Giuseppe Barbalinardo

Ciao, I am Giuseppe

I've always been curious. Luckily, that curiosity has led me to a career solving complex problems at the intersection of science and technology.

My PhD in Chemical Physics provided me not only with a scientific foundation but also instilled a commitment to rigorous research. Coupled with my extensive experience in data, software development, and AI, I am able to not just lead tech and research teams but brainstorm and collaborate with them. Today, I use my combined expertise to develop meaningful innovation in health and robotics.

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Science

I obtained a summa cum laude M.Sc. in theoretical physics. During my academic career, I was honored with a fellowship from the Molecular Sciences Software Institute under the NSF, where we developed the kALDo software—a cutting-edge tool for modeling heat transport at the nanoscale. My research has led to over ten publications in prestigious international peer-reviewed journals, including Nature Communications.

Technology

I obtained a summa cum laude M.Sc. in theoretical physics. During my academic career, I was honored with a fellowship from the Molecular Sciences Software Institute under the National Science Foundation, where we developed the kALDo software—a cutting-edge tool for modeling heat transport at the nanoscale. My research has been published in over ten articles in prestigious international peer-reviewed journals, including Nature Communications.

Sustainability

I have a deep interest in sustainability, specifically in material design. My academic research focused on designing efficient materials with high thermal performance. Additionally, I founded WeVux, a design blog that champions sustainable innovation. As part of that, I spearheaded the creation of a material design map, a tool that connects manufacturers and architects with sustainable materials, fostering eco-friendly practices across industries.

Portfolio

Heat is a mysterious quantity that has puzzled scientists for centuries, and its understanding is today more important than ever. We can simulate heat transport at the nanoscale using numerical models, at its fundamental atomic level. kALDo is a modern Python-based software that implements both the Boltzmann Transport equation and the Quasi-Harmonic Green Kubo method, which runs on GPUs and CPUs using Tensorflow. It is released open-source, for the scientific community to use and develop.

Discover kALDo

In a world where information is accessible by almost everyone and everywhere, the next big challenge is to decouple meaningful data from noise.
ERGO, is the dashboard for validating news. It is a AI powered platform that pulls the latest stories from various media sources to deliver claims with greater context so readers can better understand the landscape of current events.

Discover ERGO

Past projects
I worked as an Engineering Manager at Grio, in San Francisco. As a consultant, I had the opportunity to help tens of companies to expand and improve their mobile and web platforms, and I have being exposed to many progemming languages.

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Publications and Research

Ultrahigh Convergent Thermal Conductivity of Carbon Nanotubes from Comprehensive Atomistic Modeling

July, 2021 - Physical Review Letters

Anomalous heat transport in one-dimensional nanostructures, such as nanotubes and nanowires, is a widely debated problem in condensed matter and statistical physics, with contradicting pieces of evidence from experiments and simulations.Using a comprehensive modeling approach, comprised of lattice dynamics and molecular dynamics simulations...

Efficient Anharmonic Lattice Dynamics Calculations of Thermal Transport in Crystalline and Disordered Solids

September, 2020 - Journal of Applied Physics

Understanding heat transport in semiconductors and insulators is of fundamental importance because of its technolog-ical impact in electronics and renewable energy harvesting and conversion. Anharmonic Lattice Dynamics provides a powerful framework for the description of heat transport at the nanoscale... Source code

Neural network reproduces vibrational effects in manganese-germanium

June, 2020 - American Institute of Physics, Scilight

The machine learning method has been applied for the first time to a binary compound. Researchers are increasingly using neural networks as a machine learning method to analyze the atomic structure of complex materials. Although the method has been applied to phase transitions in single compounds, its transferability across compositions of binary compounds has never been tested...

Modeling heat transport in crystals and glasses from a unified lattice-dynamical approach

August, 2019 - Nature Communications

We introduce a novel approach to model heat transport in solids, based on the Green-Kubo theory of linear response. It naturally bridges the Boltzmann kinetic approach in crystals and the Allen-Feldman model in glasses, leveraging interatomic force constants and normal-mode linewidths computed at mechanical equilibrium...

A Statistical Physics Model for Demand-Supply Imbalance in Stock Market Prices

June, 2019 - UC Davis

We introduce a novel approach to model heat transport in solids, based on the Green-Kubo theory of linear response. It naturally bridges the Boltzmann kinetic approach in crystals and the Allen-Feldman model in glasses, leveraging interatomic force constants and normal-mode linewidths computed at mechanical equilibrium...

An introduction to probabilistic programming

Jul, 2018 - Grio Tech Talk, Youtube, SF

In a world of data, where everything is represented by a probabilities, programming languages are providing new kind of native variables, distributions. Starting from an introduction of probability and Bayes theorem, In this video, we show how modern Machine Learning can take advantage of new probabilistic programming...

Compressing sensing using the Least Absolute Shrinkage and Selection Operator

December, 2016 - Presentation at UC Davis

In a world of data, where everything is represented by a probabilities, programming languages are providing new kind of native variables, distributions. Starting from an introduction of probability and Bayes theorem, In this video, we show how modern Machine Learning can take advantage of new probabilistic programming... Source code

An introduction to Quantum Annealing

November, 2016 - UC Davis

In 2011, the Canadian company D-Wave announced D-Wave One, the first commercially available quantum computer based on Rainer, a 128 superconducting flux qubits processor. Since very early age, the D-Wave computer had been used as a heuristic minimizer of the Ising energy functions. In the last few years, many institutions supported the research for the use of this machine as an optimizer...

Server side swift using IBM Kitura

Aug, 2016 - Grio Tech Talk, Youtube, SF

Swift has gained a lot of popularity during recent years. From being a language used to develop only Apple devices, this programming language, has recenlty expanded its applications to many other field. A recent example is Android development. In this video we show how to quickly create a web server usign Swift and IBM Kitura... Source code

Apple TV prototyping with Interface Builder

March, 2016 - Grio Tech Talk, SF

With the acquisition of Next in 1997, a new tool was initiated into the Apple family. Originally known as an enhancement of OpenStep, called NextStep, it caught the attention of the developer community under the name of Interface Builder, as part of the XCode suite. Now about to celebrate its 20th birthday, Interface Builder represents the most powerful IDE to... Source code

Parallel computing with a GPU

May, 2015 - Grio Tech Talk, SF

Graphic Processor Units are becoming more and more important in recent years and are spreading into many different fields, some of which include: computational finance, defense and intelligence, machine learning, fluid dynamics, structural mechanics, electronic biology, physics, chemistry, numerical analysis and security. There are many reasons why a... Source code

A Monte Carlo simulation for predicting the World Cup

July, 2014 - Grio Tech Talk, SF

Several weeks ago I tried to predict who would win the World Cup. I faced this interesting problem I want to share: how can we relate the outcome of the World Cup with the strength of the teams... Source code

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