Highly motivated Artificial Intelligence and Data Science student with a strong foundation in machine learning, deep learning, and computer vision. Proven ability to develop and deploy innovative AI solutions, demonstrated through impactful projects like real-time multimodal Q&A systems and advanced neural network training. Seeking to leverage strong technical skills and a passion for data-driven problem-solving in a challenging AI/ML engineering role.
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Bachelor of Engineering (BE)
Artificial Intelligence and Data Science
Grade: 8.9 CGPA
Courses
Cloud Computing
Operating System
Computer Networks
Data Structures And Algorithms
Database Management System
Software Development LifeCycle
Cryptography And System Security
Object Oriented Programming (OOPs)
Published by
IJCRT
Summary
A research paper focusing on regulatory motifs using bioinformatics and machine learning techniques. Utilized k-mer frequency vectors and GC content for DNA sequence representation beyond alignment-based methods, enabling ROC-based threshold optimization through calibrated probabilities.
Python, JavaScript, C++.
Machine Learning, Deep Learning, Computer Vision, Natural Language Processing.
Pandas, NumPy, PyTorch, Seaborn, Mediapipe, Flask.
Tableau, MS Excel.
SQL.
Communication, Teamwork, Leadership, Adaptability.
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Summary
Developed an AI-powered palm reading system integrating Computer Vision and Zodiac Insights. Tech stack: Python, Flask, OpenCV, MediaPipe, JavaScript.
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Summary
Explored Gradient-Free Neural Network Training via Layer-Wise MLP Optimization. Tech stack: Python, Deep Learning, Gradient-Free Methods, MLP.
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Summary
Developed a Gemini-based Multimodal Q&A Application with Real-Time Text & Image Understanding. Tech stack: Python, Gemini API, Data Processing, Prompt Engineering, Streamlit.
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Summary
Implemented Generative Terrain Synthesis using Deep Convolutional GANs. Tech stack: Python, Deep Learning, Image Processing, Neural Networks.