Utpal Kumar

Utpal Kumar, PhD

Assistant Project Scientist at UC Berkeley building scalable seismic and structural monitoring systems, from real-time data pipelines to HPC inversion workflows.

Research Data Analysis Web Computing GitHub

Data Analysis

Current Data-Analysis Workflows

  1. MyShake statewide structural health monitoring (California): Built scalable pipelines to process ambient smartphone accelerometer records, estimate building dynamic properties, and track temporal changes in modal behavior.
  2. QSIS cloud-based building monitoring: Developed real-time workflows for ingestion, automated processing, quality checks, and structural response analysis from in-building acceleration streams.
  3. Near-real-time geophysical data systems: Designed low-latency processing pipelines for mixed seismic and citizen-science streams, with automated feature extraction and event handling.
  4. Large-scale inversion and tomography workflows: Implemented and optimized high-performance box-tomography and full-waveform inversion pipelines across HPC systems.
  5. Reproducible research software: Built testing, CI/CD, and container-friendly workflows for maintainable scientific pipelines and long-running data services.
  • Languages and scientific stack: Python, C/C++, Fortran, MATLAB, NumPy, SciPy, Pandas
  • Real-time and backend: FastAPI, gRPC, WebSockets, Kafka, RabbitMQ
  • Data and storage: miniSEED, SAC, StationXML, HDF5/Zarr, netCDF, PostgreSQL, MongoDB, InfluxDB, Redis, SQLite
  • HPC and cloud: MPI, OpenMP, SLURM, Docker, Kubernetes, AWS, GCP

Tutorials and Guides on EarthInversion

  1. How to start using Pandas immediately for Earth data analysis
  2. Analyzing huge data files with Pandas
  3. Using Dask to read huge global earthquake catalogs
  4. Parallel computing in Python
  5. MPI4Py for parallel computing on supercomputers

Additional Projects and Legacy Tutorials

  1. Amazon AWS S3 Management Console: Web application for managing datasets in AWS S3 buckets (Python + Flask).
  2. Download Earthquake Catalogs from Global CMT website: Python script to fetch Global CMT event catalogs for user-defined time windows.
  3. Spectral Analysis of wide variety of data in MATLAB: Fourier transform, power spectrum, and spectrogram examples.
  4. Linux Tutorials (For beginners): Linux navigation, file operations, shell usage, and environment basics for research workflows.
  5. Linux Tutorial (Data Processing): Practical shell loops and text processing with awk and grep.
  6. Complex Moving Waves in MATLAB: moving waves, Fourier transform, and Hilbert transform demonstrations.
  7. Introduction to PERL: fundamentals for text and array processing in scripting workflows.

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