VISHNUPRIYA VIJAYAN

Aspiring to secure a challenging role in data science, where my expertise in data analysis, machine learning, and pattern recognition can be leveraged. Enthusiastic about contributing to innovative solutions and professional growth within a dynamic organization, with a keen interest in machine learning, artificial intelligence, and future opportunities in computer vision.

• Certified Specialist in Machine Learning and Artificial Intelligence, ICT Academy of Kerala, Thiruvananthapuram, Thiruvananthapuram, 92/100
• Python Programming, ICT Academy of Kerala, Thiruvananthapuram, Thiruvananthapuram, 98/100
• Internship on AI (30 days), Pantech Solutions

• Best Paper Award, Biomedical Image & Signal Processing Track, CISCON - 2022
• Recipient of National Doctoral Fellowship (2019-2022)
• Qualified GATE 2019 with an all-India rank of 4601 and a score of 514
• Qualified UGC-NET exam for Assistant Professor (July 2018)
• Recipient of GATE scholarship (2015-2017)
• Recipient of CSSS scholarship (2010-2014)

• Performance analysis of modulation classification using machine learning, Second author, IEEE
• SNR estimation based on machine-learned modulation classification for link adaptation, Corresponding author, CISCON_2022, Accepted and submitted to Lecture notes in electrical engineering, springer

• Modulation Classification using Deep Learning- Implemented ResNet, GRU, and CNN models to classify modulation formats. Utilized CNN for feature extraction and ResNet/GRU for classification.

- Skills & Tools: Deep Learning, Convolutional Neural Networks (CNN), Gated Recurrent Units (GRU), Residual Networks (ResNet)

• Real-time Face Recognition System- Developed a real-time face recognition system using OpenCV and LBPH algorithm. Integrated Haar Cascade classifier for face detection and trained on a specific dataset.

- Skills & Tools: OpenCV, Machine Learning, Image Processing, Python

• Feature-based Deep Learning for Modulation Classification- Extracted statistical features from signals in Rayleigh faded channels. Implemented feature selection and compared performance of MLP and CNN models.

 - Skills & Tools: Deep Learning, Machine Learning, Feature Engineering, Signal Processing

• Sentiment Analysis on Twitter Data- Analyzed sentiment from Twitter using text preprocessing, TF-IDF vectorization, and Random Forest model. Visualized sentiment categories with confusion matrices.

- Skills & Tools: Natural Language Processing (NLP), Machine Learning, Python, Data Visualization

• Online Retail Orders Analysis- Conducted SQL queries and data analysis on an online retail store's orders database. Provided actionable insights for business decision-making.

- Skills & Tools: SQL, Data Analysis, Business Intelligence Tools

• Advanced Computer Vision - Object Detection and Recognition- Developed object detection model for human faces and implemented a face identification system using CNN and Siamese Networks.

- Skills & Tools: Computer Vision, CNN, Siamese Networks, TensorFlow

• Neural Networks & Deep Learning - Image Classifier- Built neural network models to predict signal quality and classify street-level images using TensorFlow.

- Skills & Tools: Neural Networks, Deep Learning, TensorFlow, Image Recognition

• Feature Engineering & Model Tuning - Semiconductor Manufacturing- Applied supervised learning techniques to predict yield in semiconductor manufacturing. Conducted feature engineering and optimized models using grid search.

- Skills & Tools: Supervised Learning, Feature Engineering, Model Tuning, Python

• Ensemble Techniques Project - Customer Churn Prediction- Addressed customer churn prediction using ensemble methods like logistic regression, decision trees, and XGBoost for a telecommunication company.

- Skills & Tools: Ensemble Learning, Machine Learning, Python, EDA

• Supervised Learning Project - Healthcare Biomechanics- Predicted patient conditions and potential customer conversion using various classification techniques applied to biomechanical data.

- Skills & Tools: Supervised Learning, Classification Algorithms, Healthcare Analytics

• Unsupervised Learning Project - Vehicle Segmentation- Segmented cars into categories based on fuel consumption and classified vehicle silhouettes using clustering and SVM.

- Skills & Tools: Unsupervised Learning, Clustering, Support Vector Machines (SVM), Python

• Applied Statistics Project - Startup Analysis- Utilized statistical inference and hypothesis testing to analyze startup competition data and inform investment decisions.

- Skills & Tools: Statistical Analysis, Hypothesis Testing, Data Visualization, Python

• Image and Video Enhancement- Designed a real-time image enhancement algorithm based on Retinex theory in MATLAB to improve image quality and detail preservation.

- Skills & Tools: Image Processing, MATLAB, Algorithm Design