جست‌وجوی استاد و پژوهشگر

Daler N. Rakhmatovمشاهده پروفایل

دانشیار

• Reconfigurable architectures
• Energy-efficient computing
• Electronic design automation
• +۹ مورد دیگر

Daler N. Rakhmatov is an Associate Professor in the Electrical and Computer Engineering Department at the University of Victoria . His research focuses on energy-efficient computing architectures for biomedical imaging applications, including ultrasound systems and embedded systems optimization. He is also involved in hardware/software co-design and battery management systems. Education: Bachelor of Science (BSc) in Engineering, University of Rochester Master of Science (MSc) in Engineering, University of Arizona Doctor of Philosophy (PhD) in Engineering, University of Arizona Professional Engineer (PEng) designation Research Interests: Rakhmatov's work emphasizes four core areas: 1. Low-complexity biomedical ultrasound imaging techniques for energy efficiency. 2. Configurable hardware/software architectures for computation-intensive tasks. 3. Analytical models for battery dynamics in embedded systems. 4. Model-driven configuration algorithms for energy-constrained applications. Teaching: Rakhmatov teaches courses such as ECE 242 (Discrete Structures) , ECE 355 (Microprocessor Systems) , and advanced topics like ECE 568 (System-on-Chip Engineering) . Students & Alumni: Rakhmatov supervises PhD and MASc/MEng students in biomedical imaging and embedded systems. Notable alumni include: - Hamad Alrimeih (PhD, Cryptographic Hardware Acceleration) - Mohammed Albulayli (PhD, Ultrasound Imaging Reconstruction) - Solmaz Khezerloo (MASc, Gradient-Driven Beamforming) Labs & Collaborations: His research integrates with the University of Victoria's biomedical engineering and embedded systems communities. He is a member of the Cadence University Program .

Anna-Lena Horlemannمشاهده پروفایل

دانشیار

• Algebraic Coding Theory
• Post-Quantum Cryptography
• Network Coding Theory
• +۳ مورد دیگر

Anna-Lena Horlemann is an Associate Professor for Foundations of Computation at the School of Computer Science, University of St. Gallen. Her research focuses on algebraic coding theory, post-quantum cryptography, and network coding. She leads the Coding Theory and Cryptography research group, actively contributing to NIST's post-quantum standardization efforts. Her work addresses quantum computing threats to current cryptosystems and develops error-correcting codes for reliable data transmission and storage. Education: PhD in Mathematics from the University of Zurich (2013), supervised by Prof. Joachim Rosenthal. Diploma in Mathematics from Ruhr-Universität Bochum. Research interests span coding theory (e.g., rank-metric codes, subspace codes), cryptography (code-based systems, privacy protocols), and neuroinformatics (connectome analysis). Recent publications emphasize Lee metric applications, MDS code classification, and cryptanalysis of Gabidulin-based systems. She mentors doctoral researchers such as Nadja Willenborg and Violetta Weger, focusing on topics like code densities and quantum-resistant algorithms. Her team's work bridges theoretical foundations and practical implementations, with contributions to error-correction resilience and cryptographic security in post-quantum scenarios. No formal awards listed, but actively participates in international conferences (IEEE, CBCrypto) and journal reviews.

Mitra Baratchiمشاهده پروفایل

دانشیار

• Spatio-Temporal Data Analysis
• Machine Learning
• Mobility Data Modeling
• +۵ مورد دیگر

Mitra Baratchi is an Associate Professor at the Leiden Institute of Advanced Computer Science (LIACS) , Leiden University. She leads the Spatio-temporal data Analysis and Reasoning (STAR) research group, co-leads the Automated Design of Algorithms (ADA) group, and founded the Special Interest Group on Spatio-Temporal Data Mining (SIG-SDTM) . PhD from University of Twente (Mobility Data) Master’s/Bachelor’s in Computer Engineering, Iran Research Interests focus on automated pattern extraction from spatio-temporal data across urban, environmental, and industrial domains. Key applications include: Automated Machine Learning (AutoML) for Earth Observations Time-Series Forecasting for public health (e.g., pandemic modeling) Urban Mobility Optimization with ESA, Honda, and municipalities Reliable Vehicular Communication Systems Smart Garments for Health Risk Detection Geocast Protocols for Internet-wide Communication Grant Highlights include €120K NWO-Aspasia, €2.9M Marie Skłodowska-Curie, €350K NWO-KLEIN, and €135K Center for BOLD Cities funding. She has supervised 12 PhD students and 4 current Master’s students since 2011, with notable best paper award at WWIC'16. Teaching includes Machine Learning (2020-present) and Urban Computing (2018-present) at Leiden, plus past courses in Data Visualization, Software Engineering, and Research Methods.

• Differential Privacy
• Database Systems
• Data Privacy
• +۵ مورد دیگر

Ashwin Machanavajjhala is a Professor in the Department of Computer Science at Duke University's Pratt School of Engineering. With over 166 publications spanning from 2001 to 2025, his research has significantly impacted the fields of differential privacy, database systems, and data security. His recent work focuses on practical applications of differential privacy for government data releases, particularly for the US Census Bureau. Machanavajjhala's research primarily centers on differential privacy, with significant contributions to database systems, privacy-preserving data analysis, and statistical disclosure control. His work bridges theoretical foundations with real-world applications, particularly in government statistics and census data protection. He has developed numerous frameworks and algorithms including DPXPlain for explaining differentially private query results, PreFair for generating fair synthetic data, and various components of the US Census Bureau's disclosure avoidance system. His research demonstrates a consistent trajectory from theoretical privacy mechanisms toward practical implementations that balance privacy guarantees with data utility. His recent publications reveal a strong focus on applying differential privacy to census data (SafeTab, PHSafe), developing methods for explaining private query results (DPXPlain), addressing fairness in private data analysis (PreFair), and exploring privacy applications in blockchain technology. His work shows increasing engagement with government agencies, particularly the US Census Bureau, where his research has directly informed disclosure avoidance systems for the 2020 Census. Machanavajjhala has advised numerous PhD students who have become prominent researchers in privacy and databases, including Ryan McKenna, Xi He, Yuchao Tao, and David Pujol. His collaborative network includes leading researchers from major institutions, with frequent collaborations with Gerome Miklau, Michael Hay, and Daniel Kifer. His research has been consistently funded by major grants supporting privacy-preserving data analysis. He leads research on the Tumult Analytics framework, a robust and scalable differential privacy system, and has been instrumental in developing privacy technologies for the US Census Bureau's 2020 data release. His work demonstrates a commitment to making differential privacy practical for real-world statistical agencies and data providers.

Yackolley Amoussou-Guenouمشاهده پروفایل

استاد

• Blockchain
• Consensus
• Distributed Systems
• +۱ مورد دیگر

Yackolley Amoussou-Guenou is a Professor in Computer Science at Paris-Panthéon-Assas University, affiliated with the Center for Research in Economics and Law (CRED). His work focuses on blockchain technologies, consensus algorithms, distributed systems, and algorithmic game theory. He earned a Doctorate in Computer Science from Sorbonne University in 2020. His research explores the intersection of game theory and blockchain security, analyzing rational player behaviors, fairness mechanisms, and consensus robustness. His publications highlight trends in committee-based blockchain design, adversarial modeling, and formal verification of consensus protocols. He has contributed to venues including The Review of Financial Studies and conferences like OPODIS, NETYS, and AAMAS. His teaching includes Data Science, Python programming, and Computer Science Fundamentals, reflecting his expertise in both theoretical and applied distributed systems research.

Yevgeniy Dodisمشاهده پروفایل

استاد

• Cryptography
• Leakage-Resilient Cryptography
• Random Number Generation
• +۱۰ مورد دیگر

Yevgeniy Dodis is a Professor of Computer Science at New York University's Courant Institute of Mathematical Sciences. He is a Fellow of the International Association for Cryptologic Research (IACR) and leads research in cryptography and theoretical computer science. Educational Background: Bachelor's degree in Mathematics and Computer Science (summa cum laude) from New York University (1996) PhD in Computer Science from MIT (2000) Professor Dodis specializes in cryptography with particular expertise in leakage-resilient cryptography, random number generation, cryptography with biometrics and other noisy data, hash functions and random oracle model, information-theoretic cryptography, and secure group messaging. His work bridges theoretical computer science with practical cryptographic applications, contributing significantly to the field's understanding of randomness in cryptographic systems. Throughout his career, Professor Dodis has received numerous prestigious awards including the 2021 and 2019 IACR Test of Time Awards for his groundbreaking work on verifiable random functions and fuzzy extractors, respectively. In 2020, he was named an IACR Fellow for his "fundamental contributions to cryptology, especially to cryptographic randomness and symmetric-key primitives, and for service to the IACR". Professor Dodis has advised 14 PhD students to completion, with current advisees including Peter Fenteany and Eli Goldin. He has also mentored numerous postdoctoral researchers throughout his career. He serves as Editor of the Journal of Cryptology and organizes the NYU Cryptography Seminar, fostering academic collaboration in the field. His research group at NYU focuses on advancing cryptographic techniques with practical applications in security and privacy, particularly in areas related to randomness generation and secure communication protocols.

Emmanuel Baccelliمشاهده پروفایل

استاد

• Internet of Things (IoT)
• Low-power protocols
• Network security
• +۵ مورد دیگر

Emmanuel Baccelli is a Professor for "Open and Secure IoT Ecosystem" at Freie Universität Berlin since September 2019, holding a joint position with Inria and the Einstein Center Digital Future (ECDF). He is also a scientific researcher at Inria since 2007 and co-founder/coordinator of the RIOT open source operating system for IoT devices since 2013. His research focuses on the intersection of low-power protocols, deeply embedded open source software, and security in the Internet of Things (IoT) ecosystem. Baccelli emphasizes the critical trade-off between energy efficiency and security in IoT systems, advocating for privacy-by-design principles and open specifications. His work addresses how users can maintain control over their systems and data in an increasingly connected world. Baccelli's publications demonstrate a clear progression toward secure, efficient IoT systems with recent work focusing on secure firmware updates, TinyML deployment, and privacy-preserving protocols. His research spans from foundational networking protocols to practical implementations for constrained devices, with a consistent emphasis on open source solutions and security-by-design. Baccelli completed his PhD in 2006 at École Polytechnique in Paris on "Routing and Mobility in Large Packet-Based Networks" and received his habilitation from Université Pierre et Marie Curie in 2012. He previously served as a Guest Professor at Freie Universität Berlin in 2013-2014 with a DAAD Grant. His professional activities include significant contributions to IETF standards, particularly RFCs related to routing protocols for low-power networks. Baccelli's research has practical applications across multiple domains including healthcare, smart agriculture, and industrial IoT systems, where security and energy efficiency are paramount concerns.

Dan Gutfreundمشاهده پروفایل

پژوهشگر

• Machine Learning
• Natural Language Processing
• Computer Vision
• +۳ مورد دیگر

Dan Gutfreund is a Principal Research Scientist and Senior Manager at the MIT-IBM Watson AI Lab, focusing on machine learning with applications to natural language processing and computer vision. He previously held managerial and technical roles at IBM's Haifa Research Lab and was involved in IBM Project Debater. Gutfreund earned his PhD in computer science from the Hebrew University in Jerusalem in 2005. His research spans Neuro-Symbolic AI , Computational Complexity , and Foundations of Cryptography , with notable contributions to datasets like Moments in Time and ObjectNet . His recent work includes multimodal models for the metaverse, generative AI for engineering design, and simulator-assisted training for interpretable systems. Gutfreund's publications reflect expertise in AI applications for supply chain prediction, avatar personalization, and reconciling virtual disputes. He has also explored evolutionary algorithms for software engineering and constraint-based generative models in design tasks.

• Finite Fields
• Cryptography
• Coding Theory
• +۴ مورد دیگر

Qiang (Steven) Wang is a Professor in the School of Mathematics and Statistics at Carleton University. His academic career spans several decades with a strong focus on finite fields and their applications in cryptography and coding theory. He maintains an active teaching schedule including courses like Abstract Algebra, Rings and Fields, and Fields and Coding Theory. Professor Wang's research interests center on Finite Fields and Applications in Cryptography and Coding Theory, Combinatorics, Algebra and Number Theory. His work particularly focuses on polynomials and functions over finite fields, sequences over finite fields, and applications in Coding Theory and Cryptography. He has made significant contributions to the study of irreducible polynomials, permutation polynomials, primitive polynomials, planar functions, Boolean functions, LFSR and NLFSR sequences, de Bruijn sequences, stream ciphers, pseudorandom generators, and linear complexity. His research bridges theoretical mathematics with practical cryptographic implementations. His extensive publication record shows a consistent and growing research program, with numerous publications in top-tier journals including Designs, Codes and Cryptography, Finite Fields and Their Applications, and Cryptography and Communications. His most recent work (2022-2024) has increasingly focused on compositional inverses of permutation polynomials, stable polynomials, additive codes with few weights, and generalized cyclotomic mappings, while maintaining strong connections to cryptographic applications. Editorial board member of Applicable Algebra in Engineering, Communication and Computing, Springer Editorial board member of Finite Fields and their Applications, Elsevier Professor Wang actively contributes to the academic community through his editorial work and seminar organization. He coordinates the Carleton Finite Fields eSeminar and participates in the Ottawa-Carleton Combinatorics and Optimization Seminar, fostering research collaboration in discrete mathematics and related fields. His teaching portfolio is diverse, covering both undergraduate and graduate courses that reflect his broad expertise across algebraic structures, coding theory, and discrete mathematics.

Athanasios D. Panagopoulosمشاهده پروفایل

استاد

• Communications
• Wireless Communications
• Radio Communications
• +۹ مورد دیگر

Athanasios D. Panagopoulos is a Full Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), specializing in Satellite & Space Communications , Antennas and Propagation , and Quantum Communication . He leads the Division of Information Transmission Systems and Material Technology, with a focus on wireless systems, machine learning, and 5G/6G technologies. Born in Athens (1975), received summa cum laude Diploma and Dr. Engineering from NTUA (1997, 2002). Former roles: part-time Assistant Professor (2003-2007), head of Satellite Division at Hellenic Authority for Information Security (2005-2008). Research Trends emphasize Quantum Key Distribution (QKD) , Reconfigurable Intelligent Surfaces , and Deep Learning Applications in satellite networks. His work bridges atmospheric propagation effects with terrestrial-satellite convergence , including AI-driven excess attenuation prediction and UAV channel modeling. Scientific Awards include URSI General Assembly Young Scientist Award (2002, 2005) Best Paper Awards: IEEE RAWCON 2006, IEEE ISWCS 2015 Grants & Collaborations : Principal Investigator for EU/ESA R&D programs, with editorial roles at IEEE Transactions on Antennas and Propagation, and Elsevier Physical Communication. Member of ITU-R , ETSI Study Groups , and IEEE (Senior) .

Chiara Petrioliمشاهده پروفایل

استاد

• Wireless Networking
• Underwater Sensor Networks
• Internet of Things (IoT)
• +۳ مورد دیگر

Chiara Petrioli is Full Professor at Sapienza University of Rome's Department of Computer, Control and Management Engineering and Deputy Rector for scouting, fundraising, and business incubation. She founded the spinoff WSENSE S.r.l. and coordinated the university's Computer Science Ph.D. program. Her research pioneers the Internet of Underwater Things, leading to breakthrough technologies featured in international media and the NT100 list. Her research interests center on wireless, embedded, IoT, and cyber-physical systems, with a focus on underwater networking. She designs and optimizes communication protocols, security mechanisms, and energy-efficient architectures for underwater sensor networks, enabling applications in environmental monitoring, archaeology, and deep-sea exploration. Recent publications highlight trends in underwater acoustic communications (e.g., dual-channel protocols, S2C modulation), security (authentication, key exchange), and energy efficiency (wake-up radio, UAV-assisted data collection). Applications span dissolved oxygen monitoring, submerged heritage preservation, and sustainable deep-sea mining impact assessment. Her scientific awards include: IEEE Fellow 2021 Fulbright Scholar Inspiring Fifty 2018 N2Women 2019 Star in Computer Networking and Communications Gamma Donna Women Startup Award 2022 Top 2% World Scientist by Stanford Repubblica D 100 Women to Change the World 2021 As principal investigator, she has led over twenty national and international projects, including EC projects GENESI and SUNRISE, and EASME projects ArcheoSub and Seastar. She founded WSENSE S.r.l., a spinoff that translates research into innovative technologies, resulting in international patents and features in BBC, RAI, Wired, and National Geographic. She actively contributes to the academic community as chair of IEEE SECON steering committee, associate editor of ACM/IEEE Transactions on Networking, and through leadership roles in ACM SIGMOBILE and IEEE Transactions on Mobile Computing.

Andrea Vitalettiمشاهده پروفایل

دانشیار

• Blockchain Technologies
• Internet of Things (IoT)
• Smart Environments
• +۷ مورد دیگر

Andrea Vitaletti is an Associate Professor at Sapienza University of Rome , affiliated with the Department of Computer Engineering, Automatics and Management Antonio Ruberti (DIAG) in the College of Engineering. His academic career spans over two decades of research in networking and algorithmic topics. PhD in Computer Science, Sapienza University of Rome (1998–2002) Assistant Professor (Ricercatore) at Sapienza (2007–2019) Co-founder of spin-offs WSENSE (2012–2019) and WLAB (2002–2016) Research Interests focus on decentralized systems , particularly blockchain technologies , Internet of Things (IoT) , federated machine learning , and data privacy . His work bridges theoretical algorithmic research with practical implementations in wireless sensor networks and distributed ledger systems. Scientific Contributions include over 90 publications, 2 patents, and leadership in the EU FET OPEN project PLEASED. His applied research has been recognized with multiple awards: 2000: Wonderland Contest - Media and Communication 2002: Simagine Innovation Prize 2004: Simagine Bronze Award 2007: Premio Perotto Top Prize 2012: Italiacamp Winner He leads the Wireless Sensor Networks lab at DIAG, supervising 2 PhD students, 1 post-doc, and 5 master students. His teaching portfolio includes courses on IoT, blockchain, cybersecurity, and digital entrepreneurship since 2000.

• Embedded Systems
• Internet of Things
• Wireless Sensor Networks
• +۵ مورد دیگر

João Luís Marques Pereira Monteiro is a Full Professor at the Department of Industrial Electronics, School of Engineering, University of Minho, Portugal. He has been with the university since 1980, progressing from Assistant Trainee to his current position. He has held significant leadership roles including Pro-rector (2005-2009), Director of the Algoritmi Center (1998-2006, 2010-2013), and Dean of the School of Engineering (2013-2019). He currently coordinates the Embedded Systems Research Group (ESRG) and is a Senior Researcher at the Algoritmi Research Center. His educational background includes: Bachelor's degree in Electrical Engineering and Computers from the University of Porto (1980) PhD in Informatics and Systems Engineering - specialization in Computer Engineering - from the University of Minho (1991) Habilitation (Dr habil) from the University of Minho (2003) Professor Monteiro's research spans multiple domains in engineering and computer science, with a strong focus on practical applications. His work in embedded systems has led to innovations in real-time processing, sensor networks, and hardware-software co-design. In medical applications, he has developed textile-based sensors for vital sign monitoring. His recent work focuses on computer vision for autonomous vehicles, particularly 3D object detection from point clouds. He also contributes to educational initiatives in data science and AI, particularly in developing countries. His recent publications show a clear progression toward applications requiring real-time processing on resource-constrained devices. There's a strong emphasis on autonomous systems, particularly self-driving vehicles, with multiple papers on 3D object detection from point clouds. His work bridges embedded systems, computer vision, and wireless communications, often focusing on practical implementations for real-world applications like emergency responder localization and medical monitoring. Professor Monteiro has supervised more than a dozen doctoral students, many of whom have gone on to become faculty members at national and international universities. His research has been supported by various funding agencies including FCT (Portuguese), ADI (Portuguese), and FP7 (European funding), as well as industry partners. He leads the Embedded Systems Research Group (ESRG), which is part of the Algoritmi Research Center. The ESRG focuses on developing embedded solutions for various applications including autonomous vehicles, medical devices, and industrial monitoring systems. The group works on both hardware and software aspects of embedded systems, with particular expertise in real-time processing and resource-constrained environments.

• Embedded real-time systems
• Computer architectures
• Hardware/software co-design for IoT
• +۵ مورد دیگر

Tiago Manuel Ribeiro Gomes is an Assistant Professor at the Department of Industrial Electronics within the School of Engineering at the University of Minho, Portugal. He is also a Senior Researcher at Centro ALGORITMI and a member of both the IE R&D Group and the ESRG R&D Lab. Holding a Ph.D. in Electronics and Computers Engineering, his research focuses on embedded real-time systems, computer architectures, and hardware/software co-design for IoT devices. Academic Degree: Ph.D. in Electronics and Computers Engineering Current Position: Assistant Professor, School of Engineering, University of Minho Gomes has led extensive research in IoT systems over 15 years, particularly in hardware acceleration for automotive LiDAR sensors, secure embedded systems, and efficient OS frameworks for low-end devices. His work includes the EU-funded CROSSCON project and spans hardware-assisted security, dynamic binary translation, and wireless sensor networks. Recent publications highlight his expertise in automotive sensor technology, with articles like FOG-Zip for LiDAR compression, SecureQNN for TinyML security, and Hardware-Assisted Range Image Generation for LiDAR processing. His work bridges IoT, embedded systems, and cybersecurity, focusing on real-time performance and hardware-software co-design. Projects include the development of reliable/secure automotive sensor solutions and EU project CROSSCON. He contributes to open-source frameworks like UTango for IoT security and investigates heterogeneous fault tolerance architectures using Arm/RISC-V processors. Labs: IE R&D Group, ESRG R&D Lab Education: Ph.D. in Electronics and Computers Engineering, Master’s in Telecommunications Engineering (both from University of Minho)

Gunnar Malmمشاهده پروفایل

استاد

• Semiconductors
• Spintronics
• Nanoelectronics
• +۳ مورد دیگر

Gunnar Malm is a full-time Professor and Deputy Head of Department at the Royal Institute of Technology (KTH) in the School of Electrical and Computer Engineering. His research focuses on semiconductors and spintronics (nano-electronics), with special emphasis on variability, noise, and fluctuations in electronic components, as well as electronics for extreme environments. He combines experimental work with large-scale computer simulations via KTH's PDC, national SNIC clusters, and Vienna University of Technology's VSC resources. Editor, IEEE Electron Device Letters (2017–present) Technical Program Committee, European Solid-State Device Research Conference (ESSDERC) His pedagogical research (TALE 2022) explores citation practices in thesis writing, and he coordinates multiple semiconductor component courses including Design of Nanosemiconductor Components (IH2657) and Simulation of Semiconductor Components (IH2653) . Malm's Noise and Fluctuations Lab investigates fundamental device physics for sustainable electronics development.