Hi! I'm Aditya Rao
Machine Learning Engineer
My interests include Machine Learning, Deep Learning, Data Science, and Software Development!
A few of my creative endeavors.
Curious to see my work?
Watch the video
Self-Driving Car
Embark on a visionary journey with our pioneering Self-Driving Car model. Intricately crafted through the application of Deep Q-Learning, it seamlessly incorporates sensor and orientation inputs. This cutting-edge project is fueled by PyTorch for neural networks and Kivy for interactive visuals, presenting a harmonious fusion of state-of-the-art AI technologies that shape the future of autonomous vehicles.
Go to →
Credit-Card-Default
Engineered payment default prediction models utilizing logistic regression, SVM, and XGBoost. Executed comprehensive data preprocessing and feature engineering in Python for enhanced accuracy, offering valuable insights for risk assessment and financial decision-making.
Go to →
Anime-Face-Generator
Created lifelike anime faces with exceptional detail using a PyTorch-based DCGAN. Deployed in a Streamlit web app for interactive anime face generation, including loss curve visualizations for model performance insights.
Go to →
Visual Odometry
Visual Odometry is the process of determining the position and orientation of a robot by analyzing the images captured by its camera(s). This project uses ORB (Oriented FAST and Rotated BRIEF) to detect and compute keypoints and descriptors, and the FLANN (Fast Library for Approximate Nearest Neighbors) based matcher to find matches between them.
Go to →
Language-Translation
This project focuses on building a transformer-based model for translating text between languages. The primary datasets used are Italian to English and Hindi to English translations, sourced from Kaggle. The project includes data preprocessing, model training, and evaluation, all implemented in a Google Colab notebook using PyTorch.
Go to →
NeRF
Implemented and trained Neural Radiance Fields (NeRF) models for high-quality, real-time 3D scene reconstruction from 2D images, leveraging deep neural networks to map spatial coordinates and viewing angles to color and density, signifi cantly improving visual quality and performance
Go to →
Structure-from-Motion
Engineered a Structure from Motion (SFM) algorithm using Python, NumPy, OpenCV, and Matplotlib to accurately reconstruct 3D scenes from 2D images, achieving critical advancements in feature detection and camera pose estimation.
Go to →
Geometry-Processing
Implemented advanced 3D mesh processing techniques, including Loop Subdivision for mesh upscaling and Quadric Error Metrics for mesh simplification, utilizing adjacency data structures like half-edge matrices for efficient mesh traversal and computation, enhancing model detail and optimization in a computational geometry project from scratch.
Go to →
Want to know more?
A bit about me.
My . . .
01
Education
I aim to showcase my passion and expertise in Electrical and Computer Engineering, with a strong focus on machine learning and deep learning. With a Master's degree from the University of Southern California and a Bachelor's degree from Veermata Jijabai Technological Institute, I have honed my skills in areas such as human activity recognition using LSTM models, autonomous self-driving car development and stock price prediction through NLP and time series forecasting.
02
Goals
My hands-on experience implementing cutting-edge technologies and leading collaborative projects underscores my commitment to innovation. I am eager to connect with fellow professionals, engage in meaningful discussions, and explore opportunities to leverage my technical skills and contribute to the ever-evolving landscape of engineering and artificial intelligence.
03
Skills
Communication is key and it's a paramount value of mine. I believe in transparency and constructive communication above all else. This helps me develop deep relationships and ensures my effectiveness and productivity in any work space with any team. I am proficient in a diverse set of programming languages including Python, C++, HTML, CSS, and JavaScript. My technical skills encompass Machine Learning, AWS, Deep Learning, Data Structures and Algorithms, Statistics, Azure, and Linux. I am adept at utilizing frameworks such as Tensorflow, Pytorch, Numpy, Pandas, Seaborn, OpenCV, MongoDB, SQL, Flask, and Python scripting, with troubleshooting expertise. I am familiar with various tools like Visual Studio Code, Pycharm, Google Colab, Jupyter Notebooks, Tableau, Kafka, Docker, Power BI, Excel, and Microsoft Office.
Scroll to see more →