جستجوی استاد راهنمای دانشگاهی

• Logic-in-memory
• Machine learning
• Nanocomputing
• +۷ مورد دیگر

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.

• Molecular electronics
• Nanoelectronics
• Quantum computing
• +۸ مورد دیگر

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
• Nanophysics
• +۳ مورد دیگر

Yuri Ardesi is a Fixed-term Assistant Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino. His research focuses on molecular electronics, nanoelectronics, and nanophysics with specific applications in field-coupled nanocomputing and sustainable microelectronics education. Scientific sector: IINF-01/A - Electronics ERC sectors: PE3_12 (Molecular electronics), PE3_10 (Nanophysics) SDGs: Quality education, Industry innovation, Responsible consumption Research Highlights include developing computational models for single-molecule optoelectronic devices, investigating field-coupled nanocomputing architectures, and exploring sustainable microelectronics education ecosystems. His recent work analyzes hydrogen passivation for metal deposition and molecular ensemble electrostatics. Scientific Awards Learning to Teach (L2T) Open Badge for educational innovation Teaching Roles span multiple academic years (2019-2025) across: Master's Degree: Technology for Nanoelectronic Systems Bachelor's Degree: Digital Systems Electronics Workshop: Innovative Systems

Cezary Czaplewskiمشاهده پروفایل

استاد

• Coarse-grained molecular modeling
• Protein structure prediction
• Molecular dynamics simulations
• +۳ مورد دیگر

Professor Cezary Czaplewski of the University of Gdańsk is a leading researcher in computational chemistry and coarse-grained molecular modeling. Affiliated with the Faculty of Chemistry and the Department of Theoretical Chemistry , he heads the UNRES server for protein simulations and contributes to projects like Multi-GPU UNRES and MAGENTA . His work bridges physics-based simulations with experimental data integration. Key roles : Professor, Computational Biophysics, University of Gdańsk Projects : EuroHPC PL, Harmonia9, Enerliq, Parylens Research Focus : His research spans coarse-grained modeling , protein structure prediction , and hydrophobic interaction studies , with applications in virology (SARS-CoV-2), antimicrobial peptide design, and large-scale biomolecular simulations. He specializes in GPU-accelerated algorithms and multi-GPU implementations for scalable systems. Teaching : Currently teaches Molecular mechanics & dynamics , Introduction to Python programming , and Parallel programming (Bioinformatics III) . Past courses include Electronic chemical diagnostics and Software in biomacromolecular calculations for PhD students. Scientific Contributions : Developed the UNRES server for polypeptide simulations, extended the UNRES force field to nucleic acids and membrane proteins, and participated in multiple CASP/CAPRI experiments for protein structure prediction. His 2025 publications focus on time-averaged restraints and multi-GPU scalability. Contact : cezary.czaplewski@ug.edu.pl Location : Room B328, Faculty of Chemistry, University of Gdańsk

• Digital circuits
• Microelectronics
• Molecular electronics
• +۷ مورد دیگر

Gianluca Piccinini serves as a Full Professor at the Polytechnic University of Turin, holding multiple leadership positions including Head of the Department of Electronics and Telecommunications and Member of the Academic Senate. His academic career spans numerous teaching roles across various programs at the university. His research focuses on digital circuits, microelectronics, molecular electronics, and nanoelectronics with particular emphasis on quantum cellular automata, molecular field-coupled nanocomputing, and nanoscale device development. His work bridges theoretical modeling with practical applications in semiconductor technology and molecular electronics. His recent publications demonstrate a strong focus on nanoscale transistor design, molecular computing architectures, and advanced fabrication techniques for next-generation electronic devices. These works consistently address the challenges of miniaturization and quantum effects in electronic components. As an academic leader, Professor Piccinini has supervised numerous PhD students through their research in micro- and nanotechnologies, devices, and systems. He has been actively involved in multiple research projects including TENS (Toward Excellence in Nanocharacterisation of single-molecule Sensors) and previously led the EUROSOI thematic network. He leads the VLSILAB research group which focuses on advanced semiconductor research, molecular electronics, and quantum computing technologies, contributing significantly to the university's research output in these cutting-edge fields.

• Quantum Computing
• Nanotechnology
• Computer Engineering
• +۳ مورد دیگر

Mariagrazia Graziano is a Lecturer at the School of Engineering (EPFL). Her teaching focuses on advanced computational paradigms. Courses: Quantum and Nanocomputing (covers quantum computing, field-coupled nanocomputing, molecular computing, and spintronic computing). Research Interests: Non-traditional computing architectures, quantum technologies, and nanoscale systems. Contact: mariagrazia.graziano@epfl.ch