Hes-so Valais

Health Tech Lunch

Coming soon...

Health Tech Lunch - 17.06.2021, 12h00-13h00 - Haute école de travail social, Corinna Bille (salle 501), Sierre & Online

Presentation by David Pichonnaz (Professeur HES assistant, Institut Travail Social, HES-SO Valais-Wallis)


David Pichonnaz est sociologue des groupes professionnels et du travail. Ses recherches portent sur les métiers relationnels du service public, en particulier le travail social, policier et soignant, ainsi que sur les parcours de socialisation, qu’il étudie en s’appuyant sur l’analyse dispositionnelle.

Title : Vivre avec la mucoviscidose et s’insérer professionnellement : l’impact des ressources familiales et du rapport à la maladie 


Cette présentation rend compte des premiers résultats d’une étude en cours, basée sur des entretiens semi-directifs approfondis, conduits avec 25 personnes vivant avec la mucoviscidose, en Suisse. La recherche part du constat, établi par la littérature, que les modalités des parcours de formation et d’insertion professionnelles de ces individus ne sont pas significativement corrélés avec la gravité de la maladie, ni avec l’étendue ou la difficulté des traitements. Pourtant, les travaux existants ont négligé la prise en compte des inégalités sociales, de même que du vécu subjectif de la maladie. Tout incite à penser, pourtant, que l’insertion professionnelle doit être étudiée, pour cette population particulière, en tenant compte de facteurs sociaux : d’une part, les ressources familiales disponibles et leur transmission (ou non), et, d’autre part, le rapport à la maladie (davantage que les symptômes objectivement mesurés).


  • 12h00-12h45 : Talk
  • 12h45-13h00 : Q&A

Registration : https://doodle.com/poll/rg6thm5dzkfdwpxn?utm_source=poll&utm_medium=link

Link to participate online : Coming soon

Health Tech Lunch - 01.06.2021, 10h30-12h00 - Campus Energypolis/HEI (room 21N105) & Online

Presentation by Bruno Correia (Tenure Track Assistant Professor, EPFL, Laboratory of Protein Design & Immunoengineering)


Throughout my PhD and postdoctoral studies I was trained in world-renowned laboratories and institutions in the United States of America (University of Washington and The Scripps Research Institute). Very early in my scientific career I found out my fascination about protein structure and function. My PhD studies evolved in the direction of immunogen design and vaccine engineering which sparked my interest in the many needs and opportunities in vaccinology and translational research. My efforts resulted in an enlightening piece of work where for the first time, computationally designed immunogens elicited potent neutralizing antibodies. During my postdoctoral studies I joined a chemical biology laboratory at the Scripps Research Institute. In this stage I developed novel chemoproteomics methods for the identification of protein-small molecule interaction sites in complex proteomes. In March 2015, I joined the École Polytechnique Fédérale de Lausanne (EPFL) – Switzerland as a tenure track assistant professor. The focus of my research group is to develop computational tools for protein design with particular emphasis in applying these strategies to immunoengineering (e.g. vaccine and cancer immunotherapy). The activities in my laboratory focus on computational design methods development and experimental characterization of the designed proteins. Our laboratory has been awarded with 2 prestigious research grants from the European Research Council. Lastly, I have been awarded the prize for best teacher of Life sciences in 2019.

Title : Expanding the landscape of functional proteins by computational design 


Finely orchestrated protein activities are at the heart of the most fundamental cellular processes. The rational and structure-based design of novel functional proteins holds the promise to revolutionize many important aspects in biology, medicine and biotechnology. Computational protein design has led the way in rational protein engineering, however many of the designed proteins have been solely focused on structural accuracy and are completely impaired of function.

I will present my group’s efforts on the development of novel computational approaches to predict and design protein function. Specifically, I will describe a new methodological framework to learn surface patterns displayed in protein structures that can be used to decipher their interactions with other molecules. I will also present a computational strategy to explore de novo protein topologies, aiming to solve prevalent problems in protein design that relate to the lack of optimal structural templates for the design of function. By expanding beyond the known protein structural space, our approaches present new paradigms for the rational design of functional proteins. I will showcase important applications for our computationally designed proteins in the domains of vaccine design, T cell-based therapies, biosensors and synthetic biology.


  • 10h30-12h00 : Talk & Q&A
  • 12h00-13h00 : Lunch at Restaurant la Ruche

Registration : https://doodle.com/poll/u99npshi5ifyhy3t?utm_source=poll&utm_medium=link

Link to participate online : Cliquez ici pour rejoindre la réunion

Health Tech Lunch - 20.04.2021, 9h45 - Online

Presentation by Stéphane Baeriswyl (Université de Berne)

Title : Design and X-ray structure determination of antimicrobial peptides


I am a motivated chemist with multidisciplinary experience. I have good knowledge in peptide synthesis and protein production & purification. My areas of expertise include microbiology (BSL2), analytics (LC/MS, NMR), microscopy and computational modeling as well. I have a PhD degree in chemistry.


  • 09:45-11:00 : Talk & Q&A

Registration : https://doodle.com/poll/54m6wtauk7ccy5h3

Health Tech Lunch - 25.01.2021, 16h00 - Online

Presentation by Iam Palatnik (Pontifical Catholic University of Rio de Janeiro, Brazil)

Title : LIME in Medical Image Classification


An application of Local Interpretable Model Agnostic Explanations (LIME) is described for two case studies: Metastases and Malaria classification. Some of the key challenges of using LIME for this purpose - most notably the instability of explanations - are discussed, as well as some potential solutions. Namely, a genetic algorithm based solution called EvEx, where explanations are evolved as the average of a Pareto Front, and Squaregrid, a parameterless rough approximation. The results seem to show that EvEx finds more consistent explanations for regions of high explanatory weight, and that Squaregrid could be a viable way to diminish the need for segmentation parameter fine tuning.


  • 16:00-16:45 : talk
  • 16:45-17:00 : Q&A