Giovanni Volpe awarded with the ERC Proof of Concept Grant

Giovanni Volpe has been awarded with the ERC Proof of Concept Grant for the research project LUCERO: Smart Optofluidic micromanipulation of Biological Samples.

The grant, consisting of 150k EUR, is meant to commercialize the research project LUCERO, providing an innovative method that combines artificial intelligence and optical tweezers to analyze cells easily and inexpensively.

The current technologies for cell analysis have many limitations: they require access to a large number of cells and considerable expertise. The available methods are also labor-intensive and in some cases the cells are destroyed.

The new method developed in LUCERO simplifies the work and lowers the costs of biomedical research by allowing ordinary standard microscopes, which are already in use in biomedical laboratories, to be used to perform the cell analysis.

The method of LUCERO can be used in several areas, from artificial insemination to forensic medicine. It has potentially a large commercial market.

Giovanni Volpe expects that LUCERO will provide around 20 jobs for university-trained experts and researchers within the next five years.

The project LUCERO has already received initial funding and support from two different organizations (Venture Cup and SPIE). Two doctoral students, Falko Schmidt and Martin B. Mojica, are part of LUCERO’s contributors team.

Links:
Press release of the Swedish Research Council: in English, in Swedish.
News on Gothenburg University website: in Swedish.

The AnDi challenge: an “anomalous” competition

Logo of the AnDi challenge.

Researchers from ICFO, UVic, Gothenborg University, Politecnica de Valencia and Potsdam University organize the AnDi challenge, a physics challenge to address Brownian motion and Anomalous diffusion.

Brownian motion was first observed in 1827 by Robert Brown: pollen grains suspended in water show a characteristic erratic motion. Almost 80 years after, Albert Einstein provided a theoretical foundation for the Brownian motion. Though the Brownian motion is observed in many different systems, significant deviations from it have also been observed, starting from biological systems to economics.

The deviation from Brownian motion is indicated with the term Anomalous diffusion. It is connected to non-equilibrium phenomena, complex environments, flows of energy and information, and transport in living systems. To understand the nature of such systems one must correctly identify the physical origin of the anomalous diffusion, and correctly characterize it, through the calculation of its properties. A simple data analysis of trajectories, though, often provides limited information, in particular when the trajectories are either short, or noisy, or irregularly sampled, or featuring mixed behaviors. Several methods going beyond the calculation of classical estimators have been proposed, in the last years, to quantify anomalous diffusion.

The AnDi challenge has been thought as a competition to test these methods as well as other alternative approaches, by bringing together the scientific community currently working on the quantification of the anomalous diffusion.

The use of the same reference datasets will allow an unbiased assessment of the performance of published and unpublished methods for characterizing anomalous diffusion from single trajectories. Participants can submit the results of their analysis on the internet until November 1st, 2020. These results will be then automatically scored and ranked among all competitors.

In addition to the main objective of the AnDi Challenge, the top-ranked participants will be invited to present their results in a workshop held at ICFO, in Barcelona, on February 17-20, 2021.

Organizers:

Website: www.andi-challenge.org

Codalab: https://competitions.codalab.org/competitions/23601

e-mail: andi.challenge@gmail.com

twitter: @AndiChallenge

Shaping the future of machine learning for active matter

Machine learning has proven to be very useful for the study of active matter, a collective term referring to things like cells and microorganisms. The field is quite new and growing fast. In an attempt to inspire more researchers to try the methods a group of scientists have published a paper in prestigious publication Nature Machine Intelligence reviewing what has been accomplished so far – and what lies ahead. Continue reading (English)

Press release:
Shaping the future of machine learning for active matter (In English)
Formar framtiden för AI-forskning på aktiv materia (In Swedish)

Article:
Machine learning for active matter

An algorithm that learns to diagnose a genetic disease

Researchers at the University of Gothenburg, together with researchers from Portugal, have now found a way to estimate the probability that a patient will suffer from a common genetic disease by training an algorithm using patient data. Continue reading (in English)

Press release:
Algoritm lär sig diagnostisera genetisk sjukdom (in Swedish)
An algorithm that learns to diagnose genetic disease (in English)

Article: Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning

Start-up “Lucero” Semi-finalist in SPIE Startup Challenge

Our idea Lucero, has reached the semi-final for the SPIE Start-up challenge, where will pitch in front of a jury at Photonics West in San Francisco, CA, USA on the 4th of February 2020.

Lucero will compete, among other 41 semifinalists, for cash prizes and business support.

In addition, Lucero was awarded one of the three Early Stage Entrepreneurship Travel Grants to attend the semi-final.

The start-up is aiming to make cutting-edge laser technology easy to use and available to anyone by combining it with commercial microscope. The product and software combo utilizes optical tweezers in a brand-new way – and bridges the gap between physics and other scientific fields that would greatly benefit from easier access to this tool.

In December, Lucero was ranked among the best 5 business ideas in West Sweden.

Team components: Christopher Jacklin, Rich Zapata Rosas, Felix Mossberg, Falko Schmidt, Alejandro Diaz Tormo and Martin Mojica-Benavides.

Links: Lucero Homepage

Start-up “Lucero Bio” among the best 5 business ideas in West Sweden

Falko Schmidt and other researchers at the University of Gothenburg, in collaboration with Business students at the Chalmers School of Entrepreneurship, have received early acclaimfor their Start-up idea “Lucero Bio”.

Lucero Bio was ranked among one of the top 5 business ideas in West Sweden by Venture Cup Sweden. Out of the 376 ideas that were submitted to the competition, nearly half came from the western region of Sweden.

The start-up is aiming to make cutting-edge laser technology easy to use and available to anyone by combining it with commercial microscope. The product and software combo utilizes optical tweezers in a brand-new way – and bridges the gap between physics and other scientific fields that would greatly benefit from easier access to this tool.

Team components: Christopher Jacklin, Rich Zapata Rosas, Felix Mossberg, Falko Schmidt, Alejandro Diaz Tormo and Martin Mojica-Benavides.

More information:
Press release, in Swedish.
Top 20 list of the 2019 winners, in Swedish.

DeepTrack selected by Optics & Photonics News as one of the most exciting optics discoveries in 2019

Optics & Photonics News has picked Saga Helgadóttir and Aykut Argun’s work on deep learning for particle tracking (DeepTrack) as a top break-through of the year.

“This has been a really good year for me, research-wise. My publication, presenting a new AI method, garnered a lot of attention,” says Saga Helgadóttir, PhD at the Department of Physics.

The research article in question, which is now included in Optics & Photonics News’ best-of-2019 list, identifies a new way of implementing neural networks and machine learning in order to track particle motion and study surrounding microenvironments.

After the publication in mid-April, Saga Helgadóttir was contacted by both national and international press to talk about her discoveries. She has also been invited to visit research groups abroad and was a speaker at the AI in Health and Health in AI conference held in Gothenburg in August.

Currently, Saga Helgadottir is collaborating with a group of scientists at Sahlgrenska’s Wallenberg Laboratory. They are working on new ways of using deep learning in the medical field.

“I started my PhD research studying bio-hybrid microswimmers, but ended up more within the area of artificial intelligence and optics. I like this work a lot, and the positive response to my publication earlier this year has allowed me to establish myself in the AI-field.”

Text: Carolina Svensson

List of highlighted research from 2019: Optics in 2019

Saga Helgadottir’s featured summary: Deep Learning for Particle Tracking

Original press release about the research: She has discovered a new method of using AI

Saga Helgadottir interviewed by Curie, a magazine issued by the Swedish Research Council

Saga Helgadottir discussed her research with Curie, a magazine issued by the Swedish Research Council. The article gives examples of how AI is used in many research disciplines. Read the article on Curie’s webpage here.

Jalpa Soni and Falko Schmidt at the Lindau Nobel Laureate Meeting

Jalpa Soni and Falko Schmidt have been nominated by the Marie-Curie association and the Ragnar-Söderbergs foundation to attend the 69th Lindau Nobel Laureate Meeting from the 30 June till 5 July 2019. Congratulations to both!

The Lindau Nobel Laureate Meeting is an annual scientific conference that brings together Nobel laureates and young scientists to encourage scientific exchange among different generations and cultures.
The 69th meeting will be dedicated to Physics, where 580 young scientist from 88 countries will be present.

Jalpa Soni is MSCA Fellow of the Week

Our Marie-Curie postdoctoral researcher Jalpa Soni becomes the #MSCA Fellow of the Week, and gets her project highlighted on Tweeter and Facebook pages of the Marie-Skłodowska-Curie Actions

Jalpa is studying the behaviour of micro swimmers like bacteria in 3D complex environments. That will give us the understanding of how they propagate in living systems, which in turn will be used to manipulate them for medicinal advantages.One such example would be to create artificial swimmers (active particles) mimicking natural bacteria for more efficient and targeted drug-delivery applications.To monitor the movement of such micro swimmers in 3D, Jalpa has developed a customised light-sheet microscope that is capable of fast volumetric imaging. The long term goal of the project is to create active particle induced drug-delivery methods for organ-on-chip devices and to monitor the drug efficacy in real time.

This is Jalpa’s insight as a MSCA fellow:

“The unique opportunity to build a new collaborative network has been the most beneficial aspect of my MSCA fellowship. The travels for the project has allowed me to experience different research organisations and to meet experts of various fields which is very important for interdisciplinary research that I love doing.”

Project Name: ActiveMotion3D – Experimental study of three-dimensional dynamics of Active particles

Learn more about Jalpa and her project:
CORDIS: https://bit.ly/2Rz1rVD

Tweeter: https://twitter.com/MSCActions/status/1070985015754919936
FB: