جست‌وجوی استاد و پژوهشگر

• Quantum Optics
• Quantum Information Science
• Quantum Imaging
• +۳ مورد دیگر

Prof. Juan P. Torres is a Professor at ICFO (Institut de Ciències Fotòniques) leading the Quantum Engineering of Light research group. His work focuses on generating and tailoring novel forms of classical and quantum light for fundamental quantum theory exploration and applications in secure communications, high-resolution imaging, and precision probing. His research centers on quantum optics and photonics with specialized expertise in spatial and frequency engineering of photons. He pioneers techniques for tailoring spatial entanglement through spontaneous parametric down-conversion schemes, enabling the generation of qudits with on-demand properties. His group actively develops quantum imaging methods using undetected light and explores high-dimensional quantum information processing. Analysis of his recent publications reveals dominant trends in quantum imaging with undetected photons, high-dimensional quantum teleportation, and decoherence-assisted quantum key distribution. His work consistently bridges theoretical quantum mechanics with practical implementations in optical coherence tomography and quantum communication protocols, emphasizing spatial mode manipulation. Prof. Torres maintains active international collaborations with leading researchers including Prof. Bahaa Saleh (CREOL), Prof. Malvin Teich (Boston University), Dr. Fabio Sciarrino (University of Rome), Prof. J. H. Eberly (University of Rochester), and Dr. Alfred U'Ren (UNAM). His laboratory features two fully equipped optical facilities with four optical tables, multiple laser systems across wavelengths, single-photon detectors, nonlinear crystals, and advanced spectroscopy equipment for quantum light generation and characterization.

• Fluid Mechanics
• Computational Fluid Dynamics
• Multiphase Flows
• +۶ مورد دیگر

Dr Sergii Veremieiev is an Associate Professor in the Department of Engineering at Durham University. His research focuses on fluid mechanics modeling, particularly in free-surface and multiphase flows, capillary phenomena, and computational fluid dynamics. He holds a PhD in Mechanical Engineering from the University of Leeds and has held academic positions at Liverpool John Moores University and Durham University since 2013. Education: Bachelor of Physics, Donetsk National University (2006) Master of Physics, Donetsk National University (2007) PhD in Mechanical Engineering, University of Leeds (2011) Research Interests: Dr Veremieiev’s work integrates computational and experimental approaches to study complex fluid dynamics phenomena, including droplet impact dynamics, rivulet instabilities, and high-performance numerical simulations using finite element and finite volume methods. His research addresses challenges in renewable energy systems, agricultural pesticide applications, and industrial flow optimization. Teaching: He teaches modules in fluid mechanics, nuclear engineering, and computational fluid dynamics (CFD) analysis at both undergraduate and postgraduate levels, including coursework in thermal renewables and design practicum. Advising & Grants: Supervised 4 completed PhD students and currently guides 5 active researchers. Develops numerical tools such as a C++/MPI free-surface solver and MATLAB subroutines for fluid dynamics analysis.

• Combinatorial computing
• Ramsey theory
• Graph theory
• +۳ مورد دیگر

Stanislaw Radziszowski is a Professor in the Department of Computer Science at Rochester Institute of Technology's Golisano College of Computing and Information Sciences. He has been at RIT since 1984, after working at the National Autonomous University of Mexico from 1980-1984. His academic career includes multiple visiting positions at the Australian National University in the 1990s and ongoing collaborations with institutions in Poland. Radziszowski earned his Ph.D. in Mathematics and Computer Science from the University of Warsaw in 1980, advised by Antoni Kreczmar and Andrzej Salwicki. His educational background includes BS and MS degrees from the same institution. Dr. Radziszowski's primary research focuses on combinatorial computing, with special emphasis on Ramsey theory and computational design theory. His "Small Ramsey Numbers" survey has become a standard reference in the field. More recently, he has expanded into applied cryptography, particularly post-quantum cryptography, leading to collaborations with the Computer Engineering Department. His work often combines theoretical insights with practical computational approaches to solve classical problems in combinatorics and graph theory. His recent publications demonstrate a growing focus on cryptographic applications, including post-quantum cryptography education, analysis of the MK-3 Authenticated Encryption Algorithm, and homomorphic encryption implementations. These works reflect his ability to bridge theoretical mathematics with practical security applications, particularly in hardware implementations and side-channel resistance. Dr. Radziszowski has made significant contributions to Ramsey theory, most notably computing R(4,5)=25 with Brendan McKay and improving bounds for R(5,5) and R(4,6). His survey "Small Ramsey Numbers" is a regularly updated reference in the field. He has also contributed to computational design theory, proving nonexistence of certain block designs. As an educator, Radziszowski teaches theory-oriented courses including Introduction to Cryptography, Foundations of Cryptography, and Quantum-Resistant Cryptography. He has developed specialized courses on combinatorial computing and has supervised numerous MS theses and projects. His recent work on post-quantum cryptography has led to educational initiatives in this emerging field. Dr. Radziszowski maintains active research collaborations, particularly with Xiaodong Xu on Ramsey and Folkman problems, and with Marcin Lukowiak on cryptographic implementations. His work often bridges the gap between theoretical mathematics and practical computing applications.

• Wireless Communications
• MIMO Systems
• Neuromorphic Computing
• +۴ مورد دیگر

Dr. Juan Carlos De Luna Ducoing is a Research Fellow at the University of Surrey, specializing in advanced wireless communication systems with a focus on MIMO (Multiple-Input Multiple-Output) technologies. His work integrates neuromorphic computing, quantum annealing, and non-linear processing to enhance the efficiency and scalability of next-generation wireless networks. Research Interests: MU-MIMO detection and precoding Neuromorphic computing applications Quantum computing in wireless systems 6G network architectures Non-linear signal processing Hardware-software co-design (e.g., SWORD platform) Key Publications: His recent work includes NeuroMIMO (2024), which explores neuromorphic principles for power-efficient MU-MIMO detection, and Scalable MU-MIMO User Scheduling (2023), addressing resource allocation in dense networks. He also contributed to quantum annealing-based detection (2022) and Gyre Precoding (2021), achieving significant SNR gains. Collaborations: Works closely with Konstantinos Nikitopoulos and the SWORD research team to develop open-source platforms for rapid prototyping of advanced communication systems.

Alex Alvaradoمشاهده پروفایل

استاد

• Optical Communications
• Wireless Communications
• Information Theory
• +۳ مورد دیگر

Alex Alvarado is a Full Professor in the Signal Processing Systems department at Eindhoven University of Technology (TU/e), leading the Information and Communication Theory Lab (ICT Lab). He is also affiliated with TU/e's Center for Wireless Technology in Eindhoven. His academic career includes roles as a Senior Research Associate at University College London (2014–2016), Marie Curie Intra-European Fellow (2012–2014), and Newton International Fellow (2011–2012) at the University of Cambridge. Alvarado is a Senior Member of the IEEE and has held editorial and committee positions in major conferences like OFC and ECOC. Alvarado holds an Electronics Engineer degree (2003) and MSc (2005) from Universidad Técnica Federico Santa María, Chile, followed by a Licentiate of Engineering (2008) and PhD (2011) from Chalmers University of Technology, Sweden. His research focuses on high-speed secure data transmission in optical and wireless systems, emphasizing energy-efficient algorithms and theoretical limits of telecommunication systems. Key areas include communication theory, information theory, optical fiber systems, and nonlinear interference mitigation. His recent articles explore advanced modulation formats, machine learning applications for channel estimation and decoding, and innovations in free-space optics and MIMO systems. This work contributes to UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and responsible consumption through energy-efficient communication solutions. Scientific Awards: ERC Starting Grant (2018) NWO VIDI Grant (2016) 2015 Journal of Lightwave Technology Best Paper Award 2015 IEEE Exemplary Reviewer Award 2018 and 2023 Asia Communications and Photonics Conference Best Paper Awards 2019 Optoelectronics and Communications Conference Best Paper Award Alvarado's advising contributions include supervising 12 research works. His grants include NWO VIDI and ERC Starting funding. He leads projects like NESTOR (Next-gen optical networks) and LaiQa (Quantum Key Distribution). His lab, the ICT Lab, drives theoretical and applied research in communication systems.

• Microwave Engineering
• RF Systems Design
• Power Amplifier Design
• +۷ مورد دیگر

Christian Fager is a Full Professor at the Department of Microwave Electronics, Chalmers University of Technology, Sweden. He has been affiliated with Chalmers since completing his Ph.D. there in 2003. As Head of the Microwave Electronics Laboratory, his research focuses on nonlinear transistor modeling, energy-efficient power amplifier architectures, and distributed MIMO systems. He has co-invented 8 patents and published over 250 papers, including a seminal book on Nonlinear Transistor Model Parameter Extraction Techniques (Cambridge University Press, 2011). Dr. Fager holds editorial roles as Associate Editor of IEEE Microwave Magazine and member of the MTT-S Technical Coordination Committee on Wireless Communications. He is a Board Member of the European Microwave Association (EuMA) and has chaired multiple IEEE topical conferences. His awards include the Chalmers Supervisor of the Year (2018), inaugural Area of Advance Award (2010), and IEEE IMS Best Student Paper (2002). He leads research initiatives in distributed antenna systems, digital pre-distortion, and GaN/SiGe-based high-efficiency amplifiers, with projects involving testbed development for 5G/6G applications. His work bridges theoretical modeling and practical implementation in RF/microwave systems, emphasizing thermal and multi-physical simulation integration.

Piya Palمشاهده پروفایل

استاد

• High Dimensional Statistical Signal Processing
• Compressive Sensing
• Tensor Methods
• +۴ مورد دیگر

Prof. Piya Pal is a Professor in the Department of Electrical and Computer Engineering at the University of California, San Diego. Her research focuses on high-dimensional statistical signal processing, energy-efficient sampling techniques, and covariance-driven inference. She previously held an Assistant Professor position at the University of Maryland, College Park, and was affiliated with the Institute for Systems Research. Education: Ph.D. in Electrical Engineering from California Institute of Technology (2013). Notable achievements include the NSF CAREER Award (2016) and the 2014 Charles and Ellen Wilts Prize for her thesis on sparse sampling and estimation. Her work emphasizes structured sampling and robust algorithms for undersampled data analysis, with applications in sensor arrays, compressive sensing, and optical imaging. Research Interests: Energy-efficient sparse array design Correlation-aware sparse estimation Covariance compression and statistical inference Tensor methods in machine learning High-resolution imaging systems Publications highlight advancements in sparse array geometries (nested/coprime samplers), Cramér-Rao bound analysis, and hybrid beamforming. Recent work explores super-resolution imaging and millimeter-wave channel sensing with learned empirical priors. Her contributions address fundamental trade-offs between sample size, resolution, and domain knowledge integration. Scientific Awards: NSF CAREER Award (2016) 2014 Charles and Ellen Wilts Prize (Caltech) Advising & Grants: Current research is supported by NSF CAREER funding. Her lab focuses on interdisciplinary projects combining signal processing with medical imaging and wireless communication challenges.

Georgios Portokalidisمشاهده پروفایل

استاد پژوهشی

• Systems Security
• Binary Analysis
• Software Hardening
• +۱ مورد دیگر

Georgios Portokalidis is an Associate Research Professor at IMDEA Software Institute and Visiting Research Professor at Stevens Institute of Technology. He leads research in software systems security with focus on binary analysis, software hardening, and operating system security. His research develops practical defenses against software vulnerabilities through techniques like binary debloating, system call filtering, and hardware-assisted security. Current projects explore Rust language security, processor-assisted protection mechanisms, and vulnerability mitigation through code reduction. Publication trends show evolution from foundational binary analysis to applied security hardening, with recent emphasis on Rust security, hardware-assisted defenses, and real-world system protection. Work demonstrates consistent focus on practical, deployable security solutions. He has supervised numerous PhD students and postdocs, currently mentoring researchers at IMDEA. His group investigates binary analysis, software debloating, and system hardening techniques. Major grants include DARPA YFA (2021-2023) and ONR funding (2017-2022) supporting adaptive binary debloating research. Leads the systems security research group at IMDEA Software Institute, collaborating with international partners. Maintains active research partnerships and regularly contributes to top security conferences as program committee member.

Yaguang Zhangمشاهده پروفایل

استادیار بالینی

• Data Science
• Digital Agriculture
• UAV-Aided Wireless Communication Systems
• +۴ مورد دیگر

Dr. Yaguang Zhang is a Clinical Assistant Professor at Purdue University, jointly appointed in the Department of Agricultural & Biological Engineering (ABE) and the Department of Agricultural Sciences Education & Communication (ASEC) . Holding a Ph.D. in Electrical and Computer Engineering from Purdue (2021), he specializes in data science , digital agriculture , and UAV-aided wireless communication systems , with applications in intelligent transportation, proactive road maintenance, and engineering education. Education: Ph.D. and M.Sc. in Electrical and Computer Engineering (Purdue), B.Eng. in Communication Engineering (Tianjin University) Research Interests span cutting-edge domains including: Digital Agriculture: GPS-based field shape generation, product traceability trees, and automated metadata collection for agricultural operations Wireless Communication: Millimeter-wave channel modeling, UAV relay systems, and rural network coverage optimization Smart Infrastructure: Pavement condition assessment tools, sun-shadow simulation for road treatment, and vehicle automation platforms Recent Publications emphasize scalable solutions for agricultural IoT, machine learning in crop monitoring, and interoperable data frameworks. His scientific awards include: 2024 Outstanding Engineering Teacher (Purdue) 2024 ASABE Superior Paper Award 2020 FFAR Student Poster First Prize Multiple NSF/IEEE travel supports Grants from USDA, NSF, INDOT, and industry partners (CableLabs, Nokia) fund projects like tractor autopilot development, rural 6G networks, and pavement monitoring systems. He mentors graduate students in agricultural robotics , data science , and connected vehicle research .

Neil Bergmannمشاهده پروفایل

استاد

• Wireless Sensor Networks
• Internet of Things (IoT)
• Embedded Systems
• +۶ مورد دیگر

Neil Bergmann is an Honorary Professor at the School of Electrical Engineering & Computer Science, University of Queensland. His research focuses on wireless sensor networks, IoT, embedded systems, and machine learning with applications in cybersecurity, energy efficiency, and industrial monitoring. He has contributed extensively to fields like cryptographic acceleration, localization systems, and sensor network optimization. His work bridges hardware-software co-design and practical implementations in domains such as healthcare and industrial automation. His academic career includes significant contributions to journals and conferences, with a focus on advancing technologies like energy harvesting, real-time data processing, and secure communication protocols. Collaborations span academia and industry, addressing challenges in sensor networks, embedded systems, and smart environments. Notable research includes energy-efficient machine fault diagnosis using industrial wireless sensor networks and secure authentication systems leveraging kinetic energy harvesting. His publications highlight interdisciplinary approaches to solving complex technical problems, emphasizing practical applicability and innovation.

Danel Draguljicمشاهده پروفایل

دانشیار

• Statistics
• Experimental Design
• Probability
• +۳ مورد دیگر

Danel Draguljic is an Associate Professor of Mathematics at Franklin & Marshall College in Lancaster, PA, where he has held this position since 2018, following a tenure as Assistant Professor from 2012–2018. Prior to academia, he worked as a Statistician III at Battelle Memorial Institute (2010–2012). He holds a Ph.D. in Statistics from The Ohio State University (2010), alongside dual undergraduate degrees in Philosophy and Mathematics from Millersville University (2003). Teaching focuses on advanced statistical courses like Design and Analysis of Experiments, Neural Networks, and Time Series. Co-authored the textbook Design and Analysis of Experiments (2017, Springer), emphasizing R and SAS applications. His research intersects statistical methodology, experimental design, and interdisciplinary applications in biology, neuroscience, and environmental science. Notable contributions include optimizing thin film coatings, modeling neural networks, and analyzing drought impacts on tropical epiphytes. Key awards include the 2015 Youden Award for the 2014 paper on screening strategies in Technometrics. Ongoing projects involve variable selection in mixed models and constrained noncollapsing design algorithms (CoNcaD).

Matthias Meckelمشاهده پروفایل

مدرس ارشد

• e-Business Strategies
• Small and Medium Enterprises (SMEs)
• Online Consumer Behavior
• +۳ مورد دیگر

Dr. Matthias Meckel is a Senior Lecturer in the School of Business, Social & Decision Sciences at Constructor University. Previously, he held academic positions at the University of Central Lancashire, including Principal Lecturer (2020-2023), Senior Lecturer (2007-2020), and Lecturer (2004-2007). His research focuses on e-business strategies for SMEs, organizational technology adoption barriers, and survey methodology. He holds a PhD in e-business strategies for SMEs from the University of Central Lancashire, alongside an MSc in Business Administration with IT (Distinction) and a Diplom-Informatiker (FH) degree. His research interests include digital transformation frameworks for SMEs, healthcare information systems, and cross-channel survey techniques. Notable work includes developing a hospital resource management system using real-time data and analyzing organizational barriers in e-Banking adoption. His publications span journals like Strategic Change and conferences such as the International Conference on Systems and Informatics. Teaching expertise spans business management, information systems, and technology strategy. He has advised numerous projects on SME digitalization and contributed to academic events globally. Currently based at Constructor University's Bremen campus, he continues advancing knowledge in business innovation and technology adoption.

• Materials Science
• Composite Materials
• Metals
• +۳ مورد دیگر

António Manuel de Bastos Pereira is a Full Professor at the Department of Mechanical Engineering, University of Aveiro, Portugal. He has held significant leadership roles including Director of the Master's program in Welding Engineering and Director of the Research Unit Centre for Mechanical Technology and Automation (TEMA) from 2015 to 2024. Under his leadership, TEMA was classified with the highest rating by FCT and included in the European network of Key Enabling Technologies institutions. Dr. Pereira's research focuses on materials science, particularly the study of materials from composites to metals. His work spans advanced manufacturing technologies, surface engineering, and mechanical characterization of materials. He has published 97 articles in SCI journals with 2140 citations and an h-index of 29 (Scopus), demonstrating significant impact in his field. His research has led to the development of over 500 industrial projects worth approximately 100 million euros. His recent publications reveal consistent research trends in materials characterization, advanced manufacturing processes, and sustainable engineering solutions. Key themes include laser processing of materials, welding technologies, composite materials, surface treatments, and thermal engineering applications. His work often combines experimental and numerical approaches to solve practical engineering challenges, with growing emphasis on sustainable manufacturing methods and energy efficiency. Dr. Pereira has supervised numerous graduate students across various mechanical engineering topics, particularly in welding, materials processing, and mechanical design. He has been Principal Investigator for 39 scientific research projects and collaborated in 68 projects total, securing significant research funding. His project portfolio includes national and European initiatives focused on sustainable manufacturing, advanced materials, and innovative industrial processes. As Director of TEMA, he coordinated over 100 researchers within the Research Unit Centre for Mechanical Technology and Automation. TEMA is included in the "Portuguese Roadmap of Research Infrastructures of Strategic Relevance" and was selected to be part of the European network of institutions relevant within Key Enabling Technologies (KETs). Dr. Pereira also coordinated the thematic line "Innovative and Sustainable Industries" of LASI, Portugal's largest associated laboratory with around 500 PhD researchers. His leadership has positioned these research units as key players in technology transfer to small and medium enterprises across Portugal.

José PICHERALمشاهده پروفایل

استاد

• Signal Processing
• Acoustic Imaging
• Array Processing
• +۵ مورد دیگر

José Picheral is a Professor at CentraleSupélec, affiliated with the Laboratory of Signals and Systems (L2S). He holds a PhD (2003) and HDR (2017) in high-resolution signal processing methods and inverse problems. His research focuses on array processing, source localization, acoustic imaging, and vibration analysis, with applications in aeroacoustics, automotive systems, and industrial monitoring. He has supervised multiple PhD students and contributed to projects like Valeo’s smartphone-based car key replacement system. Education: Engineering Degree: Supélec (1999) and Politecnico di Milano (1999, Erasmus-TIME) PhD: Paris Sud University (2003) Habilitation (HDR): Université Paris Sud (2017) Research Interests: High-resolution methods for distributed sources, sparse signal processing, acoustic imaging, asynchronous measurements, and sensor array design. Current projects include spatial source covariance estimation, EEG spectrum analysis, and automotive applications using smartphone localization. Key Contributions: Over 50 publications in top journals/conferences (e.g., IEEE Transactions, ICASSP). Notable work on MUSIC algorithm robustness, DAMAS optimization, and sparse approaches for tip-timing signals. Advising & Collaboration: Supervised 7 PhD students. Collaborations with SAFRAN, Valeo, and academic teams in Bayesian inference and inverse problems. Active in L2S’s Inverse Problems Group and SYCOMORE team. Labs/Teams: Member of L2S’s Signal Processing and Statistics group, leading research in systems and control, telecommunications, and energy systems.

• Artificial Intelligence
• Machine Learning
• Spatial Reasoning
• +۳ مورد دیگر

Dr. Paulo Santos is a Senior Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence with a focus on explainable AI systems. He holds a PhD from Imperial College London (2003) and has over 20 years of research experience in spatial reasoning, machine learning, and robotics. His work bridges knowledge representation with deep learning to enhance transparency in AI decision-making. Dr. Santos has led research groups in Brazil, collaborated internationally, and secured funding from organizations like the British Council and EU. His expertise spans robotics, computer vision, and cognitive science. Notable achievements include the British Computer Science Machine Intelligence Prize (2004) and the Santander Prize for Science and Innovation (2006). Research interests include reinforcement learning for autonomous underwater vehicles (AUVs), scene graph generation in computer vision, and spatial reasoning for multi-robot systems. Recent work emphasizes sim-to-real transfer learning and fault recovery in underwater robotics.