Alberto Marchisio

Alberto Marchisio
Projektass. Dott.mag. BSc
Phone +43 (1) 58801-18203
Fax +43 (1) 58801-18297

Vienna University of Technology
Department of Computer Engineering
Embedded Computing Systems
Treitlstrasse 3, 2nd floor, 1040 Wien, Austria

Short Biography

Mr. Alberto Marchisio received his B.Sc. degree in Electronic Engineering from Polytechnic University of Turin, Turin, Italy, in October 2015. He received his M.Sc. degree in Electronic Engineering (Electronic Systems) from Polytechnic University of Turin, Turin, Italy, in April 2018. Currently, he is a Ph.D. Student at Computer Architecture and Robust Energy-Efficient Technologies (CARE-Tech.), Embedded Computing Systems, Institute of Computer Engineering, Vienna University of Technology (TU Wien), Vienna, Austria, under the supervision of Prof. Dr. Muhammad Shafique. He is also a Project Assistant at the Institute of Computer Technology, Faculty of Electrical Engineering and Information Technology, Vienna University of Technology (TU Wien), Vienna, Austria. His main research interests include VLSI architecture design, machine learning, brain-inspired computing and emerging computing technologies.


Conference/Symposium Papers

  • A. Marchisio, M. A. Hanif, 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.
  • A. Marchisio, M. A. Hanif, M. Martina, M. Shafique, “PruNet: Class-Blind Pruning Method for Deep Neural Networks”, The International Joint Conference on Neural Networks (IJCNN), July 2018.

Workshop Papers

  • 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.

Journal Papers

  • 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".

Archive Publications

  • A. Marchisio, M. A. Hanif, S. Rehman, M. Martina, and M. Shafique, “A Methodology for Automatic Selection of Activation Functions to Design Hybrid Deep Neural Networks”, CoRR abs/1811.03980, October 2018.

Master Thesis

  • Alberto Marchisio, “Optimizing Deep Neural Networks on GPUs“. Joint supervision of Prof. Dr. Maurizio Martina, Polytechnic University of Turin, and Prof. Dr. Muhammad Shafique, Vienna University of Technology. April 2018.