Achievements
Awards
• Ph.D. Forum at the 25th Design, Automation and Test in Europe Conference (Ph.D. Forum @ DATE), 2022.
• Ph.D. Forum at the 58th Design Automation Conference (Ph.D. Forum @ DAC), 2021.
• Student Research Forum at the 26th Asia and South Pacific Design Automation Conference (SRF @ ASP-DAC), 2021.
• IEEE CIS Conference Registration Grant for Graduate Student – IEEE WCCI 2020.
• DAC Richard Newton Young Fellow Award (2019).
Scientific Review Committee
• IEEE/INNS International Joint Conference on Neural Networks (IJCNN), 2022.
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
• Conference on Neural Information Processing Systems (NeurIPS), 2021.
• International Conference on Machine Learning (ICML), 2020 – 2022.
• International Conference on Learning Representations (ICLR), 2020 – 2022.
Invited Talks
• Energy-Efficient Deep Learning at the Edge: A Cross-Layer Approach, Summer School at the 9th International Conference on Cyber-Physical Systems and Internet-of-Things, June 2021.
• Efficient Conversion and Deployment of Spiking Neural Networks for Gesture Recognition using the Loihi Chip, Intel Neuromorphic Research Community forum, June 2020.
• Resilient and Energy-Efficient Deep Learning with Capsule Networks and Spiking Neural Networks, Politecnico di Torino, Italy, February 2020.
Publications
Conference Papers
1. M. Shafique, A. Marchisio, R. V. W. Putra, M. A. Hanif, “Towards Energy-Efficient and Secure Edge AI: A Cross-Layer Framework”, IEEE/ACM 40th International Conference On Computer-Aided Design (ICCAD), November 2021.
2. A. Marchisio, G. Pira, M. Martina, G. Masera, M. Shafique, “R-SNN: An Analysis and Design Methodology for Robustifying Spiking Neural Networks against Adversarial Attacks through Noise Filters for Dynamic Vision Sensors”, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2021.
3. A. Marchisio, G. Pira, M. Martina, G. Masera, M. Shafique, “DVS-Attacks: Adversarial Attacks on Dynamic Vision Sensors for Spiking Neural Networks”, The International Joint Conference on Neural Networks (IJCNN), at the IEEE World Congress on Computational Intelligence (WCCI), July 2021.
4. A. Viale, A. Marchisio, M. Martina, G. Masera, M. Shafique, “CarSNN: An Efficient Spiking Neural Network for Event-Based Autonomous Cars on the Loihi Neuromorphic Research Processor”, The International Joint Conference on Neural Networks (IJCNN), at the IEEE World Congress on Computational Intelligence (WCCI), July 2021.
5. A. Colucci, D. Juhász, M. Mosbeck, A. Marchisio, S. Rehman, M. Kreutzer, G. Nadbath, A. Jantsch, M. Shafique, “MLComp: A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization Sequences”, IEEE/ACM 24th Design, Automation and Test in Europe Conference (DATE), February, 2021.
6. R. El-Allami, A. Marchisio, M. Shafique, I. Alouani, “Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters”, IEEE/ACM 24th Design, Automation and Test in Europe Conference (DATE), February, 2021.
7. A. Marchisio, A. Massa, V. Mrazek, B. Bussolino, M. Martina, M. Shafique, “NASCaps: A Framework for Neural Architecture Search to Optimize the Accuracy and Hardware Efficiency of Convolutional Capsule Networks”, IEEE/ACM 2020 International Conference On Computer Aided Design (ICCAD), November 2020.
8. A. Colucci, A. Marchisio, B. Bussolino, V. Mrazek, M. Martina, G. Masera, M. Shafique. “A Fast Design Space Exploration Framework for the Deep Learning Accelerators: Work-in-Progress”, 2020 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), September, 2020.
9. A. Marchisio, B. Bussolino, A. Colucci, M. A. Hanif, M. Martina, G. Masera, M. Shafique, “FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule Networks”, The International Joint Conference on Neural Networks (IJCNN), at the IEEE World Congress on Computational Intelligence (WCCI), July 2020.
10. R. Massa, A. Marchisio, M. Martina, M. Shafique, “An Efficient Spiking Neural Network for Recognizing Gestures with a DVS Camera on the Loihi Neuromorphic Processor”, The International Joint Conference on Neural Networks (IJCNN), at the IEEE World Congress on Computational Intelligence (WCCI), July 2020.
11. V. Venceslai, A. Marchisio, I. Alouani, M. Martina, M. Shafique, “NeuroAttack: Undermining Spiking Neural Networks Security through Externally Triggered Bit-Flips”, The International Joint Conference on Neural Networks (IJCNN), at the IEEE World Congress on Computational Intelligence (WCCI), July 2020.
12. A. Marchisio, G. Nanfa, F. Khalid, M. A. Hanif, M. Martina, M. Shafique, “Is Spiking Secure? A Comparative Study on the Security Vulnerabilities of Spiking and Deep Neural Networks”, The International Joint Conference on Neural Networks (IJCNN), at the IEEE World Congress on Computational Intelligence (WCCI), July 2020.
13. A. Marchisio, B. Bussolino, A. Colucci, M. Martina, G. Masera, and M. Shafique. “Q-CapsNets: A Specialized Framework for Quantizing Capsule Networks”, IEEE/ACM 57th Design Automation Conference (DAC), July 2020.
14. A. Marchisio, V. Mrazek, M. A. Hanif, and M. Shafique, “ReD-CaNe: A Systematic Methodology for Resilience Analysis and Design of Capsule Networks under Approximations”, IEEE/ACM 23rd Design, Automation and Test in Europe Conference (DATE), March, 2020.
15. A. Marchisio, M. A. Hanif, F. Khalid, G. Plastiras, C. Kyrkou, T. Theocharides, and M. Shafique, “Deep Learning for Edge Computing: Current Trends, Cross-Layer Optimizations, and Open Research Challenges”, IEEE/ACM International Symposium on VLSI (ISVLSI), July 2019.
16. A. Marchisio, M. A. Hanif, and M. Shafique, “CapsAcc: An Efficient Hardware Accelerator for CapsuleNets with Data Reuse”, IEEE/ACM 22nd Design, Automation and Test in Europe Conference (DATE), March 2019.
17. A. Marchisio, M. A. Hanif, M. Martina, and M. Shafique, “PruNet: Class-Blind Pruning Method for Deep Neural Networks”, The International Joint Conference on Neural Networks (IJCNN), at the IEEE World Congress on Computational Intelligence (WCCI), July 2018.
Journal Papers
1. A. Marchisio, V. Mrazek, M. A. Hanif, M. Shafique, “FEECA: Design Space Exploration for Low-Latency and Energy-Efficient Capsule Network Accelerators” in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2021.
2. A. Marchisio, V. Mrazek, M. A. Hanif, M. Shafique. “DESCNet: Developing Efficient Scratchpad Memories for Capsule Network Hardware”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2021.
3. M. Capra, B. Bussolino, A. Marchisio, G. Masera, M. Martina, M. Shafique. “Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead”, IEEE Access, 2020.
4. M. Capra, B. Bussolino, A. Marchisio, M. Shafique, G. Masera, and M. Martina. “An Updated Survey of Efficient Hardware Architectures for Accelerating Deep Convolutional Neural Networks”, MDPI Future Internet, 2020.
5. M. A. Hanif, A. Marchisio, T. Arif, R. Hafiz, S. Rehman, and M. Shafique, “X-DNNs: Systematic Cross-Layer Approximations for Energy-Efficient Deep Neural Networks”, in ASP Journal of Low Power Electronics (JOLPE), Vol. 14, N°4, December 2018 – Special Issue on Machine Learning and Artificial Intelligence in Low Power Electronics.
Workshop Papers
1. A. Marchisio, G. Nanfa, M. Martina, and M. Shafique, “Security Vulnerabilities of Deep, Capsule and Spiking Neural Networks against Adversarial Attacks”, at IEEE International Workshop on Reliable and Trustworthy Machine Learning (RTML), at the 50th International Test Conference (ITC), Washington, DC, USA, November 2019.
2. A. Marchisio, G. Nanfa, F. Khalid, M. A. Hanif, M. Martina, and M. Shafique, “CapsAttacks: Robust and Imperceptible Adversarial Attacks on Capsule Networks”, at ICML 2019 Workshop on Uncertainty & Robustness in Deep Learning (UDL), at the 36th International Conference on Machine Learning (ICML), Long Beach, CA, USA, June 2019.
3. A. Marchisio, R. V. W. Putra, M. A. Hanif, and M. Shafique, “HW/SW Co-Design and Co-Optimizations for Deep Learning”, Workshop on INTelligent Embedded Systems Architectures and Applications (INTESA), at the Embedded Systems Week (ESWeek), October 2018.
Presentations at Conferences/Workshops
• 2021-September Alberto Marchisio presents his paper “R-SNN: An Analysis and Design Methodology for Robustifying Spiking Neural Networks against Adversarial Attacks through Noise Filters for Dynamic Vision Sensors” at IEEE/RSJ IROS.
• 2021-July Alberto Marchisio presents his paper “DVS-Attacks: Adversarial Attacks on Dynamic Vision Sensors for Spiking Neural Networks” at IJCNN-IEEE WCCI.
• 2021-July Alberto Marchisio presents his paper “CarSNN: An Efficient Spiking Neural Network for Event-Based Autonomous Cars on the Loihi Neuromorphic Research Processor” at IJCNN-IEEE WCCI.
• 2021-February Alberto Marchisio presents his paper “Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters” at IEEE/ACM DATE.
• 2020-November Alberto Marchisio presents his paper “NASCaps: A Framework for Neural Architecture Search to Optimize the Accuracy and Hardware Efficiency of Convolutional Capsule Networks” at IEEE/ACM ICCAD.
• 2020-July Alberto Marchisio presents his paper “FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule Networks” at IJCNN-IEEE WCCI.
• 2020-July Alberto Marchisio presents his paper “An Efficient Spiking Neural Network for Recognizing Gestures with a DVS Camera on the Loihi Neuromorphic Processor” at IJCNN-IEEE WCCI.
• 2020-July Alberto Marchisio presents his paper “NeuroAttack: Undermining Spiking Neural Networks Security through Externally Triggered Bit-Flips” at IJCNN-IEEE WCCI.
• 2020-July Alberto Marchisio presents his paper “Is Spiking Secure? A Comparative Study on the Security Vulnerabilities of Spiking and Deep Neural Networks” at IJCNN-IEEE WCCI.
• 2020-March Alberto Marchisio presents his paper “ReD-CaNe: A Systematic Methodology for Resilience Analysis and Design of Capsule Networks under Approximations” at IEEE/ACM DATE.
• 2019-November Alberto Marchisio presents his paper “Security Vulnerabilities of Deep, Capsule and Spiking Neural Networks against Adversarial Attacks” at IEEE RTML Workshop @ ITC.
• 2019-June Alberto Marchisio presents his paper “CapsAttacks: Robust and Imperceptible Adversarial Attacks on Capsule Networks” at UDL Workshop @ ICML.
• 2019-March Alberto Marchisio presents his paper “CapsAcc: An Efficient Hardware Accelerator for CapsuleNets with Data Reuse” at IEEE/ACM DATE.
• 2018-October Alberto Marchisio presents his paper “HW/SW Co-Design and Co-Optimizations for Deep Learning” at INTESA Workshop @ ESWeek.
• 2018-July Alberto Marchisio presents his paper “PruNet: Class-Blind Pruning Method for Deep Neural Networks” at IJCNN-IEEE WCCI.