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Monesh N

Monesh N

Assistant Professor

About

I am an Assistant Professor with a deep passion for Artificial Intelligence, Machine Learning, and Data Science, dedicated to advancing knowledge through research, innovation, and teaching. I hold an M.Tech. in Computer Science and Engineering and am currently pursuing a Ph.D. in Computer Science and Engineering (CSE), where my research focuses on developing next-generation intelligent systems capable of addressing complex real-world challenges. My goal is to bridge the gap between academic research and practical applications by creating AI solutions that are accurate, scalable, efficient, and impactful.

My research interests encompass Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Explainable AI, Cloud Computing, Big Data Analytics, and Intelligent Decision Support Systems. I am particularly interested in designing novel AI architectures, optimization algorithms, and intelligent frameworks that improve the performance, interpretability, and adaptability of machine learning models. I actively contribute to research by exploring innovative methodologies and publishing scholarly work in reputable conferences and journals.

Beyond teaching and research, I continuously engage in learning new technologies, collaborating with researchers, and contributing to innovative solutions that benefit society. I strongly believe that interdisciplinary collaboration and lifelong learning are the foundations of meaningful technological advancement. My long-term vision is to become a leading researcher and educator in Artificial Intelligence, contributing to groundbreaking discoveries, nurturing future innovators, and developing intelligent systems that solve global challenges while creating a positive and lasting impact on society through research, innovation, and education.

Innovation begins with curiosity and grows through perseverance.

Airbnb Price Prediction using Hexaboost: A Data-Driven Approach
For both hosts and guests in the Airbnb ecosystem to make wise judgments, accurate price forecast is essential. This research suggests a novel method for predicting Airbnb listing costs that makes use of machine learning techniques. To train prediction models, the study incorporates a number of characteristics, including location, property type, amenities, and previous booking data. The dataset is pre-processed and valuable insights are extracted using feature engineering approaches. Mean absolute error and root mean square error are two relevant measures that are used during the training and evaluation of the models, which include gradient boosting, random forest, and linear regression. Moreover, ensemble techniques are used to combine the advantages of several models to improve forecast accuracy. The findings show that Airbnb's pricing predictions perform admirably, giving hosts insightful information to improve their pricing tactics and visitors’ information to help them make well-informed reservations. This study emphasizes the value of utilizing data-driven strategies in the sharing economy and adds to the expanding subject of short-term rental pricing prediction.

Link: https://ieeexplore.ieee.org/document/11156892

Pursuing a Ph.D. in Computer Science and Engineering (CSE) with a focus on Artificial Intelligence.

Research interests include Artificial Intelligence, Machine Learning, Deep Learning, and Intelligent Systems.

Exploring Mixture-of-Experts (MoE) architectures and efficient deep learning models for scalable AI.

Working on developing novel AI frameworks for improved performance, adaptability, and interpretability.

Research Interests

Artificial Intelligence (AI)

Machine Learning (ML)

Deep Learning

Computer Vision

Natural Language Processing (NLP)

Explainable Artificial Intelligence (XAI)

Intelligent Systems

Neural Networks and Deep Neural Architectures

Monesh N

Assistant Professor

M.Tech., Ph.D. (Pursuing)

School of Computer Science and Engineering

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