Recent graduate1 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.
NYU Stern May 2021, BS in finance and joint BA in math/computer science.↩