Mario Dagrada

Per aspera ad astra

Dear Internet surfer, welcome to my personal website!

I am Mario Dagrada, a researcher, developer and technology enthusiast living in Eindhoven, The Netherlands. I am currently working as VP of Quantum Software at the quantum computing startup Qu&Co based in Amsterdam.

If you are viewing this page, it means that you probably know me or are interested in my profile or my services. Here you will find both information on my experiences and my past, current and (why not?) never started projects. Occasionally I will also post some reviews or advice on books and other interesting stuff.

Professional Interests

We are drowning in information but starved for knowledge. – John Naisbitt

The technology sector is a treasure trove of interesting and continuously evolving fields. I am interested in many of them, but currently my focus and energies are mainly on:

  • Software architecture and cloud technologies, particularly for distributed applications. I am currently designing and implementing service-oriented applications on AWS, leveraging the best available tools for container orchestration and infrastructure-as-a-code.

  • Quantum Computing, particularly applied to quantum chemistry simulations. Quantum computing is for me one of the most fascinating fields in technology. It combines, among other disciplines, two of my strongest passions (computer science and physics) and is a diverse and continuosly evolving field in both academic and private sectors. Today is the right moment to join the quantum computing space, but always beware of the marketing buzz around it.

  • Product management and business innovation. In my current role, I am applying the knowledge I acquired during my career on corporate innovation, design thinking and software product management to the dynamic environment of an early stage startup at its first product release. My main goal is to build, from the start, a future-proof product strategy and a sustainable software release and innovation pipeline.

Some projects I contributed to

QUBEC, the quantum computing backend for chemistry

QUBEC is cloud platform which allows to execute chemistry simulations of molecules on the most advanced quantum computers to date. It has been developed in collaboration with Schrodinger, world-leader in conventional chemistry simulations, and integrates with Schrodinger’s Maestro chemical modeling suite to offer a glimpse on what the future of quantum chemistry simulations will look like! Check here to know more.

I am the main contributor of QUBEC and my role is two-fold. On one hand, I develop and maintain the cloud infrastructure, test automation and client APIs as well as contribute to the suite of cutting-edge quantum computing algorithms which powers QUBEC. On the other hands, I am responsible of product management, feature roadmap and in general all the processes associated with the launch, improvement and vision of a deep tech product. If you want to know more, please contact me at mario.dagrada@quandco.com.

TurboRVB

A very efficient and massively parallelized software package for executing quantum Monte Carlo simulation of materials developed in Fortran. I developed it during my PhD thesis by adding new techniques for simulating solid materials. Unfortunately the code is still closed-source, which will hopefully change in the future. You can find some more information here and here.

OpenMPI

OpenMPI is an open-source library which implements the widely used Message Passage Interface (MPI) which standardizes the communications among tens of thousands of processors within the most powerful supercomputers in the world. I contributed to this project while working in the Atos Bull R&D department to make the library works efficiently with a high-speed network card built in-house.

surfbot

A simple trading bot developed in Python for “surfing” on the very unstable cryptocurrency market. The code will be released open source ASAP.

Publications

  • K. Nakano, C. Attaccalite, M. Barborini, L. Capriotti, M. Casula, E. Coccia, M. Dagrada, C. Genovese, Y. Luo, G. Mazzola, A. Zen, S. Sorella, TurboRVB: a many-body toolkit for ab initio electronic simulations by quantum Monte Carlo, arXiv:2002.07401 (2020)
  • D. dos Santos, M. Dagrada, E. Costante, Leveraging Operational Technology and the Internet of Things to Attack Smart Buildings, arXiv:1912.02480 (2019)
  • M. Sergent, M. Dagrada, P. Carribault, J. Jaeger, M. Pérache, G. Papauré, Efficient communication/computation overlap with MPI+OpenMP runtimes collaboration, European Conference on Parallel Processing, 560-572 (2018)
  • M. Dagrada, Improved quantum Monte Carlo simulations: from open to extended systems, PhD thesis, HAL Archives (2017)
  • M. Dagrada, S. Karakuzu, V. Vildosola, S. Sorella, M. Casula, Exact special twist method for quantum Monte Carlo simulations, Phys. Rev. B 94, 245108 (2016)
  • B. Busemeyer, M. Dagrada, S. Sorella, M. Casula, L. K. Wagner, Competing collinear magnetic structures in superconducting FeSe by first principles quantum Monte Carlo calculations, Phys. Rev. B 94, 035108 (2016)
  • S. Sorella, N. Devaux, M. Dagrada, G. Mazzola, M. Casula, Density Matrix Embedding scheme for optimal atomic basis set construction, J. Chem. Phys 143, 244112 (2015)
  • M. Dagrada, M. Casula, A. M. Saitta, S. Sorella, F. Mauri, Quantum Monte Carlo study of the protonated water dimer, J. Chem. Theory Comput., 2014, 10(5), pp. 1980-1993
  • F. Piacentini, G. Brida, L. Ciavarella, M. Dagrada et al., Entanglement-assisted calibration of a photon number resolving detector, Quantum Electronics and Laser Science conference, San Jose (2012).

Patents

  • M. Sergent, M. Dagrada, G. Papaure, Efficient communication overlap by runtimes collaboration US Patent App. 16/215, 633

Blog posts

  • ML time series analysis the right way, Towards Data Science, Medium: An end-to-end guide for forecasting the future with machine learning methods.

  • Representing Hierarchical Data in Python, Towards Data Science, Medium: A simple representation for hierarchical taxonomy data and the corresponding parser implemented in Python.

  • Deploy a Containerized Application on AWS with Terraform, FAUN, Medium: A step-by-step guide for deploying containerized service oriented applications on AWS. All combined with automatic infrastructure deployment using Terraform, the best tool out there for infrastructure-as-a-code

  • Private PyPi Server on AWS with Terraform, FAUN, Medium: Deploy a private repository for your Python packages in a few clicks on AWS using Terraform for infrastructure provisioning automation.