Portfolio | Dhruv Tyagi

About Me

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Dhruv Tyagi

Developer Advocate | GSoC 2023 | X - Siemens, SixthSensAI | Siemens Scholar

I learn & build stuff related to Artificial Intelligence, Machine Learning, Data Science, Python Development, Generative AI🚀 and more. I love to share my learnings via blogs, posts, etc. and actively contribute to open-source. I am also engaged in Community Management & Developer Advocacy🥑.

Resume

Tech Stack

DataWeb DevelopmentOthers

Python

SQL

Scikit-Learn

NLP

Mediapipe

OpenPose

Keras

Data Analysis

Yolo

Pandas

Numpy

Data Modelling

Model Deployment

Streamlit

Tensorflow

Projects

Machine LearningBlogs and Studies

PaperChat

Tech Stack: LLMs, Vector DB, LangChain

Choosing the Best-Fit Organization for Your Google Summer of Code Adventure.

Tech Stack: Gsoc, Open Source, Software Development

How to deploy Streamlit applications using Docker & AWS?

Tech Stack: Data Science, Docker, AWS, Streamlit

Understanding Nature Inspired AI - NIA

Tech Stack: Explanation of Research Paper, Self Driving Cars, Artificial Intelligence, Robotics, Technology

Creating Energy Gems: Unveiling the Power of Nano Diamond Batteries

Tech Stack: Technical Writing, Clean Energy, Nuclear Energy, Emerging Technology, Science

GSoC 2023 Blog - Red Hen Lab

Tech Stack: Professional Writing, Machine Learning, Open Source, Deep Learning, GSoC 2023

Experience

Minus Zero

Developer Advocate | Jan 2024 - Present

Researching comprehensive World Models & Generalized AI for the development of NIA based autonomous vehicles, AVs.
Engaged in internal & external advocacy, redefining company mission statement and discussing research advancements.
Daily Activities: writing technical documents, summarizing & keeping up to date with latest research, supporting tech and non-tech team, setting up potential meetups.

Google Summer of Code (GSoC) 2023 - Red Hen Lab

Open Source Developer | May 2023 - September 2023

Extraction of Gesture Features: Contributed to the development of Singularity pipeline by utilizing Red Hen lab’s Distributed systems and HPC that detects & identifies hand gestures, categorizes gestures to various types, and extracts speech features within video content.
Gesture Pipeline: Utilized OpenPose and LCRN (LSTM + CNN) methodology to develop Gesture prediction pipeline having 78% accuracy.
Phrase Pipeline: Conducted Speaker Diarization, subtitle segmentation and extracted speech features to detect the speaker in the video.
Synchronization: Developed a data framework by late fusing both pipelines to analyze hand movements’ correlation with speech features.

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