جست‌وجوی استاد و پژوهشگر

• High-Performance Computing
• GPU Acceleration
• Computational Geoscience
• +۴ مورد دیگر

Ludovic Räss is a computational geoscientist at the University of Lausanne and lecturer at ETH Zurich's Glaciology Lab. His research intersects high-performance computing (HPC), geophysics, and applied mathematics, with specialization in GPU-accelerated scientific computing and supercomputing applications. He leads the GPU4GEO initiative developing multi-physics solvers and pioneers differentiable modeling techniques for geophysical simulations using Julia. Research focuses include: Portable HPC software development Ice dynamics and porous media deformation GPU-optimized computational methods Scalable simulation architectures Differentiable programming for geophysics He designed and teaches Solving partial differential equations in parallel on GPUs at ETH Zurich, providing hands-on training in GPU programming and Julia-based scientific computing. Contributes significantly to Julia's open-source ecosystem through JuliaGPU and JuliaParallel projects.

Luciano Lavagnoمشاهده پروفایل

استاد

• Field Programmable Gate Arrays (FPGA)
• High-Level Synthesis
• Indoor Positioning
• +۱۰ مورد دیگر

Luciano Lavagno is a Full Professor at the Department of Electronics and Telecommunications, Polytechnic University of Turin, with over two decades of academic and research contributions. His work bridges hardware acceleration, low-power electronics, and intelligent system design. Research Focus: Hardware-accelerated machine learning, high-level synthesis (HLS) for FPGA/ASIC, heterogeneous CPU/GPU/FPGA platforms Key Projects: SPACE (predictable acceleration), REBECCA (secure AI acceleration), HPC-National Center (quantum computing), and oral history preservation via "Ti racconto una storia" initiative His recent publications analyze CNN inference optimization, subgraph isomorphism, and superword-level parallelism exploitation. Lavagno supervises multiple PhD students working on FPGA acceleration, neural network hardware, and embedded systems. As Principal Investigator for national and EU-funded projects (PRIN, JTI-ECSEL, PNRR), he drives advancements in sustainable computing infrastructure. His patented technologies include MIx&Latch timing methodology, capacitive sensing innovations, and 5G acceleration frameworks.

• GPU Acceleration
• Embedded Systems
• Autonomous Vehicles
• +۶ مورد دیگر

Nicola Capodieci is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences at the University of Modena and Reggio Emilia, specializing in Information Processing Systems (IINF-05/A). He actively teaches multiple courses including Object-Oriented Programming, Web Technologies, and General Computer Science across Computer Science and Mathematics degree programs. His research interests focus on GPU acceleration for embedded systems, autonomous vehicles, and real-time computing. Dr. Capodieci's work addresses critical challenges in heterogeneous computing platforms, particularly for automotive applications and smart city infrastructure. His research bridges theoretical computer science with practical applications in autonomous driving and urban mobility systems. Analysis of his recent publications reveals a strong focus on optimizing GPU performance for latency-sensitive applications, particularly in autonomous vehicles. His work spans path planning algorithms, memory interference management, and real-time scheduling on heterogeneous platforms. A significant portion of his research addresses practical implementation challenges in embedded systems where computational resources are constrained but timing predictability is critical. Dr. Capodieci's teaching portfolio demonstrates expertise in both foundational programming concepts and advanced topics in web technologies. His courses emphasize practical implementation skills while covering theoretical foundations of object-oriented programming, web development frameworks, and computational thinking.

Luca Sterponeمشاهده پروفایل

استاد

• Reconfigurable computing
• Computer-aided design algorithms
• Fault tolerance and reliability
• +۷ مورد دیگر

Luca Sterpone is a Full Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He serves as Head of the Control and Computer Engineering Department (2023-2027), coordinates the Aerospace and Safety Computing Lab, and is a member of the Academic Senate and Power Electronics Innovation Center (PEIC). His research spans reconfigurable computing, fault tolerance, and radiation effects analysis in electronic systems. Professor since 2021 Department Head (DAUIN) since 2023 Coordinates international collaborations with ESA, AMD Xilinx, NVIDIA, and Thales Alenia Space Develops radiation-hardened FPGA tools (SETA, VERI-Place, PyXEL) 2007 EDAA Outstanding Dissertation Award and 2005 IEEE Best Paper Award Research Focus : Designing radiation-tolerant systems for aerospace, including fault-tolerant AI accelerators, FPGA reliability, and software-based error mitigation. He investigates soft error propagation in nanoscale circuits and develops tools for radiation sensitivity analysis in VLSI. His work integrates hardware-software co-design for mission-critical applications. Awards : EDAA Outstanding Dissertation Award (2007) IEEE European Test Symposium Best Paper (2005) SMACD Best EDA Tool Award (2018) ARC Best Paper candidate (2018) Teaching : He leads courses in Reconfigurable Computing (PhD level), GPU Programming , and Operating Systems . He has formal responsibility for teaching roles across 9 bachelor's and 7 master's years, and mentors multiple PhD students. Collaborations : Coordinates with the European Space Agency (ESA), University of Bielefeld, Universidad de Sevilla, and industrial partners like AMD Xilinx, NVIDIA, and General Motors. He leads projects such as RESCHIP4EU, VEGAS, and TERRAC for radiation-hardened computing solutions.

• Digital Forensics
• Image Processing
• Multimedia Analysis
• +۴ مورد دیگر

Giulia Boato is an Associate Professor at the University of Trento’s Department of Information Engineering and Computer Science (DISI). She teaches courses in Probability and Multimedia Data Security. Her expertise spans Cyber Security, Digital Forensics, and Multimedia Analysis, focusing on image and signal processing for data protection, forensics, and anti-forensics. She collaborates internationally with institutions like Tampere University of Technology and Dartmouth College, co-advising PhD students and contributing to European projects like LIVINGKNOWLEDGE and GLOCAL. Education: PhD in Information and Communication Technology (2005), M.Sc. in Mathematics (2002), Scientific Lyceum (1998) with bilingual Italian-German certification. Past roles include Assistant Professor at DISI (2006–2018) and visiting researcher at the University of Vigo (2006) and University of Innsbruck (2018). Research interests include multimedia data protection, image forensics (tampering detection, computer vs. natural data discrimination), and intelligent data management. She leads projects on social media forensics, event-based retrieval, and synthetic media detection. Awards include Best Paper at IEEE WIFS 2012 and Top 10% Paper at MMSP 2012. Professional contributions include roles as co-chair of workshops, Technical Program Committee member for ICIP and ICC, and reviewer for journals like IEEE Transactions on Information Forensics and Security. She has advised PhD theses and contributed to datasets like TrueFace and WILD for synthetic media analysis.

Marco Aldinucciمشاهده پروفایل

استاد

• Parallel Computing
• High-Performance Computing (HPC)
• Cloud Engineering
• +۷ مورد دیگر

Marco Aldinucci is a Full Professor and Head of the Parallel Computing group at the University of Torino's Computer Science Department. He leads the HPC Key Technologies and Tools (HPC-KTT) national lab under CINI, involving 38 Italian universities. His expertise spans parallel programming models, HPC systems, federated learning, and energy-efficient computing. Aldinucci has secured over €10M in EU research funding, contributed to frameworks like Fastflow and Streamflow, and pioneered initiatives like the HPC4AI lab and the CINI HPC-KTT lab. His research focuses on advancing exascale computing, cloud-HPC integration, and AI-driven medical solutions. Notable projects include the Gaia AVU-GSR solver for exascale systems and the DeepHealth Toolkit for medical AI. He has held governance roles in EuroHPC and chairs the Observatory on Trends and Applications of Supercomputing in Italy. Aldinucci’s publications (150+) address parallel algorithms, distributed learning, and sustainable HPC infrastructure. His work has been recognized with awards from HPC Advisory Council, NVIDIA, IBM, and Autodesk. Current initiatives include the Software & Integration lab at the Italian National HPC Centre (ICSC) and leadership in the OpenScience working group at Torino. His advising includes Iacopo Colonelli, whose thesis won CINI’s 2023 best award. He actively engages in EU projects, workflow systems, and standards for hybrid computing environments. Aldinucci’s labs and collaborations drive innovations in HPC portability, energy efficiency, and AI scalability.

Sandro Bartoliniمشاهده پروفایل

دانشیار

• High-Performance Computing (HPC)
• Computer Architecture
• Embedded Systems
• +۵ مورد دیگر

Sandro Bartolini serves as Associate Professor in the Department of Information Engineering and Mathematical Sciences at the University of Siena, Italy, where he teaches advanced courses in computer architecture and parallel programming while leading cutting-edge research in high-performance computing systems. His academic journey began with a cum laude Laurea in Computer Engineering followed by a PhD in Computer Science and Engineering from Università di Pisa. Education: PhD in Computer Science and Engineering, Università di Pisa Laurea in Computer Engineering (cum laude), Università di Pisa Research Focus: His work centers on photonic interconnects for chip multiprocessors , energy-efficient software optimization for multi-core/GPU architectures, and performance-portable parallel programming models . Current investigations span cryptographic acceleration, blockchain algorithms, and hardware/software co-design for emerging computing paradigms, with strong emphasis on practical implementations bridging theoretical advances and real-world applications. Publication Trends: Recent publications (2019-2023) reveal three dominant threads: (1) Photonic network innovations addressing energy bottlenecks in chip multiprocessors, (2) The PHAST library ecosystem enabling seamless CPU/GPU programming across domains from autonomous vehicles to UAV navigation, and (3) Hardware accelerator designs for convolutional networks and cryptographic workloads. These works consistently target performance-portability challenges in heterogeneous computing environments. Grants and Collaborations: As principal investigator for the Italian Ministry-funded PHOTONICA project, he established international research partnerships with Murcia University, Columbia University, and Hong Kong University of Science and Technology, while securing industry collaborations with STMicroelectronics, Intel Munich, IBM, and IMEC. He has also managed complex IT system deployments for Siemens Italy, RAI (Italian public broadcasting), and SpaceDys. Academic Leadership: Bartolini serves as Associate Editor for the Eurasip Journal of Embedded Computing and actively contributes to the European HiPEAC network. His research group at Siena maintains strong industry ties for technology transfer, particularly in photonic interconnect validation and parallel programming frameworks for next-generation computing systems.

Antonela Tommaselمشاهده پروفایل

استاد مدعو

• Social Computing
• Recommender Systems
• Machine Learning
• +۵ مورد دیگر

Dr. Antonela Tommasel is a Researcher at CONICET and an Adjunct Professor at National University of the Center of the Province of Buenos Aires (UNICEN) , working at the intersection of social computing, machine learning, and misinformation mitigation. Her work combines computational techniques to address challenges in social media analysis, bias detection, and recommender system design. PhD in Computer Sciences (2017), UNICEN Bachelor in Software Engineering (2012), UNICEN Her research focuses on recommender systems with applications to social media trustworthiness , including projects like Faking It! (fake news dataset creation) and OHARS (harm-aware recommendation frameworks). Key themes include misinformation spread analysis , gender bias detection , and machine learning applications for social good. She has led 11+ years of teaching in courses like Advanced Java Programming, Recommender Systems, and Natural Language Processing for AI specializations. Her technical certifications include NVIDIA Deep Learning Institute programs on GPU-accelerated data science and Coursera specializations in machine learning and visualization. Currently based at ISISTAN Research Institute in Tandil, Argentina, she advocates for responsible AI through tools like graphoW (graph-of-words library) and Sen4Smells (technical debt prioritization). Her work emphasizes bridging social media analysis with practical implementation frameworks.

• Computational Logic
• Answer Set Programming
• Bioinformatics
• +۶ مورد دیگر

Alessandro Dal Palu' is an Associate Professor at the Department of Mathematical, Physical, and Computer Sciences at University of Parma. He holds a PhD in Computer Science from University of Udine and has been with University of Parma since 2005, transitioning from Researcher to Associate Professor in 2014. His teaching portfolio includes courses on Computer Architecture, Constraint Programming, and Algorithms & Data Structures. His research spans computational logic, bioinformatics, and GPU computing. Notable achievements include the 2007 GULP award for his Ph.D. thesis and the ICLP 2010 best paper award. He has led Italian INdAM-GNCS research projects on GPU applications (2011) and Logic Programming in cancer genomics (2016). Recent publications focus on explainable AI frameworks, bioinformatics applications, and sustainable logistics solutions. His work integrates Answer Set Programming with biomedical challenges like protein structure analysis and cancer genome evolution. He chairs the International Conference on Logic Programming (ICLP 2018) and has organized multiple international workshops on constraint programming. 2007 GULP Award ICLP 2010 Best Paper PI for INdAM-GNCS projects (2011, 2016) Program Committee member for international conferences

• Numerical Analysis
• Machine Learning
• Optimization
• +۳ مورد دیگر

Luca ZANNI is a Full Professor at the Department of Physical, Computer and Mathematical Sciences, Università di Modena e Reggio Emilia. His academic career spans numerical analysis, machine learning, and optimization methods, with a focus on gradient projection algorithms, stochastic gradient techniques, and their applications in imaging and deep learning. His research includes developing adaptive steplength rules for gradient methods, variance control in stochastic optimization, and GPU-accelerated reconstruction techniques for medical imaging. He teaches courses such as Numerical Calculation with Python, Fundamentals of Machine Learning, and Mathematical Methods for Machine Learning, covering topics like numerical optimization, support vector machines, and deep learning. He has contributed to methodologies for hyperparameter-free training, active set identification in constrained optimization, and edge-preserving image reconstruction. His work bridges theoretical advancements in optimization with practical implementations in large-scale machine learning and medical imaging applications.

Andrea Dettiمشاهده پروفایل

استاد

• Computer Networks
• Information-Centric Networking (ICN)
• Cloud Computing
• +۳ مورد دیگر

Andrea Detti is a Professor at the Department of Electronic Engineering, University of Rome Tor Vergata. His research focuses on computer networks, particularly Information-Centric Networking (ICN), Cloud Computing, and Software Defined Networks (SDN). He has coordinated major EU projects like Fed4IoT and BONVOYAGE, addressing IoT and Intelligent Transport Systems. He serves as Associate Editor for IEEE Transaction on Network and Service Management and has guest-edited special issues on ICN. His teaching includes courses on Internet Technologies, Mobile Wireless Networks, and Cloud Computing, emphasizing hands-on labs with Linux, Cisco routers, and OpenStack. Key projects include leadership roles in EU initiatives such as ICN2020, GreenICN (energy-efficient ICN), and OFELIA (ICN over SDN). He coordinates industrial projects with Telecom Italia and SSI/Finmeccanica on publish-subscribe paradigms in MANET and DTN. His research spans ICN scalability, adaptive video streaming, and satellite communication optimizations. Publications (80+) cover ICN architecture, SDN integration, and network performance modeling. He actively participates in conferences and standardization efforts, contributing to the evolution of future Internet architectures.

Stefano Querمشاهده پروفایل

دانشیار

• Computer Science
• Electrical Engineering
• Formal Methods
• +۷ مورد دیگر

Stefano Quer is an Associate Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He holds a PhD in Electronic Engineering from the same institution and has been affiliated with DAUIN since 1996. Researcher (1996-2000) Associate Professor (2000-present) Visiting Faculty at UC Berkeley (1994-1995) Research Interests His work spans Formal Verification BDD/SAT Techniques Embedded Systems Hardware/Software Co-Verification Parallel Computing with applications in VLSI CAD, industrial IoT, and energy-efficient systems. Recent articles focus on GPU-accelerated graph algorithms, wireless sensor calibration, and AI-driven test optimization. Scientific Awards Best Paper Award, IEEE EURO-DAC'94 Academic Contributions Supervised PhD students Lorenzo Cardone and Andrea Calabrese Member of DATE, ICSOFT Technical Program Committees Topical Advisor for Sensors MDPI 60+ publications in IEEE/ACM venues

Andrea Formisanoمشاهده پروفایل

دانشیار

• Computational Logic
• Logic programming
• Answer Set Programming (ASP)
• +۹ مورد دیگر

Andrea Formisano is an Associate Professor in Computer Science at the Department of Mathematics, Informatics and Physics (DMIF) at the University of Udine, Italy. His research spans diverse areas within computational logic, including logic programming, answer set programming (ASP), constraint logic programming (CLP), action languages, automated deduction, theory reasoning, set theory, relational reasoning, GPU computing, and non-classical logics. Contact : Via delle Scienze 206, 33100 Udine, Italy | Tel: +39 0432 558496 | Fax: +39 0432 558400 Teaching : Offers courses on Operating Systems and Programming on Parallel Architectures through the university's elearning platform. Research Keywords : Computational Logic, Logic programming, ASP, CLP, Action languages, Automated deduction, Theory reasoning, Set theory, Relational reasoning, GPU computing, Games, Non-classical Logics. Professional Affiliations : Active in academic events such as the International Conference on Logic Programming (ICLP), Italian Conference on Computational Logic (CILC), and the Association for Logic Programming (ALP). He is also affiliated with the Italian Association for Logic Programming (GULP).

Juan David Guerrero Balagueraمشاهده پروفایل

پژوهشگر ارشد

• AI Accelerators
• GPU Reliability
• Fault Tolerance
• +۷ مورد دیگر

Juan David Guerrero Balaguera is a Research Fellow at Politecnico di Torino's Department of Automatic Control and Computer Science (DAUIN), affiliated with the CAD group. He holds a Ph.D. in Computer and Control Engineering from Politecnico di Torino (2024), advised by Prof. Matteo Sonza Reorda and Prof. Ernesto Sanchez. His research focuses on dependable hardware for safety-critical systems, including GPU reliability, fault tolerance, AI accelerators, and functional in-field testing. Prior to his Ph.D., he earned a Master's (2017) and Bachelor's (2013) in Electronics Engineering from Universidad Pedagógica y Tecnológica de Colombia, where he taught digital design, embedded systems, and FPGA-based image processing from 2014 to 2020. His research interests span advanced FPGA design, computational arithmetic for AI, fault effects analysis in GPUs, and reliability assessment of neural networks. Notable contributions include methods for generating self-test libraries (STLs) for GPUs, evaluating fault impacts on TCUs, and enhancing CNN robustness via dropout layer optimization. Education: Ph.D. in Computer and Control Engineering, Politecnico di Torino (2024) M.S. in Electronics Engineering, Universidad Pedagógica y Tecnológica de Colombia (2017) B.S. in Electronics Engineering, Universidad Pedagógica y Tecnológica de Colombia (2013) He has received the Ph.D. Quality Award (2023 and 2024) from Politecnico di Torino and Best Paper recognitions at DATE 2023 and DDECS 2021. His work bridges theoretical fault models with practical GPU testing methodologies, emphasizing real-world applications in AI and edge computing. Current teaching roles include collaborating on GPU programming (Master's level) and computer sciences courses (Automotive Engineering). Research collaborations involve exploring reliability trade-offs in split-computing DNNs and developing fault-aware design flows for AI accelerators.

Mihai Teodor Lazarescuمشاهده پروفایل

دانشیار

• Artificial intelligence
• Capacitive sensors
• Embedded software
• +۱۰ مورد دیگر

Dr. Mihai Teodor Lazarescu is an Associate Professor at the Department of Electronics and Telecommunications (DET), Politecnico di Torino , where he contributes to research and teaching activities. He is also a member of the PolitoBIOMed Lab (Biomedical Engineering Lab) and the Ambient Sensing and Processing research group. Scientific Affiliation: IEEE Member (2019-present) Editorial Roles: Guest Editor for SENSORS, ELECTRONICS, and ACM Transactions on Embedded Computing Systems His research interests focus on hardware acceleration for machine learning algorithms, particularly using FPGAs for data center and embedded applications. He works on high-level synthesis optimization flows, capacitive sensor design for indoor monitoring, and low-power embedded systems . His work intersects Internet of Things , Wireless Sensor Networks , and Machine Learning with applications in human localization, environmental monitoring, and industrial automation. Recent publications demonstrate expertise in neural network optimization , DSP resource sharing , and multi-FPGA allocation . His teaching spans Applied Electronics , Digital Electronic Design , and Embedded Systems Optimization across bachelor's and master's programs in Electronic Engineering and Computer Engineering . Patents: Noise cancellation for single-plate capacitive sensors Capacitive sensor for space change detection Projects: Scientific Manager for Horizon 2020-S2RJU project (2018)