadata-assisted IoT data classification Recent Articles (2023-2025): Explore topics like digital manufacturing consistency, AI-powered roadside asset management, and deep learning for heterogeneous IoT data. Trends emphasize autonomic systems, sensor integration, and contextual data analysis. Collaborations: Frequently works with Prem Prakash Jayaraman, Ali Yavari, Abhik Banerjee, and Anas Dawod on IoT security, sensor networks, and time-sensitive applications.