Welcome to my homepage!
phone: +41 44 63 259 12
IIS project page
I am a Ph.D. student at the Department of Information Technology and Electrical Engineering at ETH Zurich in the Digital Circuits and Systems Group, which is led by Prof. Luca Benini. Moreover, I am a proud awardee of the 2020 IBM PhD Fellowship.
My research interests lie at the border of accurate AI algorithms and approximate emerging technologies. Particularly, I am exploring brain-inspired hyperdimensional computing in the field of AI as well as communication. My interests also include energy efficient brain-computer interfaces targeting next generation human-machine interaction.
Projects at IIS
If you are interested in doing a Group project, Semester thesis, or Master's thesis with me, please visit my IIS project page.
- T. Ingolfsson, M. Hersche, X. Wang, N. Kobayashi, L. Cavigelli, L. Benini "EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfaces", Accepted in IEEE International Conference on Systems, Men, and Cybernetics (SMC 2020), 2020. [ preprint ]
- M. Hersche, E. Mello Rella, A. Di Mauro, L. Benini, A. Rahimi "Integrating Event-based Dynamic Vision Sensors with Sparse Hyperdimensional Computing: A Low-power Accelerator with Online Capability", in ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED 2020), 2020. [ PDF] [ Slides ] [ Video ] [Artifacts]
- T. Schneider, X. Wang, M. Hersche, L. Cavigelli, L. Benini, "Q-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain--Machine Interfaces", Accepted in IEEE International Workshop on Deep Learning on Edge for Smart Health and Well-being Applications (EdgeDL), 2020. [ PDF] [Artifacts]
- X. Wang, M. Hersche, B. Tömekce, B. Kaya, M. Magno, L. Benini, "An Accurate EEGNet-based Motor-Imagery Brain-Computer Interface for Low-Power Edge Computing", In IEEE International Symposium on Medical Measurements and Applications (MEMEA), 2020. [ PDF] [Artifacts]
- M. Hersche, L. Benini, A. Rahimi, "Binary Models for Motor-Imagery Brain-Computer Interfaces: Sparse Random Projection and Binarized SVM", In IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2020. [PDF] [Slides] [Artifacts]
- M. Hersche, S. Sangalli, L. Benini, A. Rahimi, "Evolvable Hyperdimensional Computing: Unsupervised Regeneration of Associative Memory to Recover Faulty Components", In IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2020. [PDF]
- M. Hersche, P. Rupp, L. Benini, A. Rahimi, "Compressing Subject-Specific Brain-Computer Interface Models into One Model by Superposition in Hyperdimensional Space", In ACM/IEEE Design, Automation, and Test in Europe Conference (DATE), 2020.[PDF] [Slides] [Artifacts]
- M. Hersche, J. d. R. Millan, L. Benini, A. Rahimi, "Exloring Embedding Methods in Binary Hyperdimensional Computing: A Case Study for Motor-Imagery based Brain-Computer Interfaces", arXiv preprint, 2018. [PDF] [Artifacts]
- M. Hersche, T. Rellstab, P. D. Schiavone, L. Cavigelli, L. Benini, A. Rahimi, "Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral Features", In IEEE European Signal Processing Conference (EUSIPCO), 2018. [PDF] [Slides] [Artifacts]