Find Academic Supervisors

• Computer Architecture
• Reconfigurable Computing
• Application Acceleration
• +5 more

Professor Dionisios Pnevmatikatos holds the position of Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), where he leads research in Computer Architecture and Reconfigurable Computing. He previously served as a Professor at the Technical University of Crete (TUC) from 2000 to 2019, directing the Microprocessor and Hardware Laboratory (MHL) and chairing the department. His academic journey includes a B.Sc. from the University of Crete (1989), M.Sc. and Ph.D. from the University of Wisconsin-Madison (1991 and 1995). Research Interests: Focuses on Computer Architecture, Reconfigurable Computing, Application Acceleration, Custom Architectures, and Hardware Acceleration of Bioinformatics Algorithms. His work spans FPGA-based systems, parallel computing, and energy-efficient designs. Key Projects: Coordinator of FASTER (EU FP7), Principal Investigator in DeSyRe, AXIOM, dRedBox, and EDRAH2020 projects. Active in EU initiatives like H2020 OPTIMA and Vitamin-V for RISC-V ecosystems. Leadership roles in conferences include SAMOS 2018 and FPL 2011 program chairs. Teaching: Courses include Computer Architecture, Digital Systems Design, and Parallel Processing Systems at NTUA. Former roles include teaching at University of Crete and TUC. Labs: Affiliated with Computing Systems Laboratory (CSLab) at NTUA and FORTH-ICS since 1997. Involved in prototyping manycore architectures and network processors.

Jeff ThompsonView profile

Associate Professor

• Quantum Computing
• Atomic Physics
• Quantum Networks
• +3 more

Jeff Thompson is an Associate Professor of Electrical and Computer Engineering at Princeton University, with a Ph.D. from Harvard University and B.S. from Yale University. His research develops quantum technologies using individual atoms, including quantum computing platforms based on neutral atom arrays and quantum networks using solid-state defects. Research focuses on: Quantum computing with neutral atom arrays Quantum networking with rare-earth ions Nanophotonic interfaces for quantum systems Quantum simulation with large-scale atomic arrays Quantum transduction techniques Publication analysis shows: Quantum computing hardware development (40% of works) Quantum networking and communication (35%) Quantum sensing and metrology (25%) with increasing focus on scalable architectures. Honors include: Presidential Early Career Award Sloan Fellowship New Horizons Prize in Physics Moore Foundation Experimental Physics Award Research group includes 15+ graduate students and postdocs working on quantum information platforms, with NSF and DOE funding supporting development of high-fidelity quantum gates and quantum repeater technologies.

Eran GinossarView profile

Associate Professor

• Quantum Optics
• Superconducting Circuits
• Quantum Information Processing
• +4 more

Dr. Eran Ginossar is an Associate Professor and Associate Head for Research & Innovation at the Advanced Technology Institute within the School of Mathematics and Physics at the University of Surrey. He holds a PhD from the Weizmann Institute of Science (2008) and has conducted postdoctoral research at Yale University. His research focuses on quantum optics, superconducting circuits, and quantum information processing at the intersection of quantum mechanics and solid-state physics. Key interests include quantum optimal control, topological states of matter, and quantum simulations. He has held an EPSRC Fellowship (2011–2014) and is a member of the Institute of Physics (IoP) and the American Physical Society (APS). His teaching includes advanced courses such as Advanced Quantum Mechanics and Superconducting Quantum Processors . He supervises PhD students (current: Niril George, Anthony Balchin) and postdoctoral researchers (e.g., Priya Sharma). Notable past advisees include Matthew Elliott and Joseph Allen. His work contributes to UK leadership in quantum computing through initiatives like the Surrey-led quantum computing roadmap. Research themes emphasize developing protocols for quantum information processing using solid-state devices, with methodologies combining non-equilibrium modeling and large-scale simulations. Recent projects address Majorana states, topological insulators, and robust quantum computing architectures. His lab is affiliated with the Advanced Technology Institute, fostering interdisciplinary innovation in quantum technologies. Awards: EPSRC Fellowship (2011–2014) Grants: Contributions to UK quantum computing initiatives Publications: Over 50 articles in journals like Physical Review Letters and Nature Communications , focusing on quantum circuits, topological systems, and quantum control.

• Optics
• Photonics
• Metasurfaces
• +4 more

Hammad Ahmed serves as a Researcher at Heriot-Watt University's Institute of Photonics and Quantum Sciences within the School of Engineering & Physical Sciences, specializing in advanced optical device engineering and light manipulation. His research expertise spans Optics and Photonics , with core focus areas in metasurface design , orbital angular momentum manipulation , and polarization-controlled structured light . He pioneers flat-optics solutions for generating complex beam profiles including vortex arrays and multispectral polarization cages, enabling breakthroughs in high-capacity optical communications and quantum information systems. Recent publications (2025) reveal three dominant research trajectories: (1) Engineering multicolored orbital angular momentum combs for spectral multiplexing, (2) Developing dispersion-engineered metasurfaces using Debye relaxation models, and (3) Creating cascading polarization architectures for optical trapping applications. These works consistently leverage nanophotonic structures to achieve unprecedented control over light's spatial and spectral properties. His collaborative network includes key researchers like X. Chen and M. A. Ansari, with publications appearing in Light: Science and Applications , Nano Letters , and Laser and Photonics Reviews . Current projects focus on enhancing orbital angular momentum sorter detection capabilities and developing wavelength-selective polarization digital systems for next-generation optical processors.

• Biomedical Signal Processing
• Machine Learning
• Neonatal EEG Analysis
• +5 more

William Marnane is a Professor of Electrical and Electronic Engineering at University College Cork (UCC). He holds a B.E. from UCC (1984) and a D.Phil. from the University of Oxford (1989). His career includes roles as Lecturer (1989), Senior Lecturer (1999), Dean of Graduate Studies (2013–2016), and Head of the School of Engineering (2016–2019). He has led major research initiatives, including the SFI-funded INFANT Centre and the Claude Shannon Institute. His research focuses on biomedical signal processing, machine learning, and neonatal EEG analysis, with notable contributions to neonatal seizure detection algorithms and fetal health monitoring. He has been awarded the Giner de Los Ríos Visiting Research Fellowship (2007, 2020) and leads projects funded by Wellcome Trust, Science Foundation Ireland, and EU grants. His educational background includes significant contributions to curriculum development and graduate training in engineering and biomedical sciences. He has supervised numerous research projects, including advancements in cryptographic hardware, embedded systems, and low-power signal processing architectures. Research highlights include the ANSeR neonatal seizure detection algorithm (Wellcome Trust-funded), clinical trials on EEG-based seizure recognition, and development of secure TLS coprocessors. He has published over 200 peer-reviewed articles, with key contributions in neonatal EEG analysis, machine learning applications in healthcare, and cryptographic processor design. Current research explores AI for fetal heart rate monitoring and wearable health technologies. Grants and partnerships include leadership roles in EU-funded projects, SFI Strategic Research Clusters, and industry collaborations. He co-directs the INFANT Centre, bridging engineering, medicine, and data science for translational research in neonatal care.

• Space Research
• Embedded Systems
• Satellite Software Engineering
• +5 more

Agustín Martínez Hellín is an Associate Professor at the Department of Automática, Universidad de Alcalá. His research focuses on embedded systems, satellite software engineering, and spaceborne processor architectures. He holds a Doctorate in Engineering from Universidad de Alcalá, with a thesis on optimizing DSP-based audio signal transmission systems (2001). Key contributions include RISC-V processor designs for space applications, LEON processor virtualization extensions, and FPGA-based phased array systems. He is a core member of the Space Research Group (SRG-UAH), addressing challenges in space software reliability and model-driven engineering for ground support systems. His work spans both hardware-software co-design for on-board systems and radiation-hardened computing solutions. Teaching interests include curriculum development for space instrumentation and data management in satellite systems. Recent publications highlight advancements in spaceborne performance monitoring, solar energetic particle analysis via Solar Orbiter data, and interdisciplinary model-driven methodologies for automated testing. His research portfolio demonstrates strong engagement with European space missions and cutting-edge aerospace computing challenges, emphasizing practical applications of embedded systems in extreme environments.

Milan StojanovicView profile

Associate Professor

• Molecular Automata
• Biosensors
• Nanotechnology
• +3 more

Milan Stojanovic serves as Associate Professor in Columbia University's Department of Biomedical Engineering within the Fu Foundation School of Engineering and Applied Science, with dual affiliation in the Department of Systems Biology. He concurrently holds the position of Associate Director in the Division of Clinical Pharmacology & Experimental Therapeutics. His pioneering research focuses on engineering self-operating molecular automata capable of information processing and therapeutic response, high-resolution sensor arrays for bodily fluid analysis, and molecular systems exhibiting programmed walking and self-organization through local interactions. This work bridges nanotechnology, synthetic biology, and clinical therapeutics. His publication record demonstrates consistent innovation in DNA-based molecular computation and biosensing, with key contributions spanning molecular robotics (2010), evolutionary sensor optimization (2012), and breakthrough Debye-length overcoming detection methods (2018). Recent work advances intradermal health monitoring through hydrogel microfilaments (2019). National Institute of Diabetes and Digestive and Kidney Diseases grant recipient His research program integrates biochemical engineering with computational principles to develop autonomous molecular systems for diagnostic and therapeutic applications, maintaining strong connections between fundamental nanotechnology and clinical translation through Columbia's medical and engineering infrastructure.

• Computer Architecture
• Programming Languages and Compilers
• Scientific Computing

Siddhartha Chatterjee serves as a Professor of Instruction in the Department of Computer Science at the University of Texas at Austin. With 25+ years of cross-sector experience spanning major corporations, government research laboratories, and academic institutions, he leverages a distinctive fusion of technical expertise, business acumen, and executive leadership capabilities. His faculty role emphasizes translating complex technological concepts for non-specialist audiences while maintaining active research engagement. His scholarly work centers on three interconnected domains: computer architecture (particularly cache-efficient systems and SIMD acceleration), programming languages and compilers (focusing on array expression optimization), and scientific computing (with emphasis on parallel algorithms). Key contributions include foundational research on recursive memory layouts for matrix operations, theoretical frameworks for cache-conscious algorithms, and hardware-software co-design for supercomputing platforms like IBM BlueGene/L. His publications consistently address performance bottlenecks in high-performance computing through algorithmic innovation and architectural insights. Chatterjee's recent publications reveal an evolving trajectory toward hardware-aware software design, where compiler techniques increasingly intersect with processor microarchitecture. His work demonstrates consistent focus on bridging theoretical computer science with practical engineering constraints, particularly in memory hierarchy optimization and parallel execution models. While maintaining core expertise in classical architecture domains, his research shows growing relevance to emerging challenges in exascale computing and energy-efficient design.

Arindam MukherjeeView profile

Associate Professor

• Internet of Things (IoT)
• Fog Computing
• Real-Time Systems
• +4 more

Dr. Arindam Mukherjee serves as an Associate Professor in the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte, College of Engineering. His office is located in EPIC 2336, and he can be reached at amukherj@charlotte.edu or by phone at 704-687-8417. His educational qualifications are as follows: Ph.D. from the University of California at Santa Barbara (2002) M.S. from the University of California at Santa Barbara (2000) B.Tech. from Jadavpur University, India (1996) Dr. Mukherjee's research spans Smart System Architectures, Internet of Things (IoT), and Fog Computing. He investigates cooperative and autonomous mobile systems, real-time system software, and database management for Big Data. His work includes scheduling algorithms for IoT systems and the integration of edge, fog, and cloud computing paradigms for real-time applications in the Big-Squared Data space. His publication record from 2003 to 2018 shows an evolution from VLSI design and bioinformatics to contemporary IoT and fog computing. Early work focused on logic synthesis, biochip testing, and FPGA-based bioinformatics implementations, while recent contributions address power management in heterogeneous processors, energy-efficient communications for smart buildings, and the synergistic integration of edge, fog, and cloud computing for real-time IoT data processing. No scientific awards are mentioned in the provided text. There is no information available regarding students advised or research grants. Similarly, no specific research labs or collaborative teams are described in the source material.

• Nanoscale CMOS architectures and circuits
• Frequency synthesizers
• Transmitters and receivers
• +3 more

Prof. Robert Staszewski is a Full Professor at the School of Electrical and Electronic Engineering, University College Dublin (since 2014) and a Visiting Full Professor at Delft University of Technology (since 2009). His academic journey began with a PhD from University of Texas at Dallas (2002), preceded by MSEE (1992) and BSEE (1991) degrees. He previously worked at Alcatel (1991–1995) and Texas Instruments (1995–2009), where he co-founded the Digital RF Processor (DRP) group and served as CTO (2007–2009). Research Focus : Nanoscale CMOS architectures, quantum computing hardware, millimeter-wave PLLs, and low-power IoT RF circuits. Recent Publications : 15 most recent works span quantum dots in 22nm FDSOI, harmonic predistortion in ADPLLs, ultra-low-jitter charge-sharing PLLs, and RF reuse strategies for IoT. Scientific Contributions include 6 books, 11 book chapters, 150+ journal papers, and 210 US patents. His Equal1 Labs co-founded in 2014 aims to build the first single-chip CMOS quantum computer. Awards: 2012 IEEE Circuits and Systems Industrial Pioneer Award IEEE Fellow (2009) Teaching Leadership : Coordinates advanced modules in Analogue Integrated Circuits , Mixed-Signal Circuits , and Quantum Computing (2014–2025). Supervises PhD thesis projects in nanoscale RF and quantum systems.

Bakhrom OripovView profile

Research Fellow

• Superconducting Single-Photon Detector Arrays
• Superconducting Electronics
• Neuromorphic Hardware
• +3 more

Bakhrom Oripov is a Research Fellow at the University of Colorado Boulder , affiliated with the Quantum Nanophotonics Group , and a Researcher at the Applied Physics Division of the National Institute of Standards and Technology (NIST) in Boulder, Colorado. B.S. in Physics, Bogazici University, 2012 Ph.D. in Condensed Matter Physics, University of Maryland, 2020 His research focuses on Superconducting Single-Photon Detector Arrays , Superconducting Electronics , and Neuromorphic Hardware , with applications in UV astronomy , bio-optical devices , and energy-efficient AI . He develops scalable readout architectures for mega-pixel superconducting nanowire arrays and explores general training techniques for hardware neural networks . Recent publications highlight advancements in thermally coupled imager designs and gradient descent methods without backpropagation , emphasizing low-energy data routing and bio-inspired hardware scalability . His work has been featured in Nature and Applied Physics Letters as a Cover of the Issue and Featured Article .

Mona JarrahiView profile

Professor

• Terahertz Electronics
• Millimeter-wave Optoelectronics
• Microwave Photonics
• +3 more

Mona Jarrahi is a Professor in the Department of Electrical and Computer Engineering at the Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles (UCLA). Holding the Northrop Grumman Chair in Electrical Engineering, she leads groundbreaking research in terahertz/millimeter-wave electronics, microwave photonics, and AI-driven imaging systems. Terahertz Electronics Millimeter-wave Optoelectronics Microwave Photonics Imaging and Spectroscopy Systems AI-Driven Optical Imaging Her recent publications highlight advancements in terahertz plasmonic focal-plane arrays, single-pixel diffractive terahertz processors, and coherent terahertz synthesis. These works span keywords like Optoelectronics , Signal Processing , and Machine Learning , with sub-fields focusing on Plasmonics , Pixel-level Resolution , and Diffractive Neural Networks . Scientific Awards: Fellow of IEEE, AAAS, APS, Optica, SPIE, and IOP Guggenheim Fellowship SPIE Quantum Sensing Achievement Award IEEE Photonics Society Aron Kressel Award Moore Inventor Fellowship As head of the Terahertz Electronics Laboratory at UCLA, she drives innovations in terahertz technologies with applications in medical imaging, security, and deep-space exploration. Her work includes room-temperature terahertz sensors and photodetectors with 50 GHz speeds.

• Information Security
• Cryptology
• Embedded Systems
• +5 more

Prof. Dr. Sıddıka Berna Örs Yalçın is a Professor at Istanbul Technical University , Faculty of Electrical and Electronics Engineering, Department of Electronics and Communication Engineering since 2020. She holds a PhD from Katholieke Universiteit Leuven (1999) and has maintained continuous academic engagement in cryptology, embedded systems, and hardware security. Education: PhD in Electrical Engineering, Katholieke Universiteit Leuven (1999) Master's in Electronics and Communications Engineering, Istanbul Technical University (1995) Licence in Electronics and Communication Engineering, Istanbul Technical University (1995) Her research focuses on post-quantum cryptography , side-channel attack mitigation , and hardware implementation for security systems. Recent work includes FPGA-based AI accelerators, IoT power consumption modeling, and quantum-resistant cryptographic algorithms. Current projects center on RISC-V processor optimization, embedded security, and hardware implementations for 5G communications. Her Scopus h-index is 17 with over 1353 citations, reflecting her impact in computer hardware and cryptographic engineering domains. Notable Research Outputs: Quantum tent map-based S-box designs for image encryption (2024) Post-quantum modular multiplication algorithms (2024) RISC-V implementation of CRYSTALS-Kyber (2023) IOT power consumption estimation frameworks (2024)

• Programming Languages
• Compiler Technology
• Reversible Computation
• +5 more

Torben Ægidius Mogensen is an Associate Professor at the Department of Computer Science, University of Copenhagen, where he leads research in the Programming Languages and Theory of Computation section. His office is located at Universitetsparken 5, Copenhagen. His primary research focuses on: Automatic program analysis and transformation (especially partial evaluation and semi-inversion) Compiler technology for functional languages Domain-specific language design Reversible computing systems and languages Algorithms, complexity theory, and automata theory Applications in graphics and fractal generation His recent publications demonstrate a strong focus on reversible computation systems, including specialized programming languages like Hermes for encryption, reversible processor architectures, and functional programming extensions. His textbook publications on compiler design (2024) and programming language implementation (2022) indicate significant contributions to computer science education and foundational knowledge. He teaches courses on compilers, programming language technology, and game development, and maintains active research collaborations internationally. He is fluent in Danish and English, with working knowledge of German and Romanian.

• Computer Architecture
• Memory Systems
• Reconfigurable Computing
• +6 more

Ronald Dreslinski is a Professor in the Department of Computer Science and Engineering at the University of Michigan, College of Engineering. His work focuses on computer architecture, memory systems, and reconfigurable computing, with applications in machine learning, wireless communication, and autonomous systems. Research spans hybrid memory systems, fault-tolerant networks, and low-power processors Key technologies include PIM (Processing-in-Memory), systolic arrays, and Galois field accelerators His publications highlight trends in adapting reconfigurable architectures for sparse data, optimizing wireless communication decoders, and integrating neural networks with traditional circuit design. He mentors PhD students through weekly 1-on-1 meetings, project-specific sessions, and group presentations. The department emphasizes broadening participation in computing and student support through community initiatives.