- Phone: 8984959212
- Email: [email protected]
- GitHub: VijayRajIITP
- LinkedIn: Vijay Raj
- LeetCode: vijayraj215
- Developed and trained a machine learning model for predicting payment dates, achieving a stellar 95% accuracy.
- Utilized time-series analysis, incorporating features like historical payment patterns, customer behavior, and seasonality.
- Conducted data preprocessing and feature engineering on large datasets, reducing noise and enhancing model performance by 20%.
- Implemented various regression algorithms (e.g., Linear Regression, Random Forest Regression) and evaluated their performance.
- Developed a Snake and Apple game using Python and Pygame.
- Implemented game mechanics, multiplayer mode, challenges, and sound effects for an immersive gaming experience.
- Generated a multi-drone detection and tracking dataset, pioneering the Multi-Drone Detection and Tracking (MDT) dataset.
- Implemented YOLO v8 and Strong-SORT, achieving a precision of 0.964 and 0.719 on seen and unseen MDT datasets.
- Implemented a PCA-based face recognition system with Python and OpenCV, achieving an impressive accuracy of 93.5%.
- Employed BERT for feature extraction and Logistic Regression, SVM, and Random Forest for classification.
- Achieved 83% accuracy with SVM and an outstanding 90% accuracy with a specialized BERT model.
- M.Tech in Signal Processing and Communication Engineering | IIT TIRUPATI (CGPA-8.61)
- B.Tech in Electronics & Telecommunication Engineering | Kalinga University (CGPA-8.59)
- WACV 2023 Challenge: Developed a single-class obstacle detection model for dynamic obstacles in the USV domain, securing the 21st rank.
- Kaggle Competitions Contributor: Ranked 172 out of 1138 participants in the NLP with Disaster Tweets competition.
- Machine Learning | Computer Vision | Deep Learning | NLP
- OOPS | Image Processing | Data Science | SQL
- C/C++ | Pygame | TensorFlow/Keras
- Blogger at Medium: Sharing insights and knowledge on machine learning and deep neural networks.
- Chegg Subject Matter Expert (2020 - Present): Assisted over 100 students with clear and comprehensive answers to academic questions.