# Portfolio
The site homepage is now [index.html](https://kugelblitz25.github.io/), and the blog archive lives at [blogs/index.html](https://kugelblitz25.github.io/blogs/index.html).
## Hi 👋, I'm Vighnesh Nayak
A passionate Mechanical Engineering student exploring the intersection of ML, Robotics, and IoT
## 👨🎓 Education
- B.Tech in Mechanical Engineering, Indian Institute of Technology Bombay (2021-2025)
- Minor: Artificial Intelligence and Data Science
## 🏆 Achievements
- Among top 2.3 percentile in IIT JEE-Advanced
- Ranked 123 in K-CET (2021)
- Second place in Astromania-2022 quiz by Krittika - Astronomy club
- Mentored students in Computer Vision at IIT Bombay
## 💼 Professional Interests
AI | Machine Learning | Robotics
# 🚀 Featured Projects
### Sign Language Video to Audio Conversion
- 🎥 Developed a system to convert sign language videos into audio outputs without relying on text.
- 🔍 Implementation Details:
- Utilized a modified I3D model for feature extraction from video data.
- Processed the WLASL-2000 dataset to generate spectrograms using Tacotron 2 and Hifi GAN models.
- Used Non-Maximal Suppression for continuous sign identification.
- 📊 **Results**:
- Achieved effective translation of sign language into corresponding audio descriptions.
- Enhanced model accuracy through extensive data preprocessing and augmentation.
- 🛠️ **Tech Stack**: Python, Pytorch, PytorchVideo, Librosa, Numpy
- 🔗 [Project Repository](https://github.com/Kugelblitz25/sign2speech)
### Musical Instruments Separation Using Deep Neural Networks
- 🎵 Implemented audio source separation using deep learning techniques
- 🔍 Implementation Details:
- Utilized MUSDB-18 dataset with 44100Hz to 8192Hz downsampling
- Performed Short Term Fourier Transform (STFT) for spectrogram generation
- Implemented U-Net architecture for semantic segmentation
- Achieved high-quality separation of instruments and vocals
- 🛠️ **Tech Stack**: Python, TensorFlow, Numpy, Librosa
- 📈 **Results**: Successfully separated multiple instrument tracks with minimal artifacts
- 🔗 [Project Repository](#)
### Local Moodle: Automated Moodle Scraper
- 📥 Developed a Python script to automate the downloading of files and posts from Moodle courses.
- 🔍 Implementation Details:
- Utilizes **Selenium** and **WebDriver** for browser automation.
- Scrapes course information from the Moodle homepage, creating organized folders for each course.
- Downloads course materials (e.g., PDFs) that haven't been previously downloaded.
- Extracts and saves forum posts along with any attachments.
- 📊 **Results**:
- Streamlined the process of accessing and organizing course materials.
- Enhanced user experience by automating repetitive tasks associated with Moodle.
- Tailored specifically for use with the Moodle version at the Indian Institute of Technology Bombay (IITB).
- 🛠️ **Tech Stack**: Python, Selenium, BeautifulSoup
- 🔗 [Project Repository](https://github.com/Kugelblitz25/LocalMoodle)
### Joint Dictionary Learning for Color Image Demosaicing
- 📸 Developed an advanced image processing algorithm without prior training data
- 🔍 Implementation Details:
- Used Gradient Corrected Bilinear Interpolation (GCBI) for initial estimates
- Developed patch-based processing pipeline
- Implemented joint sparse demosaicing dictionary learning
- 📊 **Results**: Achieved 6.67% mean log PSNR improvement over GCBI
- 🛠️ **Tech Stack**: Python, OpenCV, Numpy
- 🔗 [Project Repository](https://github.com/Kugelblitz25/DictionaryLearningForDemosaicking)
### Cargo Bots: Swarm Robotics System
- 🤖 Built a warehouse simulation model using coordinated micro-controller bots
- 🔍 Implementation Details:
- ArUco marker-based localization using overhead camera
- A* algorithm for priority-based path planning
- Collision-free trajectory generation
- PID feedback control implementation on ESP32
- 📈 **Results**: Successfully demonstrated autonomous cargo transport with multiple bots
- 🛠️ **Tech Stack**: Python, OpenCV, ESP32
- 🔗 [Project Repository](https://github.com/Kugelblitz25/Swarm-Robotics)
### IoT Monitoring System (Zwilling Labs Internship)
- 📊 Developed enterprise-grade IoT monitoring solution
- 🎯 Key Features:
- Real-time event triggering system
- Optimized schema design for time-series data
- SQLite-based event tracking
- Interactive data visualization
- 🛠️ **Tech Stack**: Python, PostgreSQL, TimescaleDB, Svelte, SQLite
- 📈 **Impact**: Improved data retrieval performance by 40%
### Topology Optimization for Robotic Gripper
- 🦾 Developed optimization framework for robotic gripper design
- 🔍 Implementation Details:
- FEniCS-based topology optimization
- SIMP algorithm for material distribution
- 3D visualization using PyVista
- Stress and strain analysis
- 📊 **Results**:
- 50% reduction in material usage
- Maintained structural integrity
- Optimized force distribution
- 🛠️ **Tech Stack**: Python, FEniCS, PyVista
- 🔗 [Project Repository](https://github.com/Kugelblitz25/Topology-Optimization)
## 🛠 Skills
### Languages
Python | C++ | JavaScript | SQL
### Libraries
Numpy | Pandas | Scikit-Learn | Keras | TensorFlow | OpenCV
### Tools
Git | LaTeX
### Operating Systems
Windows | Linux
## 📊 GitHub Stats
## 🤝 Let's Connect!
[](https://linkedin.com/in/vighnesh-nayak-88058a234)
[](mailto:kugelblitz253@gmail.com)
[](https://kugelblitz25.github.io/)
[](https://kugelblitz25.github.io/blogs/index.html)