Jeramy Abuga Arika
Toronto
Summary
Utilize advanced expertise in applied physics, computational modeling, and machine learning to develop and train AI systems that can precise physical simulation, scientific forecasting, and data-driven discovery.
Overview
5
5
years of professional experience
Work History
- Research & Development Projects
- Developed deep learning architectures to emulate solutions of complex physical PDEs.
- Built neural networks to model real-time fluid dynamics and turbulence.
- Employed reinforcement learning to control agents in physics simulation environments.
- Integrated physical constraints and conservation laws into machine learning frameworks.
- Academic & Mentoring Tasks
- Guided undergraduate students in computational physics and scientific programming.
- Organized seminars on numerical modeling, simulation methods, and AI applications in physical sciences.
Assistant Lecturer
Yoke University College
01.2021 - Current
- Assisted in developing and delivering course materials for undergraduate programs.
- Facilitated engaging discussions to enhance student understanding of core concepts.
- Collaborated with faculty to refine curriculum based on student feedback and learning outcomes.
- Supported research initiatives by managing data collection and analysis processes.
Education
Master of Science - Applied Physics
University of Nairobi
06.2019
Skills
- Theoretical & Applied Physics
- Classical Mechanics (Lagrangian & Hamiltonian formalism)
- Electromagnetism (Maxwell's Equations, field theory)
- Quantum Mechanics (Schrödinger equation, operators, quantum states)
- Statistical Mechanics (ensemble theory, thermodynamics, partition functions)
- Relativity (special & general relativity, spacetime metrics, Lorentz transformations)
- Computational & AI Skills
- Physics-informed neural networks (PINNs)
- Numerical solutions to ODEs/PDEs (finite element, finite difference, Monte Carlo methods)
- High-performance computing (GPU acceleration, CUDA, MPI)
- Scientific programming and simulation (Python, MATLAB, Mathematica, TensorFlow, PyTorch)
- Mathematical Foundations
- Vector calculus, tensor analysis, and linear algebra
- Fourier and Laplace transforms
- Stochastic processes, probability theory
- Group theory and symmetry in physics applications
- Programming Languages: Python, MATLAB, C/C, Mathematica
- AI Libraries: PyTorch, TensorFlow, JAX
- Simulation Software: COMSOL Multiphysics, Simulink
- HPC Software: CUDA, MPI, OpenMP
- Others: Git, Linux, LaTeX for technical writing
Awards
Presented research on integrating physics laws into deep learning models for scientific forecasting., Wrote technical reports on computational modeling of nonlinear dynamical systems., Created specialized numerical solvers for coupled differential equations in physics investigations.
Languages
English
Full Professional
Timeline
Assistant Lecturer
Yoke University College
01.2021 - Current
Master of Science - Applied Physics
University of Nairobi
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