Aryan Garv
Data Science & Engineering Student
Manipal University Jaipur • CGPA: 7.80
Passionate about Artificial Intelligence, Machine Learning, and Data Science. Experienced in developing intelligent systems for real-world applications.
About Me
I'm Aryan Garv, currently pursuing B.Tech in Data Science and Engineering at Manipal University Jaipur with a CGPA of 7.80. I'm passionate about leveraging data science and artificial intelligence to solve real-world problems and create innovative solutions.
My interests span across various domains including Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, and IoT. I have hands-on experience in developing intelligent systems, from recommendation engines to computer vision applications for agriculture and traffic management.
AI & ML Enthusiast
Passionate about developing intelligent systems and algorithms
Data Scientist
Extracting insights and patterns from complex datasets
Featured Projects
Professional Experience
Key Achievements:
- Preprocessed and analyzed hyperspectral datasets to extract relevant spectral-spatial features for mineral classification
- Designed and implemented a 3D Convolutional Neural Network (3D-CNN) architecture capable of learning voxel-level features across spectral and spatial dimensions
- Successfully trained the model to classify multiple mineral types with high accuracy, demonstrating the potential of HSI in remote mineral detection
- Evaluated the model's performance using metrics such as accuracy, confusion matrix, and per-class classification reports
- Contributed to discussions on real-world applications of HSI in mining, exploration, and automated geological surveying
Key Achievements:
- Researched and implemented optimality algorithms including Lagrangian multipliers, Stackelberg games, and Coalition Game Theory for sensor selection
- Formulated a comprehensive optimality equation using critical parameters such as Energy Consumption, ERS, Reliability Index, Proximity, Device User Load, Matched Efficiency Ratio, Matched Sensor Index, Device Performance Index
- Developed a Monte Carlo-based Virtual Simulator to test and validate the model under various simulated environments and constraints
- Analyzed results across multiple device and user scenarios to benchmark performance and scalability of the proposed selection algorithm
Certifications
Gained a strong foundation in core data structures and practiced solving complex algorithmic problems using recursion, dynamic programming, and greedy techniques.
Covered end-to-end C++ programming fundamentals including OOP, memory management, templates, STL, and file handling.
Explored big data processing using Hadoop, Spark, and MapReduce for handling structured and unstructured data.
Understood essential concepts in data security including encryption, access control, authentication, and data anonymization.
Learned theoretical foundations of neural networks and implemented models in TensorFlow/Keras for classification tasks.
Explored OS concepts such as processes, threads, CPU scheduling, memory management, and synchronization.
Skills & Technologies
Get In Touch
Let's Connect
I'm always interested in discussing new opportunities, collaborations, or just having a chat about technology and innovation. Feel free to reach out!