Lucky Encounters: From Optical Tweezers to deep Learning
Giovanni Volpe
ICFO Alumni Seminar (Online)
16 June 2020
In this semi-autobiographical talk, I will look back at my career and its evolution. It all started at ICFO with a PhD on optical tweezers in 2008. It then continued with a series of diverse research projects on different fields: active matter, stochastic thermodynamics, neurosciences and, finally, deep learning. I will emphasize how my career has been shaped by lucky encounters. Encounters that have taken me to places and topics I’d never have imagined beforehand. But it all makes sense, in insight.
The SAIS workshop is a forum for building the Swedish AI research community and nurture networks across academia and industry. Because of the concern for the COVID-19, the workshop this year is an online conference.
The contributions of Saga Helgadottir will be presented according to the following schedule:
Saga Helgadottir Medical Diagnosis with Machine Learning Date: 17 June 2020 Time: 15:00 CEST
Giovanni Volpe will give an invited presentation at Nanolight 2020.
The conference, organized by Luis Martín Moreno (ICMA, CSIC – U. Zaragoza) and Niek van Hulst (ICFO, Barcelona), aims at the exploration of the frontiers in the field of subwavelength optics. It is meant to facilitate the interaction between worldwide researchers working in the field, with a special emphasis on interaction between young and more experienced researchers.
The conference is held in Benasque, Spain, from 8 to 14 March 2020.
The contributions of Giovanni Volpe will be presented according to the following schedule:
Giovanni Volpe Deep Learning for Microscopy Date: 12 March 2020 Time: 15:35 CET
Alessandro Magazzù and Giovanni Volpe will give invited presentations at the Kick-off meeting of SPACE Tweezers (Spectroscopy of Planetary and AtmospheriC particulatE by optical Tweezers).
SPACE Tweezers proposes research activities to trap and characterise spectroscopically extraterrestrial particles and their analogs. The opportunity to apply optical tweezers to planetary particulate matter can pave the way for space applications for in situ analyses and/or for sample return of particles in pristine conditions, i.e. preventing contamination and alteration, unlike collection methods so far used in space exploration.
The meeting, organised by Maria Grazia Donato, Pietro Guicciardi, Maria Antonia Iatì, and Onofrio M. Maragò, will take place at CNR-IPCF, Messina, on 18-19 February 2020.
The contributions of Giovanni Volpe and Alessandro Magazzù will be presented according to the following schedule:
Giovanni Volpe Optical Tweezers Activities in Gothenburg Date: 19 February 2020 Time: 10:55 CET
Alessandro Magazzù Controlling the Dynamics of Colloidal Particles by Critical Casimir Forces using Blinking Optical Tweezers Date: 19 February 2020 Time: 11:20 CET
On Monday, the 16th of December, Falko Schmidt, will visit Frank Cichos’ lab at the University of Leipzig. He will present latest research on a nanoscopic particle in a harmonic trap.
On Friday, the 13th of December, Falko Schmidt, will visit Juliane Simmchen’s lab at the Technical University of Dresden. He will present results on Liquid-Liquid-Phase Separation a project that is currently in collaboration with their lab.
Light-induced phase separation power novel micro machines Falko Schmidt, and Giovanni Volpe
Light at the Nanoscale Conference, Chalmers University, Gothenburg, Sweden
5 December 2019, 16:30-18:30
Focused laser light is used to trap a micronsized absorbing particle around its beam center where it performs constant orbital rotation. The light-induced local phase separations create a concentration gradient on which the particle moves along. Large patches of absorbing material on the particle’s surface give rise to a torque required for steady rotation1
Phase separation is a phenomena that commonly exists in nature, from the freezing of ice to the intrinsic mechanism of the cell to order matter. We are exploiting phase separations to produce new types of miniaturised machines, in particular micron and nano sized engines1as well as to form self-assembled colloidal molecules2. We control their behaviour using only light and varying its ambient temperature making this a simple tool to study complex matter3. This will enhance the development of future medicine where nano robots deliver drugs specifically to the local infection side.
References:1. F. Schmidt et al. Microscopic engine powered by critical demixing, Phys Rev Lett 120, 068004, 2018
2. F. Schmidt et al. Light-controlled assembly of active colloidal molecules, J Chem Phys150, 094905, 2019
3. S. Bo et al. Measurement of anomalous diffusion using recurrent neural networks, Phys Rev E 100, 010102(R), 2019
Machine learning as a tool for the natural sciences: Opportunities and challenges
Giovanni Volpe
Invited Talk at BRC Day “Biomaterials meets AI”, University of Gothenburg, Gothenburg, Sweden, 12 November 2019
Abstract: Data-driven machine-learning methods are more and more widely used in the natural sciences. Machine learning offers unprecedented opportunities, but it also poses unexpected practical and fundamental challenges. Most importantly, machine-learning methods often work as black boxes, and therefore it can be difficult to understand and interpret their results. Here, we present an overview of the current state of the art of the adoption of machine learning in active-matter research. Finally, we discuss the opportunities and challenges that are emerging, highlighting how active matter and machine learning can work together for mutual benefit.
Bio: Giovanni Volpe is Associate Professor at the University of Gothenburg, where he leads the Soft Matter Lab (http://www.softmatterlab.org/).
He has published more than 80 articles on diverse topics including optical trapping, active matter, neurosciences, and machine learning.
He has co-authored the book “Optical Tweezers: Principles and Applications” (Cambridge University Press, 2015).
He is the recipient the ERC Starting Grant ComplexSwimmers, coordinator of the MSCA Innovative Training Networks ActiveMatter, and the KAW research grant “Active Matter Goes Smart”.
He is one of the chairs of the Conference Emerging Topics in Artificial Intelligence at the SPIE Optics & Photonics Meeting held annually in San Diego (CA).
Machine learning for active matter
Giovanni Volpe
Introductory Talk at CECAM Workshop “Active Matter and Artificial Intelligence”
CECAM-HQ-EPFL, Lausanne, Switzerland
30 September – 2 October, 2019
Data-driven machine-learning methods are more and more widely used in the natural sciences. Active-matter research is no exception and has recently started experiment- ing machine-learning approaches. Machine learning offers unprecedented opportunities, but it also poses unexpected practical and fundamental challenges. Most importantly, machine-learning methods often work as black boxes, and therefore it can be difficult to understand and interpret their results. Here, we present an overview of the current state of the art of the adoption of machine learning in active-matter research. Finally, we discuss the opportunities and challenges that are emerging, highlighting how active matter and machine learning can work together for mutual benefit.
