Recent graduate [1] broadly interested in optimization, machine learning, and scientific computing, mainly using Python, C++, and C. Most of my personal and professional work is in Python, although lately I find myself using C++, namely C++17, more and more.
For fun, here's a toy norm-constrained convex optimization problem and a plot of its solution against the objective's minimum. The Python script used to solve the problem and generate the plot can be found in my profile repository.
- numpy-lapacke-demo
- Python C extension implementations of linear regression using QR/SVD and Newton's method with diagonal Hessian modification using the Python C API and NumPy C API to work with Python objects on the C level. Computations are done using CBLAS/LAPACKE routines operating directly on NumPy array memory. All public and private methods are rigorously unit tested using pytest.
| [1] | NYU Stern May 2021, BS in finance and joint BA in math/computer science. |