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Engineer by training, creator by passion. I'm a Graduate Student at ASU blending |
Name: Brijesh Kumar
Role: Graduate Student @ Arizona State University
Passion: AI/ML, Data Mining, Computer Vision, Software Engineering
Strengths:
- ๐ Data-driven Development
- ๐ง Deep Learning, NLP, Recommender Systems
- ๐ ๏ธ Microservices, REST APIs, Scalable Backend
- ๐งฎ Big Data, Distributed Computing
CodingPower:
- ๐ป Solved 600+ LeetCode Problems
- ๐
Top 150 out of 20,000+ on CodeChef
- ๐ข TA for Statistics & Probability๐ป Languages: Python | Java | C++ | R | SQL
๐ฆ Tools: Pandas | NumPy | Sklearn | TensorFlow | PySpark | Hadoop
๐งฑ Backend: Spring Boot | Flask | Django | Node.js
๐งฐ DevOps: Docker | Jenkins | AWS | Terraform | Git
๐ง Domains: Data Mining | ML | Computer Vision | Recommender Systems | Clustering
Developed a medical AI application to assist in early-stage dementia diagnosis by classifying brain MRI scans.
- Utilized Convolutional Neural Networks (CNNs) for automatic feature extraction from brain images
- Implemented image segmentation to isolate critical brain regions for focused analysis
- Achieved improved prediction accuracy through model optimization and data augmentation
- Tech Stack: Python, TensorFlow, OpenCV, Scikit-learn, Matplotlib
๐ Impact: Helps neurologists make informed decisions earlier, improving patient outcomes
Engineered a hybrid recommender engine tailored for job seekers, blending skill-based and collaborative filtering.
- Extracted user skill sets and job descriptions using TF-IDF vectorization
- Used K-Means clustering to group similar job seekers for better collaborative matching
- Designed backend APIs to return ranked job matches with justification tags (skills, titles, industries)
- Tech Stack: Python, Flask, PostgreSQL, NLTK, Scikit-learn
๐ Impact: Offers personalized job discovery and recruiter insights based on user profiles
Built a cost-efficient maze-solving robot using IR sensors and the LSRB (Left-Straight-Right-Backtrack) algorithm.
- Minimized hardware requirements by using only 3 IR sensors, reducing cost for hobbyists
- Integrated Arduino Pro Mini, motor drivers, and MPU6050 to handle real-time navigation and obstacle avoidance
- Designed to detect paths, turns, and dead ends, then dynamically recalculate optimal route
- Tech Stack: Arduino, IR Sensor Array, L298 Motor Driver, MPU6050, Embedded C
๐ Impact: Educational robotics platform demonstrating pathfinding logic and microcontroller integration
โThink, Create, and Innovate.โ ๐ก
Letโs build something impactful together!