Aurora Maccarone serves as an RAEng Research Fellow within the Institute of Photonics and Quantum Sciences at Heriot-Watt University's School of Engineering & Physical Sciences. Her work focuses on advanced photonics applications for challenging environments, particularly underwater and obscured conditions. Her research expertise spans: Single-photon LiDAR systems for underwater 3D imaging Photon-counting detector arrays for depth profiling Real-time reconstruction algorithms for obscurant-penetrating imaging Quantum sensing applications in marine environments Recent publications demonstrate consistent innovation in single-photon imaging techniques, with emphasis on underwater applications (2023-2024) and obscurant penetration (2022). Her work shows strong interdisciplinary connections between optical engineering, computational imaging, and environmental sensing. Key publications reveal growing impact in underwater LiDAR technology, with multiple high-citation papers on photon-efficient imaging systems. Dr. Maccarone actively supervises PhD students and has created significant research datasets. Her collaborations span international institutions, with notable contributions to sensor hardware development and computational imaging algorithms. Recent work shows increasing integration of machine learning techniques with traditional photon-counting approaches.
Prof. Dr. Tobias Gemmeke is a University Professor at RWTH Aachen University's Faculty of Electrical Engineering and Information Technology, leading the Chair of Integrated Digital Systems and Circuit Design. His work focuses on neuromorphic computing, hardware accelerators, and energy-efficient electronics. He has pioneered advancements in FPGA-based computational neuroscience simulators, neuromorphic processor architectures, and sensor integration for industrial and medical applications. Research interests include time-domain computing, ReRAM reliability, and co-optimization of neural networks with hardware. Notable contributions include the neuroAIx framework for accelerated neuroscience simulations and energy-efficient ASIC designs for post-quantum cryptography. He actively explores memristive devices and domain generalization techniques for edge computing. Recent publications highlight innovations in spiking neural networks, sensor systems for plain bearings, and time-domain compute-in-memory engines. His work bridges theoretical neuroscience with practical hardware implementations, emphasizing scalability and real-time performance.
Azad J Naeemi is a Professor holding the Dean's Professorship in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He serves as Editor-in-Chief of the IEEE Journal on Exploratory Computational Devices and Circuits and Associate Director for Computation of the NSF-supported National Nanotechnology Coordinated Infrastructure (NNCI). His educational background includes a B.S. in Electrical Engineering from Sharif University (1994) and M.S./Ph.D. in Electrical and Computer Engineering from Georgia Tech (2001/2003). Prior to academia, he worked as a design engineer in Tehran (1994-1999) and as a research engineer at Georgia Tech's Microelectronics Research Center (2004-2008). Professor Naeemi's research spans nanotechnology with focus on emerging nanoelectronic devices, spintronics, ferroelectric devices, and design technology co-optimization for CMOS/beyond-CMOS technologies. His work bridges materials, devices, circuits, and systems, particularly investigating integrated circuits based on nanoscale devices and interconnects. Educational research includes experiential learning environments for engineering education. Recent publications (2024-2025) demonstrate strong emphasis on spin-orbit torque MRAM, ternary content addressable memories, ferroelectric/antiferroelectric devices, and plasmonic circuits. Key trends include energy-efficient hardware accelerators, neuromorphic computing applications, and compact modeling for advanced technology nodes. His scientific honors include: IEEE Solid-State Circuits Society James Meindl Innovators Award (2022) IEEE Electron Devices Society Paul Rappaport Award (2008) NSF CAREER Award (2013) SRC Inventor Recognition Award (2010) Multiple Georgia Tech teaching awards Professor Naeemi leads research supported by NSF (including NNCI infrastructure) and SRC. His editorial role with IEEE JXCDC positions him at the forefront of exploratory computational devices. He previously served as General Co-Chair for the IEEE International Interconnect Technology Conference (2013). His work connects with Georgia Tech's Microelectronics Research Center and national nanotechnology initiatives through the NNCI network, focusing on computational infrastructure for nanoscale device characterization and design.
Michal Lipson serves as the Eugene Higgins Professor of Electrical Engineering and Professor of Applied Physics at Columbia University's Fu Foundation School of Engineering and Applied Science. Elected to both the National Academy of Engineering and National Academy of Sciences, she pioneered critical building blocks in silicon photonics that have transformed the field, with over 50,000 related publications annually. Her research has generated more than 250 scientific publications and 45 issued patents. Lipson's research focuses on nanophotonics and silicon photonics, where she demonstrated the ability to tailor electro-optic properties of silicon in landmark 2004 and 2005 Nature papers. Her work has enabled the development of photonic devices and circuits that now form the foundation of over 1,000 papers published yearly. She investigates novel optical phenomena while developing practical applications that address major bottlenecks in microelectronics. Her research spans fundamental physics to practical device implementation, with particular emphasis on integrated photonic systems. Analysis of her recent publications reveals a strategic expansion from foundational silicon photonics into emerging applications including quantum information processing, machine learning acceleration, biomedical sensing, and topological photonics. While maintaining core expertise in silicon-based devices, her work increasingly incorporates 2D materials, heterogeneous integration, and novel optical phenomena to push performance boundaries. The research demonstrates consistent progression from fundamental device physics to system-level implementations with practical applications. National Academy of Engineering (2025) National Academy of Sciences MacArthur Fellowship Blavatnik Award Optica's R.W. Wood Prize IEEE Photonics Award John Tyndall Award NAS Comstock Prize in Physics Thomson Reuters Top 1% Highly Cited Researcher (annually since 2014) Professor Lipson has mentored an exceptional research group, graduating 40 PhD students and 2 MS students, with numerous postdocs and visiting researchers. Her alumni occupy prominent positions including professorships at major universities (Rochester, Ottawa, UNICAMP, Johns Hopkins), leadership roles at Intel, Bell Labs, and startups she co-founded (HyperLight, Voyant Photonics). Her laboratory has received substantial research funding supporting cutting-edge work in nanofabrication, optical characterization, and device development. Current research directions include quantum photonics, AI-accelerated optical systems, and novel materials integration. The Lipson Research Group operates state-of-the-art facilities for nanophotonic device design, fabrication, and characterization. The team comprises principal investigators, postdoctoral researchers, PhD students, and administrative staff working collaboratively across disciplines including electrical engineering, materials science, physics, and applied physics. The group maintains strong industry partnerships while pursuing fundamental scientific advances in light-matter interactions at the nanoscale.
Professor Terry Rudolph is a Professor of Quantum Physics at the Department of Physics within the Faculty of Natural Sciences at Imperial College London. His affiliations include the Quantum Engineering, Science and Technology group, Quantum Optics and Laser Science Group, and The Light Community. His research focuses on quantum-anything, encompassing optical physics, quantum computing, photonics, and related interdisciplinary fields such as nanotechnology and communications technologies. Rudolph’s work emphasizes photonic quantum computing architectures, entanglement generation, and fault-tolerant quantum systems. His recent publications highlight advancements in cluster state generation, photonic multiplexing, and reconfigurable entangling systems. He has contributed to scalable quantum hardware design, including silicon photonic platforms and error-correction protocols. His academic contributions span theoretical and experimental quantum mechanics, with a focus on bridging quantum theory and practical implementation. Notable themes in his research include deterministic teleportation, photonic integrated circuits, and fusion-based quantum computing. He has also engaged in educational initiatives to introduce quantum information science to high-school students. Affiliations: Quantum Optics and Laser Science Group, Quantum Engineering Centre, and The Light Community at Imperial College London.
Prakash Murali is an Associate Professor in the Department of Computer Science at Cambridge University, specializing in quantum computing, quantum architecture, and resource estimation. He previously worked as a quantum architect at Microsoft, where he contributed to the Azure Quantum Resource Estimator. He earned his Ph.D. in Computer Science from Princeton University in 2021, with a dissertation recognized by the ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award. His research focuses on bridging the gap between quantum algorithms and hardware through compiler and architecture innovations. His awards include the ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award (2022), Communications of ACM Research Highlights (2022), and the IBM PhD Fellowship (2021). He leads a research group comprising PhD students (e.g., Sanaa Sharma and Dmitry Filippov), MPhil candidates, and undergraduate researchers. Key contributions include the TriQ compiler framework for quantum systems and the TimeStitch technique for decoherence mitigation. His work has been adopted in industry compilers and has influenced quantum benchmarking practices.
Jon Schuller is a Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB), within the College of Engineering. His research focuses on nanophotonics, metamaterials, plasmonics, and their applications in energy-efficient technologies such as photovoltaics, thermal management systems, and advanced optical devices. He leads the Schuller Lab, which explores engineered metasurfaces and naturally occurring materials to control light-matter interactions at subwavelength scales. His work bridges fundamental science (e.g., quantum phenomena in hybrid perovskites) and engineering (e.g., reconfigurable semiconductor meta-optics). He is affiliated with the California NanoSystems Institute (CNSI) and actively contributes to interdisciplinary research initiatives. Contact: jonschuller@ece.ucsb.edu, Office 3221C Engineering Science Building. Research interests include directional light emission control via metasurfaces, thermal radiation tuning using phase-change materials, and the development of high-efficiency photonic devices. His lab emphasizes fabrication and characterization of nanophotonic structures, with applications ranging from space technology to exoplanet imaging systems. Recent efforts focus on electrically tunable metasurfaces and multipolar optical phenomena in layered materials. Key technical contributions involve designing reconfigurable optical antennas, optimizing metasurface-based LEDs, and exploring magnetic dipole emission in 2D perovskites. His team collaborates across disciplines to address challenges in energy, aerospace, and quantum technologies. Current opportunities include postdoctoral positions in nonlinear optics and photonics.
Crystal Noel is an Assistant Professor at Duke University in the Pratt School of Engineering and Trinity College of Arts & Sciences , with appointments in both the Department of Electrical and Computer Engineering and Physics since 2022. She is also a Member of the Duke Quantum Center since 2024. Ph.D. in Electrical and Computer Engineering from University of California, Berkeley (2019) B.S. in Massachusetts Institute of Technology (2013) Her research focuses on quantum computing and simulation with trapped ions , integrated photonics for scalable trapped ion systems , and electric-field noise from surfaces . Recent work includes developing non-invasive mid-circuit measurement techniques, sympathetic cooling for ion chains, and cross-platform quantum state comparison. She has secured significant grants from National Science Foundation , Rochester Institute of Technology , and Defense Advanced Research Projects Agency for quantum co-design and networking projects. Her lab ( Noel Lab ) explores scalable quantum computing architectures and surface noise mitigation. She teaches courses ranging from foundational Fields and Waves: Fundamentals of Information Propagation to advanced topics in Quantum Engineering with Atoms and Advanced Topics in Electrical and Computer Engineering .
Georges Kaddoum is a Professor at École de technologie supérieure (ÉTS) , specializing in Electrical Engineering. He holds the Canada Research Chair in Unlocking the Power of IoT 6G-Networks and the LACIME – Communications and Microelectronic Integration Laboratory affiliation. His work bridges wireless communications, IoT, and machine learning. Research Interests include wireless communication systems, physical layer security, machine learning for networking, and 6G technologies. He focuses on optimizing network performance in challenging environments (impulsive noise, underwater, non-terrestrial networks) and developing AI-driven solutions for jamming mitigation, resource allocation, and secure IoT frameworks. Recent Publications highlight 6G-enabled vehicular networks, quantum-safe blockchain integration, federated learning for transportation systems, and deep learning-based receivers for chaotic communication systems. His work emphasizes semantic communication, interference management, and digital twin applications. Awards IEEE TCSC Award for Excellence in Scalable Computing (2022) Prix d’excellence de la relève (Université du Québec, 2018) Prix d’excellence en recherche (ÉTS, 2018) Multiple IEEE Exemplary Reviewer and Best Paper Awards (2014–2022) Supervision includes 15+ PhD/Master’s students working on topics like index modulation, physical layer security, UAV communications, and intelligent resource management. Research Units Ultra Research Chair on Intelligent Tactical Wireless Networks LACIME Laboratory Canada Research Chair in IoT 6G-Networks
Henry Corrigan-Gibbs is an Assistant Professor in MIT's Department of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). He leads research in computer security, cryptography, and privacy-preserving systems. His work focuses on practical cryptographic systems that empower users while maintaining strong security guarantees. Notable contributions include the Tiptoe private search engine, Prio for privacy-preserving data aggregation, and Larch for secure authentication. His research has influenced industry standards at Apple, Google, and Mozilla, and has been recognized with awards such as the Best Young Researcher Paper at Eurocrypt and the Caspar Bowden Award. Education: PhD in Computer Science (Stanford University, advised by Dan Boneh), Postdoc at EPFL (hosted by Bryan Ford). B.S. in Computer Science from Yale University. Research Interests: Private Information Retrieval, Secure Authentication, Cryptographic Systems, Privacy-Preserving Analytics, and Hardware Security. His lab collaborates with PDOS and CSS research groups at MIT and co-hosts the MIT Security Seminar series. Grants and Funding: Supported by industry and government agencies (details in paper acknowledgments). Teaching roles include co-instructor for Applied Cryptography (6.5610) and Foundations of Computer Security (6.1600). Key Projects: Prio (used in iOS/Android), Tiptoe (private web search), Larch (backdoor-resistant authentication), and Whisper/Poplar systems for private data aggregation. His team includes postdocs, PhD students, and undergrad researchers working on cutting-edge cryptographic protocols.
Michela Becchi is an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University. She specializes in computer architecture, systems software, and applications, with a focus on heterogeneous systems, parallel algorithms, and acceleration techniques for bioinformatics, pattern recognition, and quantum computing. Her work spans multi-core CPUs, GPUs, FPGAs, and distributed clusters, emphasizing the boundary between hardware and software design. Dr. Becchi holds a Ph.D. and Master’s degree in Computer Engineering from Washington University in St. Louis (2009) and a Bachelor’s degree in Computer Engineering from Politecnico di Milano, Italy (2000). Her research has been recognized with prestigious awards, including the NSF CAREER Award (2015) and the University of Missouri System President Award for Early Career Excellence (2016). Her research interests include compiler and runtime techniques for heterogeneous systems, acceleration of bioinformatics algorithms, and high-speed networking applications. She has pioneered frameworks for efficient data transformation, GPU-accelerated compression, and memory-efficient graph algorithms for quantum computing. Her work also explores thread coarsening, mixed-precision auto-tuning, and secure multi-core processor design. Key contributions include the PILOT runtime system for GPU memory management, the GPU-FPtuner auto-tuner for floating-point applications, and innovative approaches to automata processors for genomic analysis. Her publications emphasize reproducible accuracy in scientific simulations and the optimization of irregular applications on many-core platforms.
Nathan Youngblood is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh , with a secondary appointment in the Department of Physics and Astronomy . His research focuses on reconfigurable photonic materials and devices for energy-efficient artificial intelligence applications. Educational Background: PhD in Electrical Engineering from the University of Minnesota Postdoctoral research at the University of Oxford (2017–2019) His work explores photonic in-memory computing, neuromorphic systems, and phase-change materials to minimize computing latency and energy consumption. Recent publications highlight advancements in magneto-optical non-reciprocity, coherent crossbar arrays, and plasmonic-enhanced phase-change devices. Scientific Awards: NSF CAREER Award (2024) AFOSR Young Investigator Award (2024) William Kepler Whiteford Faculty Fellowship (2024) Dr. Youngblood's lab develops photonic accelerators like LightML and LightBulb for machine learning, emphasizing scalable integration and novel material applications in silicon photonics.
Petteri Nurmi is a Professor of Computer Science at the University of Helsinki, affiliated with the Department of Computer Science and the Helsinki Institute of Sustainability Science (HELSUS). His research focuses on IoT systems, environmental monitoring, AI-driven solutions, and sustainable computing. He leads projects such as the NordForsk-funded initiative (2024-2028) and the Team Finland Knowledge programme (2024-2026), emphasizing large-scale IoT deployments and quantum computing integration. Key research interests include drone-based air quality monitoring, low-cost sensor networks, and AI applications in environmental science. Nurmi has published extensively in top venues like IEEE IoT Journal and ACM workshops. His work bridges technical innovation with societal challenges, such as urban pollution reduction and sustainable resource management. He supervises doctoral students in the Computer Science program and collaborates internationally on projects like underwater plastic detection (SEAGULL) and smart city infrastructure. Nurmi’s contributions to edge computing and pervasive sensing have been recognized through grants totaling over €2M. His lab develops tools for data-intensive systems, including thermal imaging for energy efficiency analysis and AI-driven sensor fusion frameworks.
Eugene Tang is an Assistant Professor in the Department of Mathematics and Physics at Northeastern University. His research focuses on quantum information theory and the theoretical limitations of quantum computing, particularly quantum error correction and efficient protocols using high-rate codes. He received his PhD from the California Institute of Technology in 2021. Dr. Tang's research interests include quantum error correction, the development of efficient quantum protocols surpassing conventional schemes, and the study of quantum algorithms such as QAOA. He explores the theoretical boundaries of quantum computing, with a focus on optimizing error detection and decoding methods for quantum LDPC codes and subsystem codes. His work also intersects with quantum gravity, particularly in the context of black hole interiors and bulk geometry construction through tensor methods. His recent publications highlight advancements in quantum error correction, including optimal locality in subsystem codes and efficient decoding strategies for quantum LDPC codes. His work on variational quantum optimization addresses challenges in scalability, such as QAOA's performance at large qubit scales and symmetry-related obstacles. Earlier contributions include research on superoscillations and hybrid quantum-classical algorithms for graph coloring. No scientific awards or grants are explicitly mentioned in the provided information. No specific labs or teams are associated with his work in the given data.
Olivia Di Matteo serves as an Assistant Professor in the Department of Electrical and Computer Engineering within UBC's Faculty of Applied Science, leading the Quantum Software and Algorithms Research (QSAR) group since her January 2022 appointment. Her academic foundation includes a BSc from Lakehead University and MSc/PhD in Physics (Quantum Information) from the University of Waterloo, completed in 2019. Dr. Di Matteo's research centers on quantum software engineering , with pioneering work in quantum compilation , circuit optimization , and debugging tools . She champions open-source quantum frameworks and develops accessible educational resources to democratize quantum computing. Analysis of her 15 most recent publications (2021-2025) reveals dominant trends in quantum programming infrastructure, particularly circuit analysis (33%), bug classification (20%), and qubit network optimization (15%), with strong emphasis on practical software tooling over theoretical physics. No scientific awards were documented in the source materials. She advises graduate students in the QSAR group while contributing to open-source quantum ecosystems through projects like PennyLane and The Ionizer transpiler, and teaches courses including CPEN 400Q (Gate-model quantum computing) and ELEC 221 (Signals and Systems). The QSAR group operates at the intersection of quantum software development and education, focusing on making quantum programming accessible through visual tools, real-time debugging environments, and hardware-agnostic compilation techniques.
