Suryoday Basak - Graduate Assistant

Suryoday Basak

Graduate Assistant

State College, Pennsylvania, United States

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Summary

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Senior

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Top School

Suryoday Basak is a PhD candidate and graduate assistant at Penn State with 11 years of experience applying machine learning to wireless sensing, embedded systems, and cross-domain science problems. He has built and validated deep learning pipelines on SOCs and AI accelerators during internships at Meta, and prototypes for AI smart glasses and neural interfaces that bridge HCI and hardware. His research focuses on mmWave radar motion and vibration sensing, speech processing, and security of cyber-physical systems, complemented by teaching Python and wireless sensing courses. An active contributor to numerical optimization tooling, he implemented Particle Swarm Optimization in the mlpack/ensmallen C++ library, demonstrating practical optimization on classic test functions. Comfortable across Python, C/C++, and embedded platforms like Raspberry Pi and ESP32, he brings both academic rigor and production-minded engineering to interdisciplinary teams.

11 years of coding experience

2 years of employment as a software developer

Bachelor's degree, Computer Science, First Class, Bachelor's degree, Computer Science, First Class at PES University

Master of Science - MS, Computer Science, 4.0, Master of Science - MS, Computer Science, 4.0 at The University of Texas at Arlington

Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Penn State University

Github Skills (10)

algorithm10

machine-learning10

machine-learning-algorithms10

c-language10

cprogramming-language10

optimisation10

optimizers10

optimization10

deeplearning-ai9

deep-learning9

Programming languages (2)

C++Python

Github contributions (5)

mlpack/ensmallen

Feb 2019 - Jul 2019

A header-only C++ library for numerical optimization --

Role in this project:

ML Engineer

Contributions:96 commits, 4 PRs, 71 comments in 5 months

Contributions summary:Suryoday contributed significantly to the `ensmallen` repository by implementing the Particle Swarm Optimization (PSO) algorithm. Their work involved adding a new class (`PSOType`), along with related update policies and initialization policies. They also included tests for the implemented PSO, demonstrating its usage with various test functions like the Rosenbrock, Ackley, and Beale functions.

optimization-methodsoptimization-algorithmsnumerical-optimizationheader-onlycplusplus

AstrIRG/AstrIRG.github.io

Oct 2017 - Dec 2020

Contributions:101 pushes, 1 branch in 3 years 2 months

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