جست‌وجوی استاد و پژوهشگر

Tommaso Calarcoمشاهده پروفایل

استاد

• Quantum Optimal Control
• Quantum Computing
• Quantum Technologies
• +۳ مورد دیگر

Tommaso Calarco serves as Director of the Institute for Quantum Control (PGI-8) at Jülich Research Centre, leading cutting-edge research in quantum optimal control methodologies for next-generation quantum technologies. His work focuses on developing transformative computational frameworks applicable to natural sciences, logistics, and high-performance computing through advanced quantum device engineering. His research spans quantum optimal control for computation and many-body systems, emphasizing physical model development, model reduction techniques, and machine learning integration for scalable quantum hardware. Key focus areas include spin-qubit optimization, diamond quantum register engineering, and error suppression in gate operations, with significant contributions to ultracold atom systems and semiconductor-based quantum platforms. Analysis of his 2024-2025 publications reveals concentrated efforts on hardware-specific challenges across multiple quantum modalities: spin shuttling fidelity in semiconductor systems, gate optimization for nitrogen-vacancy centers, and photon-spin interface engineering. This work demonstrates a unifying thread of optimal control solutions tailored to platform-specific decoherence mechanisms and scalability constraints. As Director of PGI-8 within the Peter Grünberg Institut, Calarco oversees a dedicated research team advancing quantum control theory and applications, contributing substantially to European quantum technology roadmaps including the Quantum Flagship initiative and strategic European Commission reports.

Himanshu Jainمشاهده پروفایل

استاد

• Glass Science and Technology
• Photonics
• Nanomaterials
• +۵ مورد دیگر

Dr. Himanshu Jain is the T.L. Diamond Distinguished Chair in Engineering and Applied Science and a Professor of Materials Science & Engineering at Lehigh University. He leads the International Materials Institute for New Functionality in Glass and previously directed the Institute for Functional Materials and Devices (I-FMD). His research focuses on advancing glass science through innovations in photonics, bioactive materials, crystal engineering, and laser processing. Education: D.Eng.Sc., Materials Science, Columbia University M.Tech., Indian Institute of Technology (India) M.S., Banaras Hindu University (India) B.S., Kanpur University (India) Research Interests: Laser-induced single-crystal architectures in glass Optical and electronic functionalities in glass Biomedical applications of bioactive glass (e.g., bone scaffolds) Thermal and radiation effects on glass properties Machine learning for crystal growth modeling Awards: Recipient of Otto Schott Research Prize for atomic fluctuation models Zachariasen Award for lithium transport discovery Morey Award for defining new glass science horizons Fulbright and Humboldt Fellowships Advising & Grants: Has supervised numerous students and secured grants for interdisciplinary projects. Active in collaborative initiatives like the Lehigh-NC A&T flood damage mapping partnership. Labs/Teams: Oversees Lehigh's advanced materials facilities, including Sinclair Lab 120A. Coordinates global networks for glass science education and research.

Chunming Qiaoمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Optical Networks
• Wireless Networks
• +۶ مورد دیگر

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 .

Domenico Ciuonzoمشاهده پروفایل

استادیار

• Information Fusion
• Statistical Signal Processing
• Wireless Sensor Networks
• +۹ مورد دیگر

Dr. Domenico Ciuonzo is an Assistant Professor at the University of Naples Federico II , Department of Electrical Engineering and Information Technologies. His research focuses on Information Fusion , Statistical Signal Processing , Wireless Sensor Networks , Network Analytics , Artificial Intelligence , and Wireless Communications . He actively explores applications in deep learning , encrypted traffic classification , and IoT security . His recent work emphasizes explainable AI , quantum machine learning , and class incremental learning for network intrusion detection. Over 30+ publications span topics like decision fusion in MIMO systems , mobile app traffic analysis , and cybersecurity for IoT . He is also involved in dataset development (e.g., MIRAGE-APP× ACT-2024) and algorithmic frameworks for encrypted traffic classification . Key research trends include: Optimizing holographic communication systems and reconfigurable intelligent surfaces for wireless networks Developing attack-adaptive intrusion detection systems resilient to emerging threats Advancing quantum computing applications in network monitoring and prediction His research integrates statistical signal processing with modern AI techniques , addressing challenges in data privacy , network security , and resource-constrained environments .

• Materials Science
• Corrosion Engineering
• Electrochemistry
• +۵ مورد دیگر

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.

• Cybersecurity
• Internet of Things (IoT)
• Blockchain Technology
• +۳ مورد دیگر

Yuan Liu is a faculty member affiliated with Guangzhou University's Cyberspace Institute of Advanced Technology. Their research focuses on cybersecurity, blockchain technology, federated learning, and IoT systems. They have held roles at multiple institutions, including Northeastern University (Software College) and Nanyang Technological University (PhD in Computer Engineering). Liu's work emphasizes secure communication, edge computing, and distributed systems, with contributions to protocols like blockchain-based redactable systems and quantum federated learning frameworks. They have collaborated extensively on projects addressing IoT security, smart healthcare, and privacy-preserving technologies. Key research trends include leveraging AI for enhanced security (e.g., watermarking frameworks, attack detection) and optimizing resource allocation in edge computing environments. Their publications span journals like IEEE Communications Surveys & Tutorials and conferences such as GLOBECOM.

Tom Henzingerمشاهده پروفایل

استاد

• Formal Methods
• Software Engineering
• Computer Science
• +۵ مورد دیگر

Tom Henzinger is a Professor at the Institute of Science and Technology Austria (ISTA), leading the Tom Henzinger Group. His research focuses on formal methods to enhance software quality, addressing challenges in concurrent systems, real-time and embedded systems, quantum computing, neural networks, and biochemical reaction networks. He has advised numerous PhD students and postdoctoral researchers, contributing to advancements in these fields. His work emphasizes mathematical rigor in software analysis and verification. Current projects include VAMOS (Middleware for best-effort third-party monitoring) and SPyCoDe (Semantic and Cryptographic Foundations of Security and Privacy by Compositional Design). Past projects involved model checking and runtime verification techniques. Research interests span concurrent software synthesis, quantitative modeling of reactive systems, predictability of real-time systems, and formal methods applied to quantum computation and neural networks. He is also engaged in exploring hardware-optimal solutions for quantum algorithms. Administrative Assistant Ksenja Harpprecht supports the group. Courses taught include 'Formalisms Every Computer Scientist Should Know,' focusing on logics, automata, and semantics. The group hosts regular seminars, such as the Tuesday group seminar and the Wednesday joint formal methods seminar with TU Wien's FORSYTE group.

• Electric Vehicles
• Fuzzy Logic
• Blockchain
• +۵ مورد دیگر

Shahid Hussain is an Associate Professor at King Abdullah University of Science and Technology (KAUST) in the Computer, Electrical and Mathematical Sciences and Engineering Division. His research spans multiple domains including electric vehicle infrastructure, blockchain technology, and intelligent systems for IoT applications, with a focus on practical implementations of computational intelligence techniques. Dr. Hussain's research interests include: Electric Vehicles and Smart Grid Integration Fuzzy Logic and Intelligent Decision Systems Blockchain Applications for Security and Privacy Machine Learning for IoT and Healthcare Applications Energy Management Systems Smart City Infrastructure Development His recent publications demonstrate a strong focus on applying hybrid computational approaches to solve complex engineering problems, particularly in transportation systems and healthcare applications. Dr. Hussain has published extensively in IEEE journals, with particular emphasis on innovative approaches to electric vehicle charging infrastructure, secure IoT systems, and blockchain-enabled solutions for real-world challenges. Dr. Hussain maintains active collaborations with researchers globally, particularly with Reyazur Rashid Irshad, Young-Chon Kim, and Subhasis Thakur. His work bridges theoretical advancements with practical implementations, as evidenced by his research on fuzzy integer linear programming for EV charging stations and blockchain-enabled security frameworks for medical IoT systems.

Kai Salomaaمشاهده پروفایل

استاد

• Theory of Computation
• Automata Theory
• Formal Languages
• +۵ مورد دیگر

Kai Salomaa is a Professor and Graduate Chair in the School of Computing at Queen’s University, Canada. He holds a Ph.D. from the University of Turku (1989). His research focuses on theoretical computer science, particularly automata theory, formal languages, and their applications. Key areas include descriptional complexity, cellular automata, and quantum computing innovations. Affiliations: Queen’s University, School of Computing. Education: Ph.D. in Computer Science from the University of Turku (1989). Research Interests: Prof. Salomaa explores foundational topics like automata state complexity, nondeterminism measures, and computational models. His work bridges classical theory with modern applications in quantum computing, vehicular networks, and algorithmic resource optimization. Notable contributions include studies on input-driven pushdown automata and the integration of quantum algorithms into practical systems. Publications: His recent work spans quantum-enhanced optimization (e.g., vehicle platooning), fair matching algorithms, and complexity analysis of automata. These studies emphasize innovative solutions for computational challenges in dynamic systems and distributed networks. Grants & Labs: Leads the Formal Languages and Automata Theory Research Group, actively organizing conferences like CIAA and DCFS. His work often addresses practical applications of theoretical computer science in areas like sensor networks and metaverse resource management.

Peter Bienstmanمشاهده پروفایل

استاد

• Photonics
• Neuromorphic computing
• Nanophotonics
• +۱۱ مورد دیگر

Peter Bienstman is a full professor at Ghent University, working in the Department of Information Technology (INTEC) where he has been since 1997. He is affiliated with the Photonics Research Group and also collaborates with imec. His research spans nanophotonics, neuromorphic computing, and biosensing applications. Bienstman received his electrical engineering degree from Ghent University in 1997 and completed his Ph.D. at the same institution in 2001. His doctoral work focused on "Rigorous and efficient modelling of wavelength scale photonic components." His research interests primarily revolve around nanophotonics and its applications, with specific focus areas including: Photonic Reservoir Computing for neuromorphic information processing Optical label-free biosensors based on ring resonators TE/TM biosensors for measuring conformational changes SiN biosensors operating in the visible spectrum Optical spiking neurons and neuromorphic architectures Nanophotonic information processing systems Analysis of his recent publications reveals a strong focus on advancing photonic reservoir computing for practical applications, particularly in communications signal processing and biomedical sensing. His work demonstrates how photonic systems can implement neuromorphic computing paradigms with energy efficiency advantages over traditional electronics. Recent trends show increasing integration of phase-change materials and exploration of quantum-inspired photonic computing approaches. Bienstman has received significant recognition for his work, most notably an ERC Starting Grant for the Naresco-project: "Novel paradigms for massively parallel nanophotonic information processing." This prestigious European grant supports his innovative research at the intersection of photonics and computing. As an advisor, Bienstman has supervised numerous doctoral students to completion and currently mentors a large research group with nine active PhD students and two postdoctoral researchers. His research is supported by multiple grants that enable the development of novel photonic computing architectures and biosensing platforms. The group's work bridges fundamental photonics research with practical applications in communications, healthcare, and computing. The Photonics Research Group at Ghent University, where Bienstman works, maintains state-of-the-art facilities for nanophotonic device design, fabrication, and characterization. The group collaborates extensively with imec and other international research institutions, creating a vibrant ecosystem for advancing photonic technologies from fundamental research to potential commercial applications.

• Quantum Physics
• Condensed Matter Physics
• Functional Renormalization Group Methods
• +۳ مورد دیگر

Sabine Andergassen is an Associate Professor at TU Wien, affiliated with the Machine Learning Research Group (E194-06). Her work bridges quantum physics and computational methods, focusing on strongly correlated electron systems and functional renormalization group (fRG) techniques. She collaborates across disciplines, integrating machine learning with quantum system analysis. Her research emphasizes the Hubbard model, exploring pseudogap phenomena, Mott transitions, and computational tools for lattice systems. She develops efficient fRG methods and modular code frameworks for lattice fermion simulations. Her interdisciplinary projects combine solid-state physics with information systems engineering. Key topics include quantum many-body systems, renormalization techniques, and computational physics applications. She actively contributes to conferences and publishes on topics ranging from single-boson-exchange fRG to cluster extensions in DMF²RG.

Christoph Brabecمشاهده پروفایل

استاد

• Photovoltaics
• Perovskite Solar Cells
• Organic Electronics
• +۳ مورد دیگر

Prof. Christoph Brabec is a distinguished academic and researcher at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), holding the Chair of Materials Science. He is the spokesperson of the FAU Solar Profile Center and leads the Helmholtz Institute Erlangen-Nürnberg for Renewable Energy (HI ERN). His research focuses on photovoltaic technologies, particularly perovskite and organic solar cells, emphasizing sustainability, scalability, and material innovation. He has pioneered advancements in recycling photovoltaic materials, high-throughput screening, and automation-driven material discovery. His work bridges theoretical and applied research, addressing challenges in energy efficiency, device stability, and large-scale manufacturing. Prof. Brabec’s academic achievements include election as an ordinary member of the Bavarian Academy of Sciences and Humanities (BAdW) and recognition as a Highly Cited Researcher (Web of Science Group). His contributions span over 200 publications, with recent emphasis on automated laboratories (AMADAP), machine learning applications, and achieving world-record efficiencies in organic photovoltaic modules. Collaborations with global institutions, such as the City University of Hong Kong and Jinan University, underscore his international impact. His research group actively explores novel materials and processes, including recyclable solar cell designs, inkjet-printing on 3D objects, and light management systems. He emphasizes interdisciplinary approaches, combining materials science, computational modeling, and engineering to drive renewable energy innovation. Current projects target cradle-to-cradle recycling frameworks and scalable production methods for terawatt-scale photovoltaics.

Michael Fowlerمشاهده پروفایل

استاد

• Electrochemical Power Sources
• Fuel Cell Reliability
• Battery Degradation Analysis
• +۶ مورد دیگر

Michael Fowler is a Professor in the Department of Chemical Engineering at the University of Waterloo, cross-appointed to the Department of Mechanical and Mechatronics Engineering. His research focuses on electrochemical power systems, including battery degradation analysis, fuel cell reliability, and clean energy hubs. He leads projects like ChallengeX and EcoCar, developing fuel cell and hybrid vehicles. He teaches CHE 331 (Electrochemical Engineering) and actively supervises graduate students. His work integrates hydrogen economy concepts, renewable energy incentives, and Power-to-Gas energy storage. Key interests span polymer science, interfacial phenomena, and battery thermal management systems. Education: Ph.D. in Chemical and Materials Engineering (2003, Royal Military College of Canada), M.Sc. in Engineering Chemistry (1988, Queen's University), B.Sc. in Fuels and Materials Engineering (1986, Royal Military College of Canada). Research emphasizes modeling fuel cells, battery performance, and electrolyte materials. Recent articles explore lithium-ion battery diagnostics, aluminum-air batteries, and thermal runaway prevention. He collaborates with industries on sustainable energy solutions and advises student teams in green energy systems. His lab focuses on advanced materials for electrochemical systems and energy storage innovations. Current roles include co-faculty supervisor of vehicle design teams and director of the Waterloo Fuel Cell Research Network. He welcomes graduate applications and is involved in developing Canada’s hydrogen transition strategies. His work bridges academic research with practical applications in automotive, renewable energy, and material science sectors.

• Quantum Computing
• Edge Computing
• Distributed Systems
• +۲ مورد دیگر

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

Swastik Karمشاهده پروفایل

استاد

• Nanophysics
• Materials Science
• Quantum Materials
• +۳ مورد دیگر

Swastik Kar is a Professor of Physics at Northeastern University, specializing in experimental nanophysics and materials science. His research focuses on the electronic, optical, and electrochemical properties of graphene and 2D quantum materials, with applications in energy storage, sensing, and quantum technologies. He holds a BS from Presidency College, MS and PhD from the Indian Institute of Science, followed by postdoctoral research at Universität Karlsruhe and Rensselaer Polytechnic Institute. His academic journey includes roles as Assistant Professor (2010–2016) and Associate Professor (2016–2023) before becoming a full Professor in 2023. His work bridges experimental physics with advanced fabrication techniques, emphasizing scalable synthesis and characterization of atomically thin materials. Research interests span 2D heterostructures, quantum materials manufacturing, and AI-driven materials discovery. Key projects include the Laboratory for 2D Quantum Materials (2DQM) and the Experiential Quantum Advancement Laboratories (EQUAL), focusing on quantum materials and sensing technologies. Collaborative efforts with industry and academia aim to commercialize innovations like radiation detectors and color-recognition systems. Publications highlight advancements in moiré physics, defect engineering, and optoelectronic devices. His work on graphene-based sensors and nanomaterial color identification systems has been widely recognized. Grants include an NSF award for radiation detector development and TIER 1 funding for interdisciplinary quantum initiatives. Labs and affiliations include the Northeastern Center for Renewable Energy Technology and the Quantum Materials and Sensing Institute (QMSI), where he serves as Deputy Director. His research integrates computational modeling, machine learning, and advanced characterization to accelerate quantum material commercialization.