Find Academic Supervisors

Vitaly PetrovView profile

Assistant Professor

• Terahertz Communications
• 6G and Beyond Networks
• Satellite Communications
• +5 more

Vitaly Petrov is an Assistant Professor at the Division of Communication Systems within the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology. He leads the TERANET@KTH Research Lab and focuses on terahertz (THz) communications, 6G/7G networks, and non-terrestrial networks (NTNs). His research bridges theoretical frameworks with experimental validations, addressing challenges such as beamforming, blockage mitigation, and physical layer security in high-frequency systems. Affiliations: KTH Royal Institute of Technology (2024–present), Northeastern University (2022–2024), Nokia Bell Labs (2020–2022) Education: PhD in Communications Engineering (Tampere University, 2020), M.Sc. in IT & Security (SUAI University, 2011), M.Sc. in Communications Engineering (Tampere University of Technology, 2014) Research interests span THz band communications, satellite integration in 6G+, and innovative beam management techniques. He has pioneered work on near-field THz systems and wavefront hopping for security. His contributions include experimental platforms for beam realignment algorithms and CubeSat missions for 7G THz exploration. Awards: Best Student Paper (IEEE VTC 2015), Best Student Poster (IEEE WCNC 2017), IEEE Finland Best Journal Paper (2019), Runner-Up Best Paper (IEEE CCNC 2025) Teaching includes courses on mobile networks, scientific writing, and research methodology. He actively contributes to IEEE journals as an editor and has advised Ph.D. students through open positions (e.g., deadline March 2024). Labs and projects: TERANET@KTH, 7G THz CubeSat mission, seamless satellite integration with 6G+ networks, re-programmable THz surfaces for sensing/communications.

Luca ManneschiView profile

Lecturer

• Machine Learning
• Neuromorphic Computing
• Biological Networks
• +3 more

Dr Luca Manneschi is a Lecturer in Machine Learning at the School of Computer Science, University of Sheffield, with an IBM Liaison role. He holds a PhD in Physics from the University of Sheffield (2021) and completed a PostDoc there before his current position since March 2022. His research focuses on designing learning algorithms inspired by biological networks for physically defined systems, emphasizing neuromorphic computing, reservoir computing, and stochastic environments. Education: Bachelor's in Physics: University of Padua (Italy) Master's in Physics: Sapienza University of Rome (Italy) PhD in Physics: University of Sheffield (2021) Research Interests: Dr. Manneschi explores algorithms for physically defined networks, leveraging biological network principles to enhance computation in dynamic environments. His work bridges machine learning with neuromorphic hardware, emphasizing adaptability and energy efficiency. Key areas include reservoir computing, magnetic metamaterials, and multi-timescale learning strategies. Grants & Funding: "Real-time Reservoir Computing on Prosthetic Devices" (2023–2025, Royal Society, PI) "MARCH: Magnetic Architectures for Reservoir Computing Hardware" (2021–2025, EPSRC, Co-PI) "CausalXRL: Causal Explanations in Reinforcement Learning" (2021–2024, EPSRC, Co-PI) "ActiveAI" (2019–2024, EPSRC, Co-PI) Lab/Team Affiliation: Machine Learning Research Group, School of Computer Science.

Ivan SchullerView profile

Professor

• Superconductivity
• Nanostructures
• Magnetic Materials
• +4 more

Ivan Schuller is a Distinguished Professor in the Department of Physics at the University of California San Diego (UCSD). His research focuses on superlattices, nanostructures, vortices, organic semiconductors, insulating thin films, proximity effects, and devices. He holds a Ph.D. from Northwestern University (1976). Key awards include the 2015 Lise Meitner Award, the 2014 NTN Nanostar Award, and the 2004 E.O. Lawrence Award. His work spans phase transitions in quantum materials, neuromorphic computing, and magnetic phenomena. The Schuller Group has pioneered studies on hybrid materials, including vanadium dioxide-based devices and thermal neuristors for energy-efficient computing. Research highlights include discoveries in giant magnetic effects induced in hybrid materials, voltage-controlled spin resonance, and stochastic synchronization in spiking oscillators. He has collaborated on projects such as phase-change metasurfaces for thermal management and neuromorphic architectures using correlated electron systems. His lab explores intersections between materials science, energy applications, and computational neuroscience. Education: Ph.D. in Physics, Northwestern University (1976) Awards: NSSEFF Award, IEEE Distinguished Lecturer, Doctor Honoris Causa (Universidad Complutense de Madrid) Labs/Teams: Schuller Group (focusing on quantum materials and neuromorphic engineering) Recent work includes studies on ramp reversal memory in VO₂, resistive switching in engineered Mott insulators, and correlative microscopy of phase transitions. His research bridges fundamental physics and applied technologies, with implications for next-generation computing and energy systems.

Barry C. SandersView profile

Professor

• Quantum Computing
• Quantum Information Theory
• Quantum Algorithms
• +3 more

Barry C. Sanders is a Professor and Director of the Institute for Quantum Science and Technology at the University of Calgary. He holds additional roles as Lead Investigator of the Alberta Major Innovation Fund Project on Quantum Technologies, a Thousand Talents Chair at the University of Science and Technology China, and Vajra Visiting Faculty at the Raman Research Institute. His research focuses on quantum computing, quantum algorithms, and optical implementations of quantum information tasks. Sanders has a PhD from Imperial College London (1987) and has held faculty positions at Macquarie University and the Australian National University. Education: BSc (University of Calgary, 1984), PhD (Imperial College London, 1987) Affiliations: Institute for Quantum Science and Technology, Alberta Major Innovation Fund Project His research interests include quantum-limited measurement, nonclassical light, quantum cryptography, and quantum algorithm development. He has pioneered work on Schrödinger cat states, qudit systems, and quantum error correction. Awards include Fellowships from the Institute of Physics, Optical Society of America, and Royal Society of Canada. His work bridges theory and application, with contributions to quantum technology commercialization and interdisciplinary collaborations. Editor-in-Chief, New Journal of Physics Past leadership roles: President of the Australian Optical Society, Founding Co-Chair of the Canadian Association of Physicists Division His recent publications explore quantum speedup in machine learning, topological quantum walks, and fault-tolerant quantum computing architectures.

Rabah AoufiView profile

Senior Lecturer

• Digital Signal Processing
• Microcontroller Systems
• Control Systems
• +3 more

Rabah Aoufi is a Senior Lecturer in the Department of Engineering Technology & Industrial Distribution at the College of Engineering, Texas A&M University. His primary affiliation includes the Electronic Systems Engineering Technology program. He can be reached at raoufi@tamu.edu and is located in FERM 304AA. His work focuses on digital signal processing, microcontroller systems, control systems, and engineering entrepreneurship. Research interests span embedded systems design, real-time data processing, and innovative educational projects. His publications reflect expertise in both foundational engineering principles (e.g., signal processing fundamentals) and applied technologies (e.g., microcontroller programming and big data frameworks). His articles demonstrate a career-long engagement with evolving technologies—from foundational 1980s multiprocessor architectures to modern big data systems. No scientific awards or grants are explicitly mentioned in the provided materials.

Garth V. CrosbyView profile

Associate Professor

• Internet of Things (IoT)
• Industrial Internet of Things (IIoT)
• Cyber-physical Systems Security
• +5 more

Garth V. Crosby is an Associate Professor at Texas A&M University's Department of Engineering Technology and Industrial Distribution within the College of Engineering. He is also affiliated with the Multidisciplinary Engineering program. His research focuses on IoT and IIoT security, cyber-physical systems, and STEM education innovation. Crosby holds a Ph.D. in Electrical Engineering from Florida International University (2007), an M.S. in Computer Engineering, and a B.S. in Electronics (Applied Physics) from the University of the West Indies. His work spans cybersecurity frameworks for emerging technologies, including blockchain-based federated learning, post-quantum cryptography, and IoT threat mitigation. He has contributed to educational advancements through online lab design and faculty efficacy studies in hybrid learning environments. Crosby's recent publications emphasize securing robotic IoT systems, supply chain blockchain applications, and ransomware evasion techniques using generative AI. His research portfolio includes over 40 peer-reviewed articles in journals like IEEE Transactions and conferences such as ASEE and FiCloud. Key themes include volunteer cloud reliability models (ProTrust), edge computing security, and educational technology evaluation. Crosby's interdisciplinary approach bridges engineering systems with pedagogical innovation, addressing both technical and human factors in modern technological challenges.

Sonia Solera CotanillaView profile

Assistant Professor

• Cybersecurity
• 5G Networks
• Internet of Things (IoT) Security
• +3 more

Sonia Solera Cotanilla is an Assistant Professor at the Universidad Politécnica de Madrid, specializing in cybersecurity, IoT security, and privacy protection in connected devices. She leads the RSTI research group, actively participates in European projects like DESIRE6G, 6Green, and ACROSS, focusing on 5G network security, energy efficiency, and cross-layer provisioning frameworks. Her work integrates hardware-software solutions for emerging technologies such as smart home systems, wearables, and e-voting infrastructure. Key affiliations: RSTI Group, Polytechnic University of Madrid Research areas: Cybersecurity frameworks, threat detection, privacy-preserving architectures Recent contributions include developing the SPEDIA system for insider threat detection, cybersecurity frameworks for FCAS risk assessment, and privacy analysis of wearable devices for minors. She has advised doctoral candidates like Mario Sanz Rodrigo and Carmen Sánchez Zas, both awarded PhDs in Telematic Systems Engineering. Notable awards: ISDEFE Prize for Best Doctoral Thesis (2024) Grants: National Cybersecurity Institute (INCIBE) funding, Horizon 2020 projects Labs/Teams: RSTI Group focuses on advanced cybersituational awareness platforms and secure IoT/IIoT infrastructure development. Current projects include GovTech4Impact, RAMONES, and e-Voting security audits for Minsait.

• Security
• Embedded Systems Security
• Cyber-Physical Systems Security
• +13 more

Francesco Regazzoni is a Senior Researcher at the Faculty of Informatics, Università della Svizzera italiana (USI), and affiliated with the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). His work bridges embedded systems, cybersecurity, and artificial intelligence, with a focus on securing hardware and cyber-physical systems. Research Interests: His expertise spans embedded and cyber-physical systems security, side-channel attacks, post-quantum cryptography, hardware trojans, random number generators, and the security of AI and approximate computing. He also contributes to hardware/software co-design and operating systems security. The analysis of his recent publications reveals a consistent focus on hardware and system-level security , particularly in resource-constrained environments like IoT and embedded devices. His work integrates machine learning for attack detection and applies formal methods to ensure trust in hardware. A growing emphasis is placed on securing AI systems from physical and adversarial threats. Scientific Contributions: Over 100 peer-reviewed publications One book and one patent Extensive international collaboration (Belgium, Netherlands, USA, Switzerland, Singapore) Advising and Grants: While specific advisees and grants are not listed, his leadership in funded research projects and involvement with ALaRI and IDSIA suggest active mentorship and project coordination. His work has been supported by industry (e.g., ST Microelectronics, HP), the Swiss National Foundation, and the European Union. Labs and Teams: He is part of the Graph Machine Learning Group (GMLG) at IDSIA, which evolved from the Advanced Learning and Research Institute (ALaRI). This group focuses on graph machine learning, reinforcement learning, and dynamical systems, particularly in non-stationary environments.

• Cryptography
• Computer Security
• Privacy
• +3 more

Gene Tsudik is the Peter & Lois Griffin Professor at the University of California, Irvine (UCI), affiliated with the School of Information and Computer Sciences. His research focuses on cryptography, computer security, privacy, and applied cryptographic protocols. He has authored over 300 publications in top-tier venues, addressing challenges in secure communication, key management, privacy-preserving technologies, and network security. Key research areas include group key agreement, secure data possession, privacy-preserving protocols, and mobile agent systems. His work has influenced foundational aspects of computational grid security, cloud storage integrity, and post-quantum cryptography. Collaborations include prominent institutions like KAIST, University of Surrey, and NYIT. His publications span topics from theoretical cryptographic proofs to practical system implementations, reflecting a balance between academic rigor and real-world applicability.

• Educational Technology
• Digital Competence in Education
• Digital Transformation in Higher Education
• +7 more

Linda Castañeda is a Professor of Educational Technology in the Department of Didactics and School Organization at the Faculty of Education, University of Murcia, Spain. Born in Bogotá, Colombia, and based in Murcia, she holds a PhD in Educational Technology from the University of the Balearic Islands. She is a leading figure in digital transformation in higher education, coordinating major European projects such as CUTIE and DALI, and directing strategic research contracts with the European Union's Joint Research Center. Her research focuses on educational technology, digital leadership, AI in education, and digital literacy. She has conducted international research stays at prestigious institutions including the Open University (UK), University of Oxford, UC Berkeley, and UJI. She is actively involved in editorial roles for top journals such as the European Journal of Educational Technology in Higher Education , Journal of New Approaches in Educational Research , and Educational Technology Research & Development . Linda leads the development of open educational resources, such as the course Strategic Leadership for Digital Transformation in Universities , adapted for the Spanish context. Her recent work emphasizes integrating AI into pedagogical practices, rethinking student roles, and fostering critical engagement with technology. She is deeply committed to ethical, people-centered, and pedagogically grounded digital transformation in education. She has contributed to national and European frameworks, including the University Digital Teaching Competence Framework (MCDDU) and the UNIDIGITAL accreditation project. Her publications reflect a strong focus on institutional change, teacher development, data literacy, and open, collaborative knowledge creation. Member, Editorial Board – European Journal of Educational Technology in Higher Education Member, Editorial Board – Journal of New Approaches in Educational Research Member, Development Editorial Committee – Educational Technology Research & Development (ETR&D) Member, GITE – Interuniversity Journal of Research in Educational Technology Linda mentors students through innovative teaching methods involving AI-enhanced reflection, role-based learning, and collaborative blogging. She emphasizes metacognition, feedback integration, and digital fluency. Her projects involve cross-institutional collaboration across 35 Spanish universities and European partners, demonstrating her leadership in shaping the future of digital education. She maintains an active blog, Educational Mushware , where she reflects on ideas over tools—'MUSHWARE' being the conceptual and creative layer beyond hardware and software. Her vision is for education to be transformed not by technology alone, but by thoughtful, human-centered innovation.

Georg CarleView profile

Professor

• Internet Technology
• Future Internet Architecture
• Network Security
• +3 more

Prof. Georg Carle is a full Professor in Network Architectures and Network Services at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology. He leads research in Internet technology, focusing on future network architectures, security, and real-time communication. Prior roles include positions at the University of Tübingen and Fraunhofer Institute for Open Communication Systems (FOKUS). Education: Electrical Engineering diploma from University of Stuttgart (1992), Master of Science in Digital Systems (Brunel University, London), and PhD in Telematics from University of Karlsruhe (1996). He held scholarships in complex systems and European Union-funded research at Institut Eurécom. Research Interests: Prof. Carle's work spans network security, sensor networks, autonomous systems, and future Internet protocols. His group develops tools like MoonGen (packet generator) and pos (experiment workflow system). Recent focus includes QUIC protocol analysis, network slicing, and reproducible experimentation frameworks. Key Contributions: Award-winning research includes Applied Networking Research Prizes (2017-2018), Best Paper Awards in IMC/PAM, and innovations in network measurement, security, and programmable data planes. His lab explores cutting-edge topics like post-quantum cryptography, low-latency networking, and 6G automation. Recognition: Honors include ACM SIGCOMM Community Contribution Award, IRTF ANRP, and multiple conference best paper accolades. He advises on network infrastructure for industrial IoT, automotive systems, and secure multiparty computation.

Sneha D. GoenkaView profile

Assistant Professor

• Computational Genomics
• Computer Systems Architecture
• High-Performance Computing
• +5 more

Sneha D. Goenka is an Assistant Professor at Princeton University in the Department of Electrical and Computer Engineering, with associated faculty status in the Computer Science department. She earned her Ph.D. from Stanford University (2024) and dual B.Tech./M.Tech. degrees from IIT Bombay (2017). Her research bridges computer systems architecture and computational genomics to develop accelerated genomic pipelines. Education : Ph.D. (Electrical Engineering, Stanford 2024), Dual Degree (IIT Bombay 2017) Her work focuses on optimizing genomic data processing through hardware-software co-design, achieving speedups in clinical and evolutionary genomics. She led the development of the world's fastest genome diagnosis technique using nanopore sequencing and cloud computing. Recent publications highlight her expertise in GPU/FPGA acceleration (SegAlign, Darwin-WGA) and ultra-rapid variant detection pipelines. Her research has been published in top venues like Nature Biotechnology , New England Journal of Medicine , and SC/HPCA conferences . Scientific Awards : Stanford Centennial TA Award (2024) ACM Heidelberg Laureate Forum Young Researcher (2024) Forbes 30 Under 30 (Science) (2023) NVIDIA Graduate Fellow (2022) Cadence Women in Technology Scholar (2021) She advises students in her lab and has collaborated with institutions like Stanford Medicine, NVIDIA Research, and D.E. Shaw Research. She also contributed to the Pratham satellite project at IIT Bombay.

• Neurology
• Neurosciences
• Radiology and Medical Imaging
• +10 more

Anna Falk Delgado is an Associate Professor (Docent) in Radiology at Karolinska Institutet, affiliated with the Department of Clinical Neuroscience. She leads the Clinical Brain Imaging Methods research group and focuses on advanced neuroimaging techniques. University Medical Degree, Karolinska Institutet, 2009 Docent, Karolinska Institutet, 2021 Affiliated to Research, Department of Clinical Neuroscience, 2024-2027 Her research spans Neurology , Neurosciences , and Radiology and Medical Imaging , with expertise in PET/MR , Cone-Beam CT , Brain Tumor Imaging , and Stroke Radiology . She pioneered ultra-fast multi-contrast MRI protocols and dual-layer CT angiography for stroke evaluation. Recent publications emphasize technical innovations in hybrid imaging, stroke triage optimization, and pediatric neuroimaging safety. Her work integrates machine learning , radiation reduction , and clinical translation of imaging technologies.

Alan J. SmithView profile

Professor

• Computer Architecture
• Computer Engineering
• Operating Systems
• +4 more

Alan J. Smith is a Professor in the Electrical Engineering and Computer Sciences department at the University of California, Berkeley, within the College of Engineering. With a distinguished career spanning several decades, he has made significant contributions to computer architecture, system performance analysis, and memory systems. Dr. Smith received his S. B. from MIT and a Ph.D. from Stanford University. His educational background provided the foundation for his extensive research in computer systems. Professor Smith's research focuses on computer architecture and engineering, particularly in system performance analysis, I/O systems, cache memories, and memory systems. His work has profoundly influenced how computer systems are designed and evaluated, with particular emphasis on optimizing storage systems, cache performance, and energy efficiency in computing platforms. His research has bridged theoretical analysis with practical implementation, resulting in numerous influential publications and real-world applications. His publication record shows a consistent focus on computer system performance, evolving from early work on cache memory and paging algorithms to more recent research on multimedia workloads, energy management, and storage systems. The breadth of his work spans fundamental computer architecture principles to applied system design, with particular emphasis on measurement-based analysis and optimization techniques. Harry Goode Award of the IEEE Computer Society (2006) IEEE Reynold B. Johnson Information Storage Systems Award (2008) A. A. Michelson Award of the Computer Measurement Group (2003) Fellow of the American Association for the Advancement of Science (2001) Fellow of the ACM (2000) Fellow of the IEEE (1988) Throughout his career, Professor Smith has actively contributed to the academic community through editorial roles, conference organization, and professional society leadership. He has served as Subject Area Editor for the Journal of Parallel and Distributed Computing since 1989, chaired ACM SIGARCH and SIGOPS, and participated in numerous technical committees. His research has been supported by various grants that enabled extensive experimental work and system development. Professor Smith has been instrumental in developing benchmarking methodologies and performance analysis techniques that have become standard practices in computer system evaluation. His work on cache memory systems, in particular his influential 1982 Computing Surveys paper "Cache Memories," has shaped the field for decades.

• Computer Architecture
• FPGA
• Hardware Acceleration
• +4 more

Jianyi Cheng is a Lecturer in Computer Architecture at the School of Informatics, The University of Edinburgh, where he is affiliated with the Institute for Computing Systems Architecture. His work focuses on advancing computing systems through innovative hardware design and optimization. His research interests lie primarily in computer architecture and reconfigurable computing, with emphasis on FPGA-based acceleration, high-level synthesis, and energy-efficient system design. These areas are critical for next-generation computing platforms in domains such as AI, scientific computing, and embedded applications. The trends in his research, though not detailed in specific publications here, align with modern challenges in hardware-software co-design and domain-specific architectures. His work bridges the gap between theoretical algorithms and practical implementations on programmable logic. Jianyi Cheng has not been listed with any scientific awards in the provided text. He is actively involved in research within the Institute for Computing Systems Architecture, contributing to advancements in computing systems. While specific grants or advising roles are not mentioned, his position suggests engagement in research leadership and student supervision.