Vinay Pant

Vinay Pant is currently pursuing an M Tech in Computer Science with a specialisation in Artificial Intelligence at Netaji Subhas University of Technology (NSUT), Delhi. He completed his Bachelor of Technology in Computer Science Engineering from the National Institute of Technology (NPSEI), Pithoragarh, affiliated with Uttarakhand Technical University, Dehradun. 

He is a qualified GATE candidate in Computer Science and Engineering, having cleared the examination in 2023 and 2024, conducted by IISc Bangalore. His research interests lie in Cyber Security and Artificial Intelligence, with a focus on developing secure, data-driven, and intelligent software solutions.

Vinay brings hands-on professional and research experience to his academic pursuits. He worked as a Subject Matter Expert at Chegg from April 2022 to January 2024, where he authored solutions to advanced Data Structures and Algorithms (DSA) and core computer science problems for a global student base. He also served as an R&D Trainee at Shunya Ekai Technologies, Gurgaon, from April to June 2023, where he worked on IoT-based solutions using ESP32, LoRa, and Raspberry Pi, along with embedded C and MQTT/HTTP protocols.

His project portfolio includes a Retrieval-Augmented Generation (RAG)-based Healthcare Assistant developed during the HCL Tech Hackathon, a machine learning-based health analytics web application for chronic disease prediction, and a sentiment analysis model for restaurant reviews that achieved 85% accuracy. He is proficient in Python, C, C++, Java, and JavaScript, and has practical experience with TensorFlow, Keras, Scikit-Learn, Generative AI technologies including RAG and LLM tooling, React.js, Flutter, Docker, AWS, and Linux.

Vinay has further strengthened his technical foundation through professional certifications and training programmes. He holds NPTEL certifications in ‘Joy of Computing using Python’ and ‘Problem Solving through Programming in C,’ along with Core Java and C/C++ certifications from Infowiz, Chandigarh. He has also completed a six-week industrial training programme on Machine Learning using Python.