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Jingtong Hu is an Associate Professor at the Swanson School of Engineering, University of Pittsburgh, where he also holds the William Kepler Whiteford Faculty Fellowship. His research focuses on Cyber-Physical Systems and Infrastructure Security, with significant contributions to embedded systems, non-volatile memory architectures, and hardware/software co-design for energy-constrained environments. Dr. Hu received his PhD from the University of Texas at Dallas (2007-2013) and his Bachelor of Engineering from Shandong University (2003-2007). His research spans multiple interdisciplinary areas including energy harvesting systems, non-volatile processors, FPGA acceleration, and machine learning at the edge. His recent publications demonstrate a strong focus on algorithm-hardware co-design, particularly for vision transformers, federated learning, and non-volatile memory systems. His work often addresses the challenges of implementing AI on resource-constrained edge devices, with emphasis on energy efficiency, reliability, and performance optimization. The trend in his publications shows increasing focus on sustainable AI processing, heterogeneous computing architectures, and personalized machine learning for IoT applications. Selected Awards: IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award (2021) ACM SIGDA Meritorious Service Award (2019) Multiple Best Paper Award nominations at top conferences including DAC, ASP-DAC, and CODES+ISSS Dr. Hu's research has been supported by multiple grants focusing on energy-efficient computing, non-volatile memory systems, and hardware acceleration for machine learning. His collaborative work spans numerous institutions and involves interdisciplinary teams working at the intersection of computer architecture, embedded systems, and artificial intelligence. His publications show extensive collaboration with researchers at the University of Pittsburgh, particularly with Albert K. Jones and Yiyu Shi. His laboratory work focuses on implementing practical systems for energy harvesting powered devices, non-volatile processors, and hardware accelerators for machine learning applications. Current projects appear to emphasize sustainable AI processing at the edge, heterogeneous FPGA acceleration, and personalized federated learning for health monitoring applications.

• Cyber-Physical Systems
• Infrastructure Security
• Non-Volatile Memory Systems
• +6 more

Daniel J. Sorin is a Professor of Electrical and Computer Engineering at Duke University's Pratt School of Engineering, where he also serves as Associate Chair of Education. He holds joint appointments in both the Electrical and Computer Engineering department and Computer Science department, and is recognized as a Bass Fellow for his contributions to education and research. His research focuses on computer architecture with specific expertise in memory systems, cache coherence protocols, fault tolerance, and verification-aware design. Dr. Sorin's work bridges theoretical computer architecture with practical implementations, often incorporating coding theory to solve architectural challenges. His research group has made significant contributions to automated protocol generation, hardware acceleration, and robot motion planning systems. Dr. Sorin's publications reveal a consistent focus on memory consistency models, cache coherence protocols, and verification techniques. His recent work has expanded into robot motion planning acceleration, FPGA resource management, and novel error correction techniques for emerging memory technologies. The trend shows increasing interdisciplinary work connecting computer architecture with robotics and machine learning applications. Program Chair of HiPEAC 2017 Co-chair of IEEE Micro's Top Picks selection committee (2016) Lois and John L. Imhoff Distinguished Teaching Award (2011) NSF CAREER Award recipient IEEE Micro Top Pick awards (2011, 2015) ACM Senior Member As an advisor, Dr. Sorin has mentored numerous PhD students who have gone on to successful careers at leading technology companies including Google, Microsoft, Oracle, and Nvidia. His research group maintains strong industry connections and has produced influential work in cache coherence protocols, memory systems, and fault-tolerant architectures. He has also authored the widely-used textbook 'A Primer on Memory Consistency and Cache Coherence' (2nd edition). Dr. Sorin leads an active research laboratory focused on next-generation computer architecture challenges, with ongoing projects in hardware acceleration, memory systems, and robot motion planning. His group collaborates with researchers across multiple disciplines including robotics, coding theory, and semiconductor design.

• Computer Architecture
• Memory Systems
• Cache Coherence Protocols
• +7 more

Giovanna Turvani is an Associate Professor at the Department of Electronics and Telecommunications (DET) at Politecnico di Torino, with affiliations in both the College of Electronic, Telecommunications and Physics Engineering and the College of Computer, Film, and Mechatronics Engineering. Scientific Branch: IINF-01/A - Electronics ERC Sectors: PE7_4, PE7_11, PE6_1, PE6_14, PE7_3 SDG Goals: Quality Education, Gender Equality, Affordable Energy, Industry Innovation Her research focuses on advanced electronics and quantum technologies, including: Logic-in-memory computing Quantum computing architectures Microwave imaging for medical and agricultural applications CAD tools for emerging nanotechnologies Embedded systems for bee health monitoring IoT solutions for bio-waste valorization Publications show strong expertise in quantum computing, nanocomputing, and microwave imaging, with recent trends emphasizing quantum optimization frameworks, in-memory architectures, and IoT-based agricultural technologies. She supervises PhD students in areas like quantum machine learning algorithms, predictive on-board systems, and quantum hardware design. Collaborations span multiple disciplines, including medical device development and agricultural electronics. Patents include innovations in microwave imaging, racetrack memory logic functions, and in-memory computing devices.

• CAD tools
• Digital architectures
• Emerging technologies
• +9 more

Laurent Bellaiche is a Distinguished Professor in the Department of Physics within the College of Arts and Sciences at the University of Arkansas. His research focuses on computational condensed matter physics with emphasis on ferroelectrics, multiferroics, and semiconductor materials. He leads the Computational Condensed Matter Physics (CCMP) Group and serves as a founding member of the Smart Ferroic Materials Center. His primary research interests include: Developing first-principles methods for predicting properties of ferroelectrics and multiferroics Investigating topological defects, spin liquids, and magnetic skyrmions Studying non-equilibrium effects for neuromorphic computing applications Optimizing electro-optic, electrocaloric, and piezoelectric effects Designing antiferroelectrics for high-energy-density applications Professor Bellaiche's recent publications (2024-2025) demonstrate significant activity in topological polar structures, skyrmion engineering, strain-induced phenomena, and computational design of functional materials. His work shows strong interdisciplinary connections between condensed matter theory, materials science, and device physics with particular emphasis on emergent topological phenomena in low-dimensional systems. Scientific awards include: Twenty-First Century Professorship in Nanotechnology and Science Education NSF CAREER Awardee Bellaiche maintains active collaborations with experimental groups internationally, particularly with CentraleSupélec in France. He is involved in innovative educational initiatives including a course titled "Thinking Outside the Box: Physics, Soccer and much more" and contributes to the Soccernostalgia podcast. His research group emphasizes both fundamental theoretical advances and practical applications in next-generation electronic and energy materials.

• Computational Condensed Matter Physics
• Ferroelectrics
• Multiferroics
• +7 more

Hai (Helen) Li is a Professor and Clare Boothe Luce Associate Chair at Duke University's Electrical and Computer Engineering department. She was a TUM-IAS Hans Fischer Fellow (2017) hosted by Prof. Ulf Schlichtmann in the Neuromorphic Computing focus group. Education: B.S./M.S. from Tsinghua University, Ph.D. from Purdue University Positions: Qualcomm, Intel, Seagate, Polytechnic Institute of New York University, University of Pittsburgh Her research spans neuromorphic computing systems , machine learning acceleration , emerging memory technologies , and low-power circuits . Publications demonstrate expertise in ReRAM/memristor-based accelerators, sparse neural networks, and processing-in-memory architectures. Key contributions include cross-layer optimization frameworks and robust neuromorphic designs. Her awards include: 9 Best Paper Awards (ASPDAC, ICMLA, ISVLSI, etc.) NSF Career Award DARPA Young Faculty Award IEEE Fellow (2019) ACM Distinguished Member (2017) IEEE TCSDM Outstanding Leadership Award (2021)

• Neuromorphic Computing
• Machine Learning
• Emerging Memory Technologies
• +3 more

Börge Göbel is a postdoctoral researcher at the Institute of Physics, Martin Luther University Halle-Wittenberg, within the Quantum Theory of the Solid State group led by Prof. Ingrid Mertig. He is affiliated with the Faculty of Natural Sciences II - Chemistry, Physics and Mathematics and conducts theoretical research in condensed matter physics, focusing on topological spin textures and their applications in spintronics and orbitronics. PhD in Physics (summa cum laude, 2020), Max Planck Institute Halle MSc in Physics (1.1, 2016), Martin Luther University Halle-Wittenberg BSc in Physics (1.2, 2014), Martin Luther University Halle-Wittenberg Abitur (1.0, 2011) His research centers on the interplay between topology and transport in magnetic systems, particularly skyrmions, antiskyrmions, bimerons, and hopfions. He investigates their stability, emergent electrodynamics (e.g., topological Hall effect), and dynamics under current drive, with applications in racetrack memory, neuromorphic computing, and quantum devices. A major focus is on two-dimensional materials and electron gases, where he studies spin- and orbital-to-charge interconversion. He has pioneered work in orbitronics, demonstrating the orbital Hall effect accompanying the quantum Hall effect and topological orbital Hall effects in skyrmion systems. The most recent publications show a strong trend toward the exploration of orbital angular momentum in quantum transport, the stabilization of skyrmions in van der Waals materials, and the development of neuromorphic computing concepts using biskyrmions. His work bridges fundamental theoretical insights with potential technological applications in next-generation electronics. Börge Göbel is funded by the EIC Pathfinder OPEN Grant "Orbital engineering for innovative electronics" and is a co-supervisor in the EU Horizon 2020 project "SPEAR". He has co-supervised 2 PhD, 2 master's, and 4 bachelor's students and teaches quantum mechanics, including online courses with over 30,000 participants. Co-PI, EIC Pathfinder OPEN Grant: "Orbital engineering for innovative electronics" Co-Supervisor, EU Horizon 2020 project "SPEAR" Network Postdoc, EU project "OBELIX" He collaborates extensively with experimental groups worldwide, including those of Prof. Stuart Parkin, Prof. Claudia Felser, Dr. Manuel Bibes, and Prof. Albert Fert, and has presented at major conferences such as MMM, JEMS, Gordon, DPG, and SPICE.

• Condensed Matter Physics
• Topological Spin Textures
• Skyrmions
• +9 more

Yongmei M. Jin is a Professor in the Department of Materials Science and Engineering at Michigan Technological University (MTU), affiliated with the College of Engineering. She holds a PhD in Materials Science and Engineering from Rutgers University. Her research focuses on microstructure evolution in crystalline solids, solid-state phase transformations, magnetic domains, computational materials science, and single crystal diffraction techniques. Notable work includes studies on magnetic domain boundary dynamics in Fe-Ga alloys, electric field control of magnetism at material interfaces, and phase field modeling of microstructural evolution. Selected publications demonstrate expertise in modeling material behavior under external stimuli (e.g., electric fields, currents) and analyzing microstructural changes at atomic and macroscopic scales. Teaching responsibilities include courses on materials processing, mechanical behavior of materials, and transmission electron microscopy.

• Microstructure Evolution
• Solid State Phase Transformations
• Magnetic Domains
• +3 more

Marco Vacca is an Associate Professor in the Department of Electronics and Telecommunications (DET) at Politecnico di Torino and a member of the Interdepartmental Center PIC4SeR - PoliTO Interdepartmental Centre for Service Robotics. His work bridges electronics, nanotechnology, and computing architecture with a focus on innovative solutions to the memory wall problem. His research spans Logic-in-memory computing, Machine learning hardware acceleration, and Nanocomputing with specific emphasis on circuit architectures for probabilistic computing, magnetic devices, hybrid technologies integration, and CAD tools for emerging technologies. Dr. Vacca leads research in RISC-V extensions, hardware accelerators for AI, and autonomous robot systems for agricultural applications through the VLSILAB research group. Recent publications reveal a strong trend toward solving fundamental computing challenges through nanoscale innovations, particularly in memory-centric architectures, molecular field-coupled computing, and novel transistor technologies. His work demonstrates how logic-in-memory approaches can overcome traditional von Neumann limitations while improving energy efficiency for AI workloads. Editorial board member of ELECTRONICS (2021-2023) Program committee member for Design, Automation and Test in Europe Conference (DATE) 2020-2021 Dr. Vacca supervises PhD student Alessandro Varaldi working on 'Hardware AI Accelerators for Automotive Applications' and has led significant research projects including 'Device for Storage and Processing Data and Related Method' (2020-2021) and 'Quantum Computing and Quantum Communication: State of the Art and Applications in the Telco Sector' (2020). His grant portfolio shows strong industry and competitive funding support. As a core member of the VLSILAB research group, Dr. Vacca contributes to advancing VLSI theory and design applications with particular focus on implementing Big Data, Machine Learning, and Neural Networks in specialized hardware architectures that push the boundaries of conventional computing.

• Logic-in-memory
• Machine learning
• Nanocomputing
• +7 more

Dr. Alex K. Jones is a Professor in the Department of Physics & Astronomy at the University of Pittsburgh, with a secondary appointment. His research focuses on quantum computing architectures, sustainable computing, and emerging memory technologies. He leads projects funded by NSF, DARPA, NSA, ARO, and industry, emphasizing energy-efficient computing systems and fault-tolerant designs. Dr. Jones' work spans quantum system co-design (e.g., superconducting qubit architectures), nanoscale magnetic memories (racetrack/STT-MRAM), and carbon lifecycle modeling for computing systems. He has pioneered concepts like GreenChip sustainability tools and CORUSCANT processing-in-memory frameworks. His IEEE Fellowship and Best Paper Award (IGSC 2018) highlight his impactful contributions. Key Research Areas: Quantum Computing, Non-Volatile Memories, Sustainable Computing, Fault Tolerance Funding Agencies: NSF, DARPA, NSA, ARO, Industry Collaborations Major Projects: Quantum circuit decomposition, racetrack memory applications, carbon modeling for datacenters His 200+ publications include seminal works on fault tolerance in domain-wall memories, energy-efficient architectures, and cross-disciplinary innovations at the intersection of physics and computer engineering. Current efforts explore carbon depreciation models and real-time accelerator customization for edge computing.

• Quantum Computing
• Computer Architecture
• Nanoscale Magnetic Memory Systems
• +5 more

Mariagrazia Graziano is an Associate Professor at the Department of Applied Science and Technology (DISAT) at Politecnico di Torino, where she also serves as Director of the Teaching and Language Lab (TLLab). Her academic career spans multiple institutions, including her involvement with doctoral colleges at the University of Palermo for 'Technologies and Methods for University Education' from 2022-2025. Her research interests are at the forefront of nanotechnology and quantum computing, focusing on areas including: Molecular field-coupled nanocomputing Logic-in-memory computing architectures Quantum hardware design and optimization Single-molecule devices for logic and memory applications Nanomagnetism and spintronics Micro-for-Nano (M4N) Systems for Single Molecule Sensors Dr. Graziano's work bridges fundamental physics with practical applications in electronics, with particular emphasis on next-generation computing paradigms that address the memory-wall problem and explore alternatives to traditional von Neumann architectures. Her research has significant implications for fields ranging from molecular electronics to quantum information processing. Her recent publications demonstrate a strong focus on molecular field-coupled nanocomputing, quantum optimization techniques, and single-molecule device modeling. These works reveal a consistent research trajectory toward developing novel computing architectures that leverage quantum effects and molecular-scale phenomena to overcome limitations of conventional semiconductor technology. Dr. Graziano has received notable recognition including the prestigious Marie Curie Intra-European Fellowship for Career Development from the European Commission (2014). She serves as Associate Editor for FRONTIERS IN ELECTRONICS (since 2022) and JOURNAL OF COMPUTATIONAL ELECTRONICS (since 2019), and has participated in program committees for major conferences including the IEEE Design Automation and Test Conference Europe. As an advisor, Dr. Graziano mentors numerous PhD students working on cutting-edge research in quantum computing, molecular electronics, and nanotechnology. Her supervision spans multiple doctoral programs at Politecnico di Torino, with students exploring topics from quantum algorithms for urban traffic optimization to single-molecule junctions for next-generation electronics. Additionally, she leads several research projects including TENS (Toward Excellence in Nanocharacterisation of single-molecule Sensors) and previously served as Scientific Leader for the Quantum Computing e Quantum Networking project. Dr. Graziano is actively involved in the VLSILAB research group, where she contributes to advancing the state-of-the-art in electronic design and nanoscale computing technologies. Her work on patents, particularly the 'Device for Realizing Boolean Logic Functions XOR XNOR Inside Racetrack Memory,' demonstrates her commitment to translating theoretical research into practical technological innovations.

• Molecular electronics
• Nanoelectronics
• Quantum computing
• +8 more

Dr. Jae-Chun Jeon is a leading experimental physicist at the Max Planck Institute of Microstructure Physics in Halle, Germany, where he works within the NISE department (Nano-Systems from ions, spins and electrons). He joined the institute in 2018 after completing his postdoctoral fellowship at the University of Alberta, Canada. His research focuses on spintronics, unconventional computing devices, and cryogenic systems, with emphasis on developing novel memory and logic technologies for next-generation computing. Dr. Jeon earned his Ph.D. in condensed matter physics from the University of Alberta, Edmonton, Canada, in 2016. He continued his research as a postdoctoral fellow at the same institution, focusing on strongly correlated magnetic oxide materials for spintronic and neuromorphic applications before joining the Max Planck Institute. Dr. Jeon's research centers on unraveling the physics of complex systems including spintronics, correlated oxides, and atomically engineered materials to discover their advanced functionalities. He specializes in manipulating spin textures and states using spin electrons, with particular focus on current-induced domain wall motion and spin-orbit torque-induced magnetization switching for memory and logic applications. His work explores the potential of racetrack memory for both conventional binary memory and unconventional analogue systems such as probabilistic-bit and neuromorphic devices. His recent publications demonstrate a strong focus on advanced spintronic devices, particularly racetrack memory systems, domain wall logic, and Josephson junctions for quantum applications. The research spans fundamental physics of chiral domain walls, spin-orbit torque effects, and novel materials for spin-based computing. His work frequently appears in high-impact journals including Science, Nature family journals, and Advanced Materials, reflecting the significance of his contributions to the field. Dr. Jeon's research is supported by cutting-edge facilities including atomically thin film deposition systems, state-of-the-art electronics, and advanced device fabrication techniques such as electron beam lithography and ion beam etching/deposition. His work involves close collaboration with the research group led by Prof. Stuart Parkin, a director at the Max Planck Institute of Microstructure Physics.

• Spintronics
• Unconventional computing devices
• Neuromorphic computing
• +9 more

Dr. S.N. Piramanayagam is an Associate Professor at the Division of Physics and Applied Physics (PAP) within the School of Physical and Mathematical Sciences (SPMS) at Nanyang Technological University (NTU), Singapore. He has over 30 years of expertise in magnetism, focusing on spintronics, magnetic recording, and neuromorphic computing. His academic journey includes a PhD from IIT Bombay and postdoctoral research at Shinshu University, Japan. Education: Bachelor's in Physics, Madurai Kamaraj University, India (1985) Masters in Physics, University of Kerala, India PhD in Physics, Indian Institute of Technology Bombay, India (1994) Research Interests: Dr. Piramanayagam’s work bridges magnetism, electronics, and nanotechnology. Key areas include: Neuromorphic computing using domain wall memory-based devices Spintronics materials for high-density storage and energy-efficient computing Magnetic recording media optimization Magnonic crystals and skyrmion-based systems Lithography techniques for nanoscale patterning His team collaborates with academia and industry to develop spin-based neuromorphic hardware, leveraging grants like a multi-million dollar project in this domain. Publications & Contributions: His research spans over 200 ISI journal articles, patents, and an edited book on data storage materials. Notable works address domain wall dynamics, skyrmion manipulation, and neuromorphic device fabrication. Recent trends focus on spintronic heterostructures and energy-efficient computing systems. Professional Roles: Chief Editor, IEEE Transactions on Magnetics Elected Member of AdCom, IEEE Magnetics Society (2021–2024) Organized over 20 international conferences, including Intermag and ICMAT Teaching & Mentorship: He teaches courses like Spintronics for Information Technology and has mentored 10 PhD and numerous master’s students. His lab focuses on interdisciplinary projects involving graduate and undergraduate researchers. Labs & Teams: His research group at NTU’s PAP division works on cutting-edge projects in neuromorphic computing, magnetic materials, and spintronics devices, with active collaborations across institutions and industries.

• Neuromorphic Computing
• Spintronics Materials
• Magnetic Recording
• +4 more

Holly Kruse is a Professor in the Department of Communications at Rogers State University (RSU), affiliated with the School of Liberal Arts. She holds a Ph.D. in Communication from the University of Illinois at Urbana-Champaign and a postgraduate certificate in Equine Business from the University of Louisville. Her research focuses on media technology, gender studies, horse racing industry dynamics, and digital media's societal impact. Education: Ph.D., Communication, University of Illinois at Urbana-Champaign (Institute of Communications Research) B.A., Political Science and History, University of Iowa Post-graduate Certificate, Equine Business, University of Louisville Research Interests: Her work examines intersections of technology, culture, and social structures. Key areas include the digital transformation of horse racing, gender in media, independent music scenes, and affective networks in social media. She has authored/co-authored books like Off-Track and Online: The Networked Spaces of Horse Racing (MIT Press, 2016) and Gender and Technology: An Introduction (forthcoming 2024). Publications: Over 30 refereed articles and book chapters, including studies on online gambling, music subcultures, and digital media's role in reshaping social spaces. Recent work explores gendered spaces in synth-pop and media class dynamics in horse racing. Awards: Honors include the Greg Kunz Endowed Chair in Communications (RSU, 2019–2022) and recognition for her book Off-Track and Online in media research awards. She is an active reviewer for journals like New Media & Society and conferences such as AoIR. Service: Served on RSU committees including University Assessment and Faculty Senate. Professional roles include co-founding an annual internet research teaching workshop and mentoring doctoral students. Community engagement includes volunteer work with therapeutic horseback riding programs and dog rescue initiatives.

• Communication Studies
• Media Technology
• Gender Studies
• +5 more

Alexander Vardy is a Professor at the University of California, San Diego, affiliated with the Center for Memory and Recording Research. His research focuses on coding theory, information theory, and communications, with a strong emphasis on polar codes, error-correcting codes, and their applications in storage and communication systems. He has contributed significantly to the development of efficient coding schemes for various channels, including deletion channels and wiretap channels. His work spans theoretical advancements and practical implementations, addressing challenges in decoding algorithms, code design, and system optimization. Notable areas include polar codes, write-once memory codes, and distributed storage systems. His research has implications for improving data reliability, security, and efficiency in modern communication and storage technologies. Dr. Vardy's contributions to information theory have led to innovations in coding for constrained systems, such as those found in racetrack memories and flash storage. He actively explores the intersection of combinatorics and coding theory, developing algorithms and structures for optimal code performance.

• Coding Theory
• Information Theory
• Communications
• +3 more

Dr.-Ing. Gerald Hempel is a researcher at Dresden University of Technology (TU Dresden) with active contributions to computer architecture and embedded systems from 2015–2023. His work bridges hardware/software co-design through domain-specific languages and compiler techniques, primarily within the Faculty of Electrical and Computer Engineering context. His research spans: Domain-Specific Languages for hardware acceleration Memory optimization in high-performance computing Reconfigurable computing using FPGAs Many-core and heterogeneous system design Bio-inspired algorithms for robust system mapping Racetrack memory applications in brain-inspired cognition Publication analysis reveals consistent focus on compiler-driven hardware acceleration, particularly for computational fluid dynamics and cognitive systems. His work emphasizes memory architecture innovations (e.g., high-bandwidth memory, caching) and bio-inspired robustness techniques, often through collaborations like the EVEREST consortium for compilation frameworks. No scientific awards were documented in the source material. No student advising or grant information was provided in the available texts. Dr. Hempel collaborates within TU Dresden's research ecosystem, notably with the EVEREST consortium and chairs including Compiler Construction and Emerging Electronic Technologies. His work on tools like Mocasin demonstrates active participation in teams developing rapid prototyping frameworks for heterogeneous multi-core systems and FPGA-based accelerators.

• Computer Architecture
• Embedded Systems
• High-Performance Computing
• +4 more