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Ali Mousavi, Ph.D.

ME/ML Engineer

Energy Scientist · AI/ML Engineer

Ali Mousavi, Ph.D.

Process and ML Engineer — strong energy systems, electrochemistry (Battery, Corrosion, Surface science) along with production-grade machine learning product shipment.

Open to opportunities

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At a glance

Highlights

10+
Publications Practical & Applied engineering peer-reviewed proven works
Ph.D. Energy systems
Industrial level hands-on scientist, advanced in material characterization and electrochemistry
Na–S + Li-ion
Excellent in end-to-end workflow: design, build, and modeling of energy systems, batteries, pouch & flow cell
27+
Production ML pipelines and Agentic AI for industrial application
Background

Industry & Research Experience

    • Owned 27+ production ML pipelines for ERCOT and broader power-market analytics, with forecasting work spanning wind, solar, and grid load in an energy-systems context.
    • Delivered +35% profit and +13% KPI improvement vs. baseline through model redesign and feature engineering tied to market and dispatch constraints.
    • Built CI/CD and MLOps tooling on GCP (Airflow, Docker) with monitoring and automated retraining.
    • Partnered with traders and operations staff to translate physical grid and asset behavior into durable model features.
    PythonPyTorchTransformerAirflowGCPDockerSQLSparkCI/CDMLOpsbash
    Showcases

    ERCOT grid node decision dashboard (demo)

    Problem
    Power-market and trading decisions were spread across multiple tools, making it slow to assess unit status and local price behavior at the node level.
    Approach
    Built an interactive Python dashboard (Pandas + Plotly/Bokeh + widgets) that combines unit status frequency, output behavior, and nodal price context for fast operator review.
    Result
    Reduced decision-cycle friction by surfacing critical node-level signals in one view; used as a practical decision-support showcase.

    Snapshot from the interactive dashboard demo notebook/video.

    Watch 2-min demo
Toolkit

Technical skills

Data & ML

  • Python
  • SQL
  • Spark
  • PyTorch
  • Pandas
  • scipy
  • statsmodels
  • MATLAB
  • Minitab
  • Airflow
  • Docker
  • Git
  • GCP
  • AWS
  • CI/CD
  • MLOps

Engineering Software

  • COMSOL Multiphysics
  • LabVIEW (NI-certified)
  • CAD
  • FEA

Electrochemistry

  • EIS
  • Cyclic Voltammetry
  • ORR
  • RDE
  • Tafel / PDP / LP
  • Coin / Pouch / Flow cell build & test

Material Characterization

  • SEM / EDX
  • XRD
  • XPS
  • GC (TCD/FID)
  • ICP-MS
  • Profilometry
  • Goniometer
  • PVD
  • Glove box

Statistical Methods

  • DOE: Factorial, Taguchi, CCD, RSM
  • ANOVA / t-test
  • Techno-economic modeling
Background

Education

  • Ph.D., Mechanical Engineering
    Virginia Tech
    GPA 3.90 · 2021
  • Data Science Fellowship (top 2%)
    The Data Incubator
    2020
  • M.S., Mechanical Engineering
    University of Hawai'i at Mānoa
    GPA 3.96 · 2015
  • B.S., Mechanical Engineering
    Sharif University of Technology
    GPA 3.56 · 2012
  • Summer School — Energy Storage
    Chiemsee (CEA / TUM)
    2016
Research

Selected publications

Full list available on Google Scholar.