REMYA KUNIYIL

Skilled Engineer with design, project management and planning expertise. Recent graduate with advanced qualifications, including an MSc in Robotics and Smart Technologies from the United Kingdom, actively seeking opportunities to apply expertise in robotics, machine learning, and artificial intelligence.Analytically driven professional with a background in data analysis, adept at optimizing productivity and task efficiency. Specialize in machine learning, predictive modeling, and big data analytics. Bring critical thinking, problem-solving, and teamwork skills to excel in collaborative environments.

• Individual Modules Artificial Intelligence (EU Funded)
• Artificial Intelligence Foundations: Machine Learning- LinkedIn Learning
• Machine Learning with Python: Foundations - LinkedIn Learning
• Introduction to Deep Learning with OpenCV - LinkedIn Learning
• Introducing Robotic Process Automation - LinkedIn Learning
• Intelligent Automation Foundations - LinkedIn Learning
• Introduction to PLC and Industrial Automation - LinkedIn Learning

Credit Card Fraud Detection using Machine Learning, 2024, Developed and implemented a predictive model using Logistic Regression and Random Forest to detect fraudulent credit card transactions with an accuracy of over 95%., Addressed class imbalance using SMOTE, resulting in improved recall and reduced false negatives., Conducted data preprocessing, feature scaling, and exploratory data analysis to identify key patterns in transaction behavior., Evaluated model performance using metrics like AUC-ROC, precision, and recall, achieving an AUC score of 0.98. Emotion Recognition in Textual Conversation Using Machine Learning, 2023, Built an end-to-end machine learning pipeline for multi-class emotion classification using Python libraries (NLTK, spaCy)., Preprocessed text data with tokenization, stopword removal, and feature extraction (TF-IDF, n-grams, word embeddings)., Trained models including Random Forest, Naive Bayes, and K-Nearest Neighbors, achieving over 80% accuracy in detecting emotions like joy, sadness, and fear., Evaluated model performance with a confusion matrix, highlighting Random Forest as the top-performing model. Energy Aware Routing By Crosslayer Approach in MANETS, 2015, Applied cross-layer optimization strategies to optimize mobile ad hoc networks for energy efficiency. Tongue Motion Controlled Wheelchair, 2013, Project leverages a PIC microcontroller and Hall effect sensors to create a Tongue Motion Controlled Wheelchair, enhancing accessibility and mobility for users with limited physical capabilities.

• A Survey On Energy Aware Routing Issues And Cross Layering In MANETs, International Journal of Electronics and Communication Engineering and Technology, 5, 12, 47-54, 12/2014
• QoS Improvement In Mobile Ad Hoc Networks Using Cross Layer Optimization, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 4, 1, 272-278, 03/2015
• Cross Layer Design of Energy Efficient Multipath Routing Protocol Using Adjustable Sleeping Window in Manets, IEEE, Global Conference On Communication Technologies, Noorul Islam University, Nagercoil, 04/2015

• English, Fluent
• Malayalam, Native
• Hindi, Elementary