I am a Senior Researcher at the Dalle Molle Institute for Artificial Intelligence (Istituto Dalle Molle di studi sull'intelligenza artificiale), affiliated with Università della Svizzera italiana and Scuola Universitaria Professionale della Svizzera italiana. My work centers on state-of-the-art Machine Learning applied to real-world problems.
Contact information:
Michael Wand
Dalle Molle Institute for Artificial Intelligence USI-SUPSI
Polo universitario Lugano - Campus Est, Via la Santa 1
CH-6962 Lugano-Viganello
E-Mail: michael.wand "att" supsi.ch
More access and contact information.
See also Research and Projects for information about my ongoing work.
A large part of my research has been dedicated to the application of speech recognition methods to
Silent Speech, where an acoustic signal is not available (e.g. for speech-impaired persons) or undesired
(e.g. for confidential communication in the public). A method of choice is Electromyography (EMG),
where electrical signals from the facial muscles are captured with surface electrodes. The resulting signal is fed into a suitably adapted speech
recognizer (EMG-to-text), or alternatively, a speech synthesizer (EMG-to-speech). I also work on Lipreading, where speech is recognized from images
of a person's face. Here the goal is to leverage the power of contemporary image processing towards this exciting task.
I am interested in all kinds of applications of machine learning to analysis of challenging, real-life data:
A field which is both rewarding, and offers a large variety of challenges.
I was a Marie Curie fellow in the Prototouch project, where I worked
on machine learning for diverse kinds of data related to haptics and haptic/tactile devices. I
continued this line of research within the INPUT project, where an excellent European Consortium
worked on making the control of upper limb prostheses versatile and straightforward. The method of choice is the electromyographic signal,
captured on the arm stump, processed by a powerful neural network based machine learning system. Since 2021, I have been managing the IDSIA
research within the AIDD and AiChemist project, where machine learning is applied to solve high-end chemical and pharmaceutical
challenges, aiming towards a One Chemistry model that can predict outcomes of chemical reactions, derive properties of compounds, and help in molecule generation and synthesis.
(Image credit: www.publicdomainpictures.net, public domain by Mohamed Mahmoud Hassan)
I am interested in the properties of neural networks, particularly with respect to the data representation in trained networks, and with the
training process itself. This bridges the gap between my interests in applied machine learning and the theoretical foundations of our
field. (Photo credit: "A pampered culture" by Parthiv Haldipur on Flickr, under
CC BY-NC 2.0 license).
The IDSIA is located in beautiful Ticino, located at the southern border of Switzerland and
featuring a unique blend of a moutain region and warm, mediterranean summers (apparently, summer starts in march and end in october). Hiking is
one of my favorite pastimes, and I have collected a few photos in this area.