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Working from School on a tight Schedule
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Working from School on a tight Schedule

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syipmong/README.md

Said Yipmong

Computational Science and Engineering | Cyber-Physical Systems
Research focus: Numerical linear algebra, deterministic real-time simulation, and high-performance edge computing.

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Research Interests & Academic Trajectory

My work bridges physical system dynamics with efficient discrete computation.

  • Numerical Analysis & Scientific Computing: Algorithmic stability of ordinary differential equation integrators, IEEE 754 floating-point roundoff mitigation, error-bounded state estimation, and sparse matrix factorization.
  • High-Performance Edge Execution: Cache-aware algorithm design, SIMD vectorization, and deterministic task scheduling on resource-constrained embedded targets.
  • Deterministic Telemetry & Cyber-Physical Systems: Real-time hardware-in-the-loop validation, sensor state fusion, and high-throughput serialization protocols.

Computational Toolchains & Environments

Category Technologies & Environments
Languages C (C99/C11), C++ (C++17/20), Python (NumPy, SciPy, SymPy), Rust, Go
Scientific & Numerical BLAS/LAPACK, Eigen, CMSIS-DSP, fixed-point arithmetic, discrete state-space modeling
Parallel & Edge Architecture OpenMP, POSIX Threads, ARM Cortex-M, ESP32-S3, FreeRTOS
Protocols & I/O SPI, I2C, UART, CAN Bus, Protocol Buffers
Tooling & Profiling CMake, GDB, Valgrind, OpenOCD, Git, Linux / POSIX CLI

Core Repositories & Reproducible Benchmarks

  • Numerical-Solvers-Edge
    Comparative study evaluating 4th-order Runge-Kutta against symplectic Euler methods for Hamiltonian dynamical systems. Includes quantitative drift curves, execution cycle comparisons, and floating-point error bounds under 32-bit constraints.

  • Embedded-Kalman-Filter
    C99 implementation of a discrete scalar Kalman filter engineered for zero dynamic memory allocation. Executes state updates in under 15 µs on ARM Cortex-M microcontrollers.

  • High-Performance-Matrix-Kernels
    Implementations of cache-blocked matrix multiplication, LU decomposition, and Gaussian elimination. Evaluates throughput across naive iterations, loop unrolling, and architecture-specific vector extensions.

  • Real-Time-Telemetry-Engine
    Deterministic sensor ingestion engine utilizing FreeRTOS ring-buffers. Designed for bounded latency, zero heap fragmentation, and real-time serial transmission.


System Telemetry

GitHub Overview Contribution Activity

Pinned Loading

  1. Embedded-Kalman-Filter Embedded-Kalman-Filter Public

    Python

  2. Numerical-Solvers-Edge Numerical-Solvers-Edge Public

    C

  3. High-Performance-Matrix-Kernels High-Performance-Matrix-Kernels Public

    C

  4. Real-Time-Telemetry-Engine Real-Time-Telemetry-Engine Public

    C

  5. navier-stokes-mg navier-stokes-mg Public

    C