Alessandro Fumarola

Data Scientist at Electra Vehicles, Inc.
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Contact Information
us****@****om
(386) 825-5501
Location
Rome, Latium, Italy, IT
Languages
  • English -
  • Italian Native or bilingual proficiency
  • French Limited working proficiency
  • German Limited working proficiency
Skills

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I recruited Alessandro to work with me at Electra Vehicles in the R&D team, and I have to say he far exceeded my expectations. Not only is he a great physicist that can apply his knowledge (and expand it quickly) but also a great software engineer. He contributed greatly to so many projects and products and in addition made some outstanding recommendations to the approach for an innovative grant application Electra was working on with the University of Bath and the University of Strathclyde that really made it possible to identify dendrite growth in the lab using U. Strathclydes magnetic field sensors. Alessandro is a pleasure to work with, very kind to others, always willing to explain things on their terms, and of course, gets a lot of code written that is super useful in products and to assist others in their work. He also has great leadership skills and I was planning to promote him to a Tech Team Lead very soon. I would love to work with Alessandro again and hope to soon.

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Credentials

  • Confluence Fundamentals Badge
    Atlassian
    Feb, 2023
    - Nov, 2024
  • Jira Fundamentals Badge
    Atlassian
    Feb, 2023
    - Nov, 2024

Experience

  • Electra Vehicles, Inc.
    • United States
    • Software Development
    • 1 - 100 Employee
    • Data Scientist
      • Feb 2023 - Present

      Electra's team of Artificial Intelligence (AI) and electric vehicle experts are developing innovative software technology to solve today's biggest electrification problems. With the latest in Machine Learning (ML) and access to over 300 cell models for simulation, Electra's battery pack software optimizes range, performance, lifetime, and safety across various applications and industries using an Adaptive Battery Digital Twin. My job as a R&D Data Scientist is to create accurate predictive algorithms of battery systems, including electric vehicles, by using cutting-edge Data Science and physics-based modeling techniques. Show less

  • Material Mind
    • United States
    • Research
    • Data Scientist
      • Jan 2020 - Present

      Material Mind (MM) has built a Materials Discovery Engine using artificial intelligence and machine learning combined with fundamental physics modelling by leveraging certain properties that can be predicted from correlations of patterns in the electronic, phononic, magnonic, and crystal structures of a material. My job as a Data Scientist was to build the data infrastructure and processing pipeline from the ground-up, enabling to scale the physics concepts underlying our Discovery Engine to more than 100 000 known materials. I used data science techniques to collect, sanitize and pre-process huge amounts of information from heterogeneous sources such as public databases, academic papers and data provided by our partners. I also contributed by implementing physics concepts in computer code, producing new predictions of exotic properties in already known materials. I also provided the Machine Learning team with high-quality data sets which they could use to train their Property Prediction model. Show less

  • Mythic
    • United States
    • Semiconductor Manufacturing
    • 1 - 100 Employee
    • Analog Compute Modeling Engineer
      • Jul 2021 - Nov 2022

      Working on next-generation Mixed-Signal Accelerators for Machine Learning workloads. By leveraging analog in-memory computation coupled with low-power digital circuits, Mythic Analog Matrix Processors (AMPs) offer huge improvement in terms of power, performance and cost with respect to current all-digital solutions. At the heart of Mythic AMPs lie millions of Non-Volatile Memory Cells that can simultaneously and independently store and compute information, enabling highly parallel operation. As an Analog Compute Modeling Engineer, my job is to run experiments on prototype and production AMPs to infer desirable properties of the Non-Volatile Memory Cells as well as ideal circuit configurations. The impact is twofold: my colleagues and I can immediately improve latency and precision by fine-tuning the existing analog circuitry and we can guide future design to further increase performance. Show less

  • Max Planck Institute of Microstructure Physics
    • Germany
    • Research Services
    • 1 - 100 Employee
    • Guest Scientist
      • Feb 2021 - Jun 2022

      Advising research project involving Phase-Change Materials and Non-Volatile Memory devices. Performing simulation of large circuits leveraging Analog Computation. Mentoring PhD students in choosing research topics and managing their daily work.

    • PHD Student
      • Nov 2016 - Jan 2021

      Research activity carried out in the context of the H2020 Phase Change Switch Project.PHASE‐CHANGE SWITCH aims to exploit the abrupt Metal‐Insulator‐Transition (MIT) that happens in certain materials (as for Vanadium dioxide, VO2) at temperatures that make them interesting for electronic circuits and systems by their performance, energy efficiency and scalability. The project goals combines energy efficiency and extended functionality with the engineering of new classes of solid‐state Beyond CMOS switches and memory devices.During my PhD, I designed, fabricated and characterized new memory device architectures based on the Metal-Insulator Transition of Vanadium Dioxide (VO2): - A three-terminal Non-Volatile Memory transistor exploiting the change in electrical resistance caused by migration of oxygen ions from within the VO2 film. A gate electrode with an Ionic Liquid was used to control the insertion and migration of Oxygen Ions. The resistance change was detected by a Source and Drain electrodes; - A two-terminal volatile memory switch. This device was combined with other off-the-shelf electronic components to enable complex functions such as oscillators and threshold switches;The project gathers six organisations from four different countries. Together they form a unique and balanced network including two universities (EPFL and UCAM), one research center (MPI Halle), two large industries (IBM and TRT) and one research-intensive SME (AMO)The work is supervised by Prof. Dr. Stuart Parkin (https://www.phasechange-switch.org/) Show less

  • EPFL (École polytechnique fédérale de Lausanne)
    • Switzerland
    • Higher Education
    • 700 & Above Employee
    • Visiting PHD Student
      • Aug 2017 - Feb 2018

      Characterization and simulation of micrometre-scale, reconfigurable Radio-Frequency devices based on Vanadium Dioxide. Work carried out within the H2020 Phase-Change Switch Project (https://www.phasechange-switch.org/) Supervisor: Prof. Adrian Ionescu Characterization and simulation of micrometre-scale, reconfigurable Radio-Frequency devices based on Vanadium Dioxide. Work carried out within the H2020 Phase-Change Switch Project (https://www.phasechange-switch.org/) Supervisor: Prof. Adrian Ionescu

  • IBM
    • United States
    • IT Services and IT Consulting
    • 700 & Above Employee
    • Research Intern
      • Feb 2016 - Aug 2016

      Master Thesis in 'Cognitive Computing with Non-Volatile Memory devices" Simulation of large-scale hardware accelerators for neural networks with non-volatile memories (NVMs) used as synaptic devices: evaluation of NVMs properties and cir- cuits trade-offs. Master Thesis in 'Cognitive Computing with Non-Volatile Memory devices" Simulation of large-scale hardware accelerators for neural networks with non-volatile memories (NVMs) used as synaptic devices: evaluation of NVMs properties and cir- cuits trade-offs.

  • NanoLAB - EPFL (École polytechnique fédérale de Lausanne)
    • Lausanne Area, Switzerland
    • Summer Research Intern
      • Jun 2015 - Aug 2015

      "Impact of high-k oxides on VB-FET devices" "Impact of high-k oxides on VB-FET devices"

Education

  • The Martin Luther University of Halle-Wittenberg
    Doctor of Philosophy - PhD, Engineering Physics/Applied Physics
    2016 -
  • Ecole polytechnique fédérale de Lausanne
    Master of Science (M.Sc.), Nanotechnology for the Integrated Systems
    2015 - 2016
  • Grenoble INP - Phelma
    Master of Science (M.Sc.), Nanotechnology for the Integrated Systems
    2014 - 2016
  • Politecnico di Torino
    Master of Science (M.Sc.), Nanotechnology for the Integrated Systems
    2014 - 2016
  • Politecnico di Torino
    Bachelor of Engineering (B.Eng.), Electrical and Power Engineering
    2011 - 2014

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