Sidharth Srinath
Hey, I'm Sid
I’m a software engineer based in San Diego interested in applied machine learning, platform engineering, and AI-optimized hardware. I'm currently working at Intel.
Background / About Me
My name is Sidharth Srinath - I'm UC San Diego computer science graduate and currently a Graphics Content Validation Engineer at Intel. I have previously worked at Sony Electronics, the Salk Institute for Biological Studies (at the Talmo Lab), MedSmart and Werfen as a software engineering intern and at UCSD's CSE department as an instructional assistant ( CSE 8A, CSE 12). Relevant coursework include Software Engineering Principles, Operating Systems, Digital Systems/Design, Data Science, Probability & Statistics, Intro. Machine Learning, Deep Learning:Neural Networks, Statistical Natural Language Processing and more.
Aside from programming, I enjoy playing and recording the guitar using FL Studio and Garageband.
Selected Experiences

Graphics Content Validation Engineer

July 2024 - Present

Intel

Writing AI and graphics compute workloads for a new generation of computer hardware.

Data Science Intern

Winter 2024

Sony Electronics

Tackling Computer Vision and Machine Learning challenges a part of the Sony Semiconductors Solutions (SSS) team.

Student Researcher

Fall 2023

Salk Institute of Biological Studies

Working on large-scale machine learning pipelines and state-of-the-art computer vision models for efficient pose estimation through SLEAP under Dr. Talmo Pereira.

Software Engineering Intern

Summer 2022

Werfen North America

Designed comprehensive integration/unit testing, remote procedure call libraries, and robust GUI(s) for blood coagulation medical devices.

Software Engineering Intern

Fall 2021

MEDSmart Inc.

Built data pipelines using boto3 and GraphQL to query historical sales data from AWS (DynamoDB) and perform continuous inferences to predict future medication quantities using LSTM and Autoregression predictive models.

*Further experiences and more details on resume @ (top & bottom of site).
Projects
Spotify Music Clustering
Python
Takes input of a Spotify playlist id and splits the playlist's songs into low and high-energy clusters using K-means clustering techniques. Uses OAuth for authorization workflow.
See Code
Snake Game AI Bot
Python
Utilizes the NEAT-Python framework and reinforcement learning techniques propelled by genetically evolving neural networks to develop a model that teratively learns to defeat snake game.
See Code
Social Compass App
Java, XML, CSS
Developed an Android app that displays friends’ locations in comparison to yours in real time. Process planned and documented in github projects and structured with agile principles
See Code
Image Label Generator
Python
Worked with a team to developed an encoder(convolutional)-decoder(LSTM) structured neural network that generates intelligent tags for image inputs.
Private Repo
Intelligent EQ VST
C++
Currently in progress. Using JUCE C++ framework to read in audio data from a DAW host and use DSP principles to manipulate sound signals in order to achieve intelligent equalization effects.
Not Posted Yet
Medicine Forecast System
Python
Used various regression techniques to predict future medicine demand from historical data allowing pharmacies to cut costs of unused medicine as well as avoid the abuse of excess medication.
Proprietary IP