Agenda

MEST Symposium

Mini Symposium on Hardware Security

Three talks from leading companies in the industry: Brighsight, Intrinsic ID and Riscure with the following topics:

  1.    “Past , Present and Future of Hardware Attacks on Smart Cards and SOCs” by Gerard van Battum, Sr. Security Evaluator at Brightsight;
  2.     “Removing the barriers of securing a broad range of IoT devices” by Dr. Georgios Selimis, Senior Security Engineer, Intrinsic ID;
  3.    “How to use Deep Learning for hardware security testing?” by Marc Witteman (MSc), Chief Executive Officer, Riscure.
Organized by the Micro-electronic Systems and Technology Association (MEST).

Free but required registration at the link below.

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Agenda

Microelectronics Colloquium

Sten Vollebregt, Massimo Mastrangeli, Daniele Cavallo

Tenure track colloquium

Daniele Cavallo (TS group); wideband phased arrays for future wireless communication terminals, Massimo Mastrangeli (ECTM Group); Towards smart organs-on-chip, Sten Vollebregt (ECTM group) Emerging electronic materials: from lab to fab

Signal Processing Seminar

Krishnaprasad Nambur Ramamohan

Signal processing algorithms for acoustic vector sensors

Symposium MRI for Low-Resource Setting

Steven Schiff, Johnes Obungoloch

Sustainable Low-Field MRI Technology for Point of Care Diagnostics in Low-Income Countries

Kick-off meeting of the project "A sustainable MRI system to diagnose hydrocephalus in Uganda"

Signal Processing Seminar

Peter Gerstoft

Machine learning in physical sciences

Machine learning (ML) is booming thanks to efforts promoted by Google. However, ML also has use in physical sciences. I start with a general overview of ML for supervised/unsupervised learning. Then I will focus on my applications of ML in array processing in seismology and ocean acoustics. This will include source localization using neural networks or graph processing. Final example is using ML-based tomography to obtain high-resolution subsurface geophysical structure in Long Beach, CA, from seismic noise recorded on a 5200-element array. This method exploits the dense sampling obtained by ambient noise processing on large arrays by learning a dictionary of local, or small-scale, geophysical features directly from the data.

Signal Processing Seminar

Aydin Rajabzadeh

manufacturing defect detection