Research:

My research interests lie in the development of nanotechnology for applications in electronics and neuromorphic computing. I do materials-driven research with the aim understand and control the physics and processes involved in realizing new nanoelectronic device concepts. 

Ferroelectric memristors: I currently focus on developing ferroelectric tunnel junction memristive devices based on HfO2 thin films, and their integration with III-V semiconductors. I am exploring the ability of these devices to function as synapses in artificial neuromorphic systems.

3D heterointegration: I explore how to integrate III-V nanostructures into the back-end-of-line in Si CMOS technology, using novel epitaxial methodologies with low thermal budget, based on Rapid Melt Growth and Template-Assisted Selective Epitaxy.

Previously: I pioneered antimonide-based nanowire synthesis during my PhD work, I have been strongly involved in InAs/GaSb-based tunnel field effect transistor (TFET) research both in Lund and at IBM, and at IBM I co-invented a novel method for CMOS-compatible III-V integration on Si, called Template-Assisted Selective Epitaxy (TASE).

Teaching at LTH:

• Memory technology for Machine Learning (EITP25)
  
  The purpose of this course is to give an in depth understanding for the physics of common memory device technologies with focus on non-volatile memories. Furthermore, the course covers how these memory devices can be integrated to create neuromorphic hardware for applications in machine learning and artificial intelligence. Finally, the course gives an introduction to the architectures and algorithms that are used in machine learning, to give a basic understanding for the needs that memory devices and their connections need to fulfil.
   
• Electronics (EITA35)

  This is the first course of the E program, aiming to provide an introduction to Electronics both at a theoretical and practical level.