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Profile

Field — Computational Physics
Focus — Machine Learning Systems, GPU Performance, HPC Simulation, Fluid Dynamics
Experience — 9+ years
Hardware — GPU / CUDA, MPI clusters

I build numerical and machine-learning models, and I care most about how they perform in speed and fidelity on GPUs and HPC clusters: CUDA-accelerated kernels, MPI-based parallelization, and predictive methods such as Reservoir Computing, applied to complex dynamical systems. The systems have ranged from rotating turbulence and squeezed states of light to industrial sensor time-series. I judge a model on more than accuracy: whether its results reproduce, whether its evaluation holds up, what it costs to run, and whether its predictions can be explained.

Technical Skills

Performance

GPU & Performance Engineering

GPU acceleration with CUDA and CuPy, distributed systems (MPI, OpenMP), SLURM / LSF workload management.

ML

Machine Learning & Time-Series

Reservoir Computing (ESN), time-series forecasting, neural networks, predictive AI methods.

Data

Data Architecture & I/O

HDF5, NetCDF, binary data serialization, high-throughput data input/output.

Domain

Computational Physics

Complex dynamical systems, fluid dynamics, turbulence modeling.

Languages

Programming

Python, C++, Fortran, Shell scripting (Bash).

Tooling

Environment & Tools

Linux (RHEL / Debian), Git, JupyterLab.

Analysis

Data Visualization & Analytics

Statistical data analysis, multi-dimensional data rendering, Matplotlib, Seaborn.

Frontier

Advanced Paradigms

Quantum Machine Learning (QML), Variational Quantum Algorithms (VQA), Quantum Reservoir Computing (QRC).

Professional Experience

Feb 2026 — Present

Further Software & Research Projects

Web Homepage, Germany
  • Predictive maintenance: end-to-end development of a highly optimized reservoir computing (ESN) model that is fast and accurate for predicting maintenance requirements. Designed, coded, tested, packaged, and documented to production-code standards. Code
Jan 2023 — Jan 2026

Postdoctoral Researcher

Institute of Thermodynamics and Fluid Mechanics, TU Ilmenau, Germany
  • Led the execution of a full work package on Reservoir Computing (RC) within the ERC-funded Mesocomp project.
  • GPU-batched execution for computing Information Processing Capacity (IPC) of a reservoir computer using CuPy, nearly 20 times faster than the CPU version.
  • Collaborated on Quantum RC using photonic Gaussian Boson Sampling, and Physical RC via memristor-based on-chip architectures.
Jul 2012 — Dec 2022

PhD Researcher

Indian Institute of Technology Kanpur, India — spanning rotating turbulence, astrophysics, and quantum optics

Rotating Turbulence — PhD Thesis

Developed and optimized shell model frameworks; performed Direct Numerical Simulations (DNS).

Astrophysics — Theoretical Modelling

Established a theoretical framework for magnetohydrodynamic (MHD) instabilities in the intracluster medium (ICM). Co-author on a peer-reviewed publication.

Quantum Optics & Optomechanics — Theory & Simulation

Modeled squeezed states of light; simulated optical tweezers for micro-particle manipulation.

Training & Supervision

Delivered computational modeling and advanced technical course tutorials.

Selected Publications

Full list on ORCID.

Education

Ph.D. in Physics
Indian Institute of Technology Kanpur, India
Dissertation: Spatial and Temporal Statistics of Rotating Turbulence: A Dynamical System Approach
Dec 2022
M.Sc. in Physics
Indian Institute of Technology Kanpur, India
Jun 2012
B.Sc. Physics and Mathematics
MJP Rohilkhand University, Bareilly, India
Nov 2009

Languages

EnglishFLUENT
GermanA2–B1 · LEARNING