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

Computational Seismologist | Structural Health Monitoring | Scientific Software and HPC

I am an Assistant Project Scientist at the Berkeley Seismological Laboratory, University of California, Berkeley. I build scalable computational workflows that connect geophysics with modern software architecture, with an emphasis on seismic, geodetic, and distributed sensing applications.

My current work focuses on smartphone-based ambient vibration analysis for structural health monitoring, real-time processing pipelines, and large-scale scientific computing for seismic imaging.

Experience

  • Assistant Project Scientist, Berkeley Seismological Laboratory, University of California, Berkeley (2025-Present)
  • Postdoctoral Researcher, Department of Earth and Planetary Science, University of California, Berkeley (2021-2025), with Prof. Richard M. Allen
  • Postdoctoral Researcher, Department of Earth and Planetary Science, University of California, Berkeley (2021-2023), with Prof. Barbara Romanowicz
  • Postdoctoral Researcher, Institute of Earth Sciences, Academia Sinica, Taiwan (2020-2021), with Prof. Bor-Shouh Huang

Education

  • Ph.D., Computational Geophysics (2014-2020), National Central University and Academia Sinica (TIGP Fellowship)
  • Integrated B.S.-M.S., Earth Sciences (2009-2014), IISER Kolkata, India (INSPIRE Fellowship)

Computing and Technical Skills

Area Tools and Expertise
HPC and Cloud Computing MPI, OpenMP, SLURM; Berkeley SAVIO, NERSC (Cori/Perlmutter), Anvil, TACC; Docker, Kubernetes, AWS, GCP
Scientific Programming Python (NumPy, SciPy, Pandas), C/C++, Fortran, MATLAB; CMake, Make; optimization of scientific workflows
Geophysical Data Systems miniSEED, StationXML, SAC; HDF5/Zarr, netCDF; ObsPy, SPECFEM, GMT/PyGMT
Databases and Storage PostgreSQL, MongoDB, InfluxDB (time series), Redis, SQLite; management of large geophysical archives
Real-Time Architectures Kafka, RabbitMQ, WebSockets; gRPC and FastAPI services; low-latency alerting and processing pipelines
DevOps and Reproducibility Git, GitHub Actions, pytest (unit/integration/end-to-end), semantic versioning, Sphinx/ReadTheDocs
Machine Learning PyTorch, TensorFlow; ML-based feature extraction, signal processing, and inference pipelines for geophysical data

Technical Skills & Proficiency

Representative proficiency across research software, scalable computing, and production-grade geophysical data systems.

Python (NumPy, SciPy, Pandas, automation)

HPC and Parallel Computing (SLURM, MPI, OpenMP)

Seismology Toolchain (ObsPy, SPECFEM, GMT/PyGMT)

Scientific Data Formats (miniSEED, StationXML, HDF5/Zarr, netCDF)

CI/CD and Testing (GitHub Actions, pytest, docs workflows)

Databases (PostgreSQL, MongoDB, InfluxDB, SQLite)

Cloud and Containers (Docker, Kubernetes, AWS, GCP)

Real-Time Data Systems (Kafka, RabbitMQ, Redis, WebSockets)

API and Service Development (FastAPI, gRPC)

Machine Learning for Geophysical Signals (PyTorch, TensorFlow)

C/C++ and Fortran

MATLAB

Current Research

  • MyShake statewide structural health monitoring in California: extracting and tracking building dynamic properties from ambient smartphone accelerometer recordings.
  • Automated building seismic monitoring and event processing in Taiwan: continuous acquisition, deep-learning phase picking, and large-scale event analysis.
  • Yellowstone mid-mantle seismic imaging using full-waveform inversion and broadband synthetic waveform modeling.
  • Scalable real-time geophysical data systems for seismic and citizen-science data streams.

Ph.D. Thesis

  • Ph.D. Dissertation: Read

Publications

Selected Peer-Reviewed

  1. Kumar, U., Marcou, S., and Allen, R. M. (2025). Ambient vibration analysis of high-rise buildings using MyShake smartphone data. Journal of Building Engineering, 106, 112496. https://doi.org/10.1016/j.jobe.2025.112496
  2. Patel, S. C., Gunay, S., Marcou, S., Gou, Y., Kumar, U., and Allen, R. M. (2023). Toward structural health monitoring with the MyShake smartphone network. Sensors, 23(21), 8668. https://doi.org/10.3390/s23218668
  3. Kumar, U., Legendre, C. P., Zhao, L., and Chao, B. F. (2022). Dynamic Time Warping as an alternative to windowed cross correlation in seismological applications. Seismological Research Letters. https://doi.org/10.1785/0220210288
  4. Kumar, U., Legendre, C. P., Lee, J.-C., Zhao, L., and Chao, B. F. (2022). On analyzing GNSS displacement field variability of Taiwan: Hierarchical agglomerative clustering based on Dynamic Time Warping technique. Computers and Geosciences, 169, 105243. https://doi.org/10.1016/j.cageo.2022.105243
  5. Kumar, U., and Legendre, C. P. (2022). Crust-mantle decoupling beneath Afar revealed by Rayleigh-wave tomography. Scientific Reports, 12(1), 17036. https://doi.org/10.1038/s41598-022-20890-5
  6. Kumar, U., Legendre, C. P., and Huang, B. S. (2021). Crustal structure and upper mantle anisotropy of the Afar triple junction. Earth, Planets and Space, 73(1), 166. https://doi.org/10.1186/s40623-021-01495-0
  7. Kumar, U., and Legendre, C. P. (2021). STADIUM-Py: Python command-line interface for automated receiver functions and shear-wave splitting measurements. Zenodo. https://doi.org/10.5281/zenodo.4686103
  8. Kumar, U., Chao, B. F., and Chang, E. T.-Y. (2020). What causes the common-mode error in array GPS displacement fields: Case study for Taiwan in relation to atmospheric mass loading. Earth and Space Science. https://doi.org/10.1029/2020EA001159