Giovanni M. Pavan Research Group

  • Home
  • Research
  • People
  • Publications
  • ERC
  • Downloads
  • Life in the Group
  • Join the group
  • News
  • Collaborations
  • Contacts

People

The Pavan research group is split in two labs:
– Computational Physical Chemistry Laboratory (CPC Lab) @POLITO
– Computational Materials Science Laboratory (CMS Lab) @SUPSI


Prof. Giovanni M. Pavan – Full Professor

Head of CPC Lab @POLITO
Email: giovanni.pavan.at.polito.it

Head of CMS Lab @SUPSI
Email: giovanni.pavan.at.supsi.ch

Google Scholar profile


Dr. Claudio Perego – Tenured researcher

CMS Lab @SUPSI

Email: claudio.perego.at.supsi.ch

Enhanced sampling, Molecular complexity, Out of equilibrium system, Self assembly

Google Scholar profile

Brief bio


Dr. Giovanni Doni – Senior scientist

CMS Lab @SUPSI

Email: giovanni.doni.at.supsi.ch

Machine learning, Optimisation, Bayesian inference, Atomistic modelling

Brief bio


Dr. Francesco Muniz-Miranda – Non Tenure-track researcher

CPC Lab @POLITO

Email: francesco.munizmiranda.at.polito.it

DFT, TD-DFT, Molecular Dynamics (classical & ab initio), Molecular Spectroscopy

Google Scholar profile

Brief bio


Dr. Riccardo Capelli – Postdoc

CPC Lab @POLITO

Email: riccardo.capelli.at.polito.it

Enhanced sampling, Soft matter, Supramolecular dynamics

Google Scholar profile

Brief bio


Dr. Luca Pesce – Postdoc

CMS Lab @SUPSI

Email: luca.pesce.at.supsi.ch

Coarse graining, Metal-organic interactions, Enhanced sampling

Google Scholar profile

Brief bio


Dr. Charly Empereur-mot – Postdoc

CMS Lab @SUPSI

Email: charly.empereur.at.supsi.ch

Machine learning, Optimization, Material design, Self-assembly

Google Scholar profile

Brief bio


Dr. Annalisa Cardellini – Postdoc

CPC Lab @POLITO

Email: annalisa.cardellini.at.polito.it

Atomistic & coarse-grain modelling, Self-assembly

Google Scholar profile

Brief bio


Dr. Massimo Delle Piane – Postdoc

CPC Lab @POLITO

Email: massimo.dellepiane.at.polito.it

Density Functional Theory, Atomistic modeling, Enhanced sampling, Biomaterials, Adsorption

Google Scholar profile

Brief bio


Anna L. De Marco – Joint PhD student

CMS Lab @SUPSI
& Università degli Studi di Genova, Physics Department (DIFI)

Email: a.l.demarco.at.hotmail.it

Multiscale modelling, Molecular complexity, Out-of-equilibrium systems

Brief bio


Andrea Gardin – PhD student

CPC Lab @POLITO

Email: andrea.gardin.at.polito.it

Molecular & supramolecular dynamics, Soft matter

Google Scholar profile

Brief bio


Chiara Lionello – PhD student

CPC Lab @POLITO

Email: chiara.lionello.at.polito.it

Multiscale modelling, Self assembly, Stimuli-responsive materials

Google Scholar profile

Brief bio


Luigi Leanza – PhD student

CPC Lab @POLITO

Email: luigi.leanza.at.polito.it

Multiscale modelling, Molecular and supramolecular dynamics, Enhanced sampling

Google Scholar profile

Brief bio


Martina Crippa – PhD student

CPC Lab @POLITO

Email: martina.crippa.at.polito.it

Complex molecualr systems, Multiscale Modelling, Self-assembly

Brief bio


Matteo Cioni – PhD student

CPC Lab @POLITO

Email: matteo.cioni.at.polito.it

Molecular dynamics, Multiscale Modelling, Enhanced sampling

Brief bio


Giovanni M. Pavan LabFollow

Avatar
Retweet on TwitterGiovanni M. Pavan Lab Retweeted
AvatarETH Zurich@ETH_en·
24 Feb

A digital twin of our #planet is to #simulate the Earth #system in future. It is intended to support policy-​makers in taking appropriate measures to better prepare for extreme events.
https://ethz.ch/en/news-and-events/eth-news/news/2021/02/a-highly-accurate-digital-twin-of-our-planet.html

Reply on Twitter 1364455018485710848Retweet on Twitter 136445501848571084821Like on Twitter 136445501848571084849Twitter 1364455018485710848
Retweet on TwitterGiovanni M. Pavan Lab Retweeted
AvatarNature@nature·
22 Feb

News & Views: A Nature paper reports an accessible machine-learning tool that can accelerate the optimization of a wide range of synthetic reactions — and reveals how cognitive bias might have undermined optimization by humans. https://go.nature.com/2O2Apco

Reply on Twitter 1363832916527247365Retweet on Twitter 136383291652724736545Like on Twitter 1363832916527247365112Twitter 1363832916527247365
AvatarGiovanni M. Pavan Lab@LabPavan·
17 Feb

Great work @ric_capelli!
A data-driven SOAP metrics to compare & classify lipid force fields based on the local environments surrounding the lipids along MD simulations. Versatile & not restricted to lipids! Useful to compare a variety of dynamic systems! https://chemrxiv.org/articles/preprint/A_Data-Driven_Dimensionality_Reduction_Approach_to_Compare_and_Classify_Lipid_Force_Fields/14039834

Riccardo Capelli@ric_capelli

The last @LabPavan preprint is out on @ChemRxiv! We employed a dimensionality reduction approach to compare lipid force fields, and we discovered that most of the relevant differences is not in the average, but in the local representation of the system!

https://chemrxiv.org/articles/preprint/A_Data-Driven_Dimensionality_Reduction_Approach_to_Compare_and_Classify_Lipid_Force_Fields/14039834/1

Reply on Twitter 1362045457682358273Retweet on Twitter 13620454576823582732Like on Twitter 136204545768235827314Twitter 1362045457682358273
Retweet on TwitterGiovanni M. Pavan Lab Retweeted
AvatarLarissa von Krbek@vkrbek·
15 Feb

(1/2) @aprahamian & I are organizing a #SystemsChemistry symposium on March 22-23 #ChemSystemsMeet, @nanoGe_Conf. Registration is now open and free for first 30 students, curtesy of @RoySocChem (+more depending on funding)
http://nanoge.org/ChemSystemsMeet/general-information
#realtimechem
#ChemTwitter ...

Reply on Twitter 1361330271908470789Retweet on Twitter 136133027190847078932Like on Twitter 136133027190847078972Twitter 1361330271908470789
AvatarGiovanni M. Pavan Lab@LabPavan·
29 Jan

Fascinated by molecular exchange in supramolecular polymers?
Your dream is to "encode" exchange pathways in supramolecular systems?
Better to start learning how to control defects & their statistical behavior!
All this in our last @ChemRxiv preprint: https://chemrxiv.org/articles/preprint/Controlling_Exchange_Pathways_in_Dynamic_Supramolecular_Polymers_by_Controlling_Defects/13655864

Reply on Twitter 1355249816842997764Retweet on Twitter 13552498168429977643Like on Twitter 135524981684299776430Twitter 1355249816842997764
Load More...

Cookie policy

CyberChimps ©2021
This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Cookie settingsACCEPTReject
Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.
Necessary
Always Enabled

Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.

Non-necessary

Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.

SAVE & ACCEPT