Hello, I'm
Yatharth
Garg
B.Tech CSE student at SRMIST, passionate about machine learning, satellite systems, and building impactful software. Currently researching anomaly detection & neural interfaces.
Education
B.Tech in Computer Science & Engineering
SRM Institute of Science and Technology
Relevant Courses: Data Structures & Algorithms, Operating Systems, Web Technologies, Artificial Intelligence & Machine Learning
High School Diploma
Treamis World School
Relevant Courses: Physics, Chemistry, Mathematics and Computer Science
Skills
Projects
Project Sentinel
Satellite Telemetry Anomaly Detection
An end-to-end ML-based telemetry intelligence framework designed to monitor satellite health in real time. Research paper is currently under review for publication.
Space Situational Awareness
Orbital Debris Monitoring System
Monitors satellites and orbital debris using TLE data. Predicts short-term orbital positions, identifies close approaches, and categorizes risk levels based on minimum separation distance.
View Repository →Project Levitas
Levitation via Active Stabilization
Active Magnetic Containment & Levitation System using dynamically controlled electromagnets to stabilize objects without contact. Aimed at ultra-precise contamination-free manufacturing.
View Repository →Fault Detection in Virtual Machines
Cloud Infrastructure Reliability
A machine learning–based system for detecting and classifying faults in virtual machine environments. Monitors system metrics to identify anomalies and performance degradation, enabling proactive remediation in cloud infrastructure.
View Repository →Neuro-Move
Neural Interface Motion System
A cutting-edge neural interface project exploring brain-computer interaction and motion control using signal processing and machine learning to decode neural patterns into actionable movement commands.
View Repository →Experience
R&D Intern
SRM Institute of Science and Technology
- Applying machine learning algorithms, including K-Nearest Neighbors (kNN) and Graph Neural Networks (GNN), to develop predictive models for disease recognition.
- Utilizing Principal Component Analysis (PCA) for feature extraction and dimensionality reduction to optimize model performance and processing efficiency.
- Engineering a system architecture designed to analyze complex medical data patterns and accurately predict specific disease indicators.
- Collaborating on the research and development of a diagnostic support tool, focusing on high-accuracy classification and data-driven insights.
- Contributing to technical documentation and data preprocessing pipelines to support ongoing project scaling and future peer-reviewed publications.
Web Development Intern
Unified Mentor
- Developed and styled web pages from design specifications using HTML, CSS, and JavaScript.
- Wrote clean, maintainable code following front-end best practices and accessibility standards.
- Ensured responsive design across various screen sizes and devices.
- Collaborated with designers and back-end developers to integrate UI components with application logic.
- Tested and debugged front-end functionality and made iterative improvements based on user feedback.
Get In Touch
Open to Opportunities
Currently looking for internships, research collaborations, and exciting projects. If you'd like to connect or have something interesting in mind — I'd love to hear from you!