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AI Engineer with less than a year in Machine Learning & Data Engineering
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Computer Science graduate with experience in machine learning, optimization, and data engineering. Skilled in Python, SQL, and ML frameworks, with hands-on experience in data preparation, feature engineering, model development, and evaluation. Passionate about building data-driven systems that solve practical problems and create measurable value.
Thiagarajar College of Engineering
Bachelors of Engineering · Computer Science
N/A – June 30, 2025
Indian Institute of Science Bengaluru
Research Intern
July 1, 2025 – September 30, 2025
Bengaluru, India
Cyber Crime Police Station
Software Development Intern
February 1, 2023 – August 31, 2023
Madurai, India
Adaptive Myoelectric Hand Control using RL
January 1, 2025 – May 31, 2025
• Developed a robust sEMG preprocessing pipeline for 8-channel myoelectric data (20-450 Hz bandpass filter, 200ms segmentation) to enable low-latency control adapted to user. Extracted a time-domain feature vector (MAV, RMS, WL, ZCR) to serve as the state representation for the RL control agent. • Designed and implemented a hybrid two-stage Actor-Critic Reinforcement Learning (RL) architecture with initial supervised pre-training for gesture baseline. Engineered a Human-in-the-Loop (HIL) adaptive control mechanism that processes user voice feedback (via NLP) for Temporal Difference (TD) learning updates, maintaining a validated 89% real-time operational accuracy. • Obtained a UK Design Patent on the Myoelectric Prosthetic Hand's design and a research Paper is under review for publication in the Neural Computing and Applications Journal.
Acute Lymphoblastic Leukemia Severity prediction using CNN
July 1, 2024 – December 31, 2024
Engineered the core Deep Learning model (CNN) for ALL severity classification, achieving a validated 98.6% classification accuracy in differentiating four malignant/benign subtypes. • Developed a robust image pre-processing pipeline using OpenCV (Gaussian filtering, segmentation) to consistently isolate and standardize lymphoblast cells for analysis. • Optimized the CNN architecture via transfer learning and rigorous hyperparameter tuning (Adam, batch normalization) to ensure strong generalization and minimize overfitting
Voice Based Common Cold Detection
August 1, 2023 – February 29, 2024
Collected 600+ voice samples with and without common cold. Augmented the dataset to 2000 samples. Compared 6 Machine Learning and 1 CNN based Algorithm to find the one with the best Testing Accuracy. Concluded that the CNN-based Algorithm had the lowest False Positive and True Negative Values in the Test Data while maximizing the accuracy (96%). • Won the Best Paper Award in 2nd IEEE and ACM ic-ETITE '24 Conference held in VIT, Vellore and the paper was published in the proceedings of the conference
UiPath Automation Explorer
UiPath
June 1, 2026 – Present
IBM AI Developer Specialization
IBM
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic background and project diversity, including a patent and published paper, suggest a strong drive for innovation and continuous learning, which aligns well with a research-oriented or fast-paced AI engineering environment. Their involvement in team projects and internships indicates an ability to collaborate and contribute to practical applications. The breadth of skills and exposure to different problem domains (healthcare, robotics, cybersecurity, manufacturing optimization) demonstrate versatility and a willingness to tackle varied challenges.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project work and research. Their ability to work on diverse projects (medical, robotics, optimization) suggests adaptability and a proactive learning attitude. The patent and publication indicate a drive for innovation and thoroughness. The internship at Cyber Crime Police Station shows an understanding of system development and data security in a practical, operational context.