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AI Engineer with less than a year in Machine Learning & IoT Systems
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AI & Robotics student with strong foundational knowledge and practical project experience in Machine Learning, IoT Systems, and Data Analysis. Proven ability to develop and deploy real-time AI solutions, automate workflows, and achieve high accuracy in complex tasks. Eager to apply competitive coding and deep learning skills to innovative engineering challenges.
Vellore Institute of Technology
Bachelor of Technology · Computer Science, with a specialization in Artificial Intelligence and Robotics
August 1, 2022 – June 30, 2026
Atomic Energy Central School, Kudankulam
Class XII
June 1, 2022 – May 31, 2022
AI-Based Real-Time Pothole Detection & Mapping System
March 1, 2026 – March 1, 2026
Developed a real-time pothole detection system leveraging a hybrid dual-trigger mechanism combining MPU6050 sensor-based acceleration thresholds and ResNet18-based deep learning classification, enabling robust and reliable detection under real-world conditions. Designed an end-to-end IoT pipeline integrating ESP32, ESP32-CAM, and GPS modules with UDP communication to capture and transmit acceleration data, geolocation, and real-time road images for centralized processing. Implemented a Flask-based backend with REST APIs and multithreading to handle concurrent data processing, image inference, and alert generation, ensuring low-latency real-time performance. Achieved 66.67% accuracy with the ResNet18 model; improved generalization using data augmentation and dropout, and enabled automated pothole logging (SQLite) with email alerts containing image and location data.
View ProjectAutomated Scholarship Finder & Notifier
November 1, 2025 – November 1, 2025
Developed a hybrid UiPath–Python RPA system to automate scholarship discovery, eligibility filtering, and notification workflows, eliminating repetitive manual searching across multiple scholarship portals. Designed an end-to-end automation pipeline integrating UiPath-based web data extraction, BeautifulSoup/Selenium-based web scraping, Excel-based data consolidation, and rule-based filtering using dynamic user profiles stored in JSON format. Built a lightweight web dashboard for real-time profile management and implemented SMTP-based automated email notifications containing eligible scholarships, deadlines, award details, and application links. Configured unattended weekly execution using UiPath Orchestrator with centralized logging, retry-based exception handling, and workflow monitoring to ensure reliable automation under dynamic website conditions.
View ProjectUnsupervised Network Anomaly Detection
April 1, 2025 – April 1, 2025
Developed an unsupervised network anomaly detection system leveraging SDDAE, VAE, and Stacked Autoencoder with Classifier, enabling robust feature extraction, probabilistic latent modeling, and accurate anomaly classification. Preprocessed and utilized the KDD Cup 1999 dataset (KDDTrain+ and KDDTest+) with label encoding, Min-Max scaling, and a binary classification setup (normal vs. anomaly). Achieved 78% accuracy with the Stacked Autoencoder, demonstrating the best trade-off between precision and recall for effective detection of both normal and anomalous network traffic.
View ProjectAndroid App Development
IMARTICUS Learning
June 1, 2026 – Present
Java Programming
HackerRank
June 1, 2026 – Present
MySQL Practice
LeetCode
June 1, 2026 – Present
Algorithm Practice (C++)
LeetCode
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive and innovative approach to problem-solving, aligning well with a dynamic AI engineering environment. The diversity of projects (network security, RPA, IoT) indicates a broad interest in applying AI across different domains. The specialization in AI and Robotics further strengthens the cultural fit for an AI Engineer role. However, the lack of professional experience means cultural fit is primarily inferred from academic pursuits.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to design and implement complex systems, suggesting strong problem-solving and analytical skills. The use of tools like UiPath Orchestrator for workflow monitoring and exception handling points to an understanding of operational reliability. However, without direct work experience or interview data, it's difficult to fully assess collaboration, communication, and stress handling.