Mrinmoy Borah

A committed and research-driven tech aficionado with robust expertise in Machine Learning, Deep Learning, and mobile application development. Proficient in C++ and Python, with hands-on experience in modern frameworks such as TensorFlow, Scikit-learn, and LangChain. Successfully published research in international conferences on password strength analysis and AI-enhanced financial recommendation systems. Demonstrates a proven track record in developing intelligent systems, analyzing complex datasets, and building secure, scalable applications. Recognized for strong problem-solving capabilities, critical thinking, and a self-motivated approach to continuous learning. Consistently acknowledged as a top academic performer and Dean’s Lister, showcasing the ability to blend innovation, technical depth, and real-world applicability.

• Semester topper for five consecutive semesters, recognized for academic excellence, and consistently securing the highest SGPA among peers

• Beyond Characters: A Machine Learning Approach to Password Strength Analysis, presented at the North East India AI Summit: Unraveling Trends (NEIAIS-2025), published by CRC Press, Taylor and Francis Group, February 2025, Manipur
• Enhancing Investment Decisions: A Machine Learning Approach to Recommending Stocks and Mutual Funds, presented at the 3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, published by IEEE, February 2025, Assam

• Pneumonia vs. Normal Lungs X-Rays – CNN Classification Model: Developed a Convolutional Neural Network using TensorFlow to classify chest X-ray images into pneumonia or normal categories, achieved high accuracy through image preprocessing, data augmentation, and fine-tuning hyperparameters, and demonstrated skills in deep learning, computer vision, and medical image analysis
• Suicidal Tweet Detection – NLP and Classification Model: Built a machine learning model to detect suicidal intent in tweets using NLP techniques, such as TF-IDF and word embeddings. Trained classifiers, like SVM, Random Forest, RNN and LSTM, to achieve meaningful prediction performance, focused on mental health awareness, and ethical AI
• Cypher – Android App Using Kotlin and Gemini API: Designed and developed Cypher, an intelligent Android app that interacts with users via Google’s Gemini API for natural language processing, integrated real-time communication, and personalized AI-powered features, demonstrating skills in Kotlin, API integration, UI/UX, and mobile development

• Data Scientist Professional with Python, DataCamp, January 2023 – July 2023,
• Machine Learning Specialization, DeepLearning.AI, Coursera, Stanford CPD, UVM, July 2023,
• TensorFlow Developer Professional Certificate, DeepLearning.AI, August 2023