CV

Current academic CV.

Contact Information

Name Aaditya L. Kachhadiya
Professional Title Independent Researcher
Email kachhadiyaaaditya@gmail.com

Professional Summary

High school student and independent researcher working at the intersection of machine learning, physics, and numerical optimization, with interests in scientific machine learning, and principled approaches for scientific discovery.

Experience

  • 2026 - present

    Surat, Gujarat, India

    Research Collaborator
    Sardar Vallabhbhai National Institute of Technology
    Working under the guidance of Dr. Tanmoy Hazra on optimization methods for physics-informed learning and scientific machine learning, in collaboration with researchers at SVNIT Surat.
    • First and corresponding author on a manuscript submitted to IEEE Transactions on Neural Networks and Learning Systems.
    • Co-authors include Meet Dabgar, Dr. Tanmoy Hazra, and Prof. Anupam Shukla.
    • Research focuses on optimization methods and diagnostics for physics-informed scientific learning objectives.
  • 2024 - present

    Surat, Gujarat, India

    Independent Researcher
    Self-employed
    Independent research in scientific machine learning, nonlinear inverse problems, numerical optimization, and learned solvers for PDE-governed systems.
    • Solo author of Deceptron Learned Local Inverses for Fast and Stable Physics Inversion, presented at the NeurIPS Machine Learning for Physical Sciences Workshop, 2025.
    • Solo Author of Local Inverse Geometry Can Be Amortized, arXiv:2605.13068.
    • Developed an open-source PyTorch implementation of Deceptron and D-IPG for nonlinear inverse problems.

Education

  • 2026 - 2027

    Surat, Gujarat, India

    Senior Secondary, Class 12
    Shardayatan School
    Science
    • Gujarat State Board, ongoing.
    • Expected completion in March 2027.
  • 2024 - 2025

    Surat, Gujarat, India

    Secondary, Class 10
    Shardayatan School
    Science
    • Gujarat State Board.

Publications

  • 2026
    Component-Access Subspace Optimization for Heterogeneous Scalarized Learning
    Manuscript under review, IEEE Transactions on Neural Networks and Learning Systems

    First-author manuscript on subspace optimization methods and diagnostics for physics-informed scientific learning objectives.

  • 2026
    Local Inverse Geometry Can Be Amortized
    arXiv preprint arXiv:2605.13068

    Introduces Deceptron Inverse-Preconditioned Gradient, a learned local-inverse optimization method for nonlinear inverse problems, together with a Jacobian Composition Penalty and its runtime inverse-consistency diagnostics.

  • 2025
    Deceptron Learned Local Inverses for Fast and Stable Physics Inversion
    NeurIPS Machine Learning for Physical Sciences Workshop

    Workshop paper presenting Deceptron, a learned local-inverse approach for fast and stable physics inversion.

Projects

  • Deceptron / D-IPG

    Open-source PyTorch implementation of Deceptron Inverse-Preconditioned Gradient for nonlinear inverse problems.

    • Implements learned forward-reverse modules, D-IPG inference, Jacobian-consistency training, runtime diagnostics, and PDE inverse-problem benchmarks.
    • Repository includes reproducibility scripts for scientific inverse-problem experiments.
    • Code available at github.com/AadityaKachhadiya/deceptron.
  • New York Academy of Sciences Junior Academy

    Participant in the New York Academy of Sciences Junior Academy 2025.

    • Selected & Participated in a global STEM innovation and research program for high school students. Developed a Hybrid Reinforcement Learning and Forecast-Based Solar Battery Scheduling approach on a real power plant dataset.

Skills

Programming (): Python, PyTorch, NumPy, pandas, Matplotlib, LaTeX
Scientific Machine Learning (): Nonlinear inverse problems, PDE-governed systems, physics-informed learning, surrogate modeling, learned solvers
Optimization (): Nonlinear least squares, Gauss-Newton, Levenberg-Marquardt, L-BFGS, BFGS, line search, trust-region methods, subspace methods
Mathematics (): Linear algebra, singular value decomposition, calculus, partial differential equations, automatic differentiation, dynamical systems

Languages

Gujarati : Native
English : Fluent
Hindi : Fluent

References

  • Dr. Tanmoy Hazra

    Assistant Professor and Head, Department of Artificial Intelligence, Sardar Vallabhbhai National Institute of Technology, Surat. Email: tanmoyhazra@aid.svnit.ac.in