On February 6, 2026, Srinivas Institute of Technology conducted Day 5 of the AI research bootcamp titled “GENAIVATION 2026: Innovation to Publication.” The program was organized in association with DHAARINI an AI-Tech Research Academy, with the joint effort of the ISE, CSD, and AI-DS departments.

Day 5 of the AI research bootcamp focused on advanced machine learning algorithms and ensemble learning techniques. The session was conducted by Mr. Prashanth Kannadaguli, Trainer, with the aim of helping students understand how multiple models can be combined to improve prediction accuracy.

The session began with an introduction to the K-Nearest Neighbors (KNN) algorithm, where the trainer explained how predictions are made based on the similarity between data points. This was followed by a discussion on Support Vector Machines (SVM), highlighting how SVM helps in classification by finding the optimal boundary between different classes.

The trainer then introduced the concept of ensemble learning, explaining how combining multiple models can lead to better performance than using a single model. Different ensemble methods such as voting classifiers, bagging and pasting, and boosting were discussed in a simple and clear manner, with examples to help students understand their purpose and advantages.

The session focused on building conceptual clarity around when and why ensemble techniques are used in real-world machine learning problems.

The program received strong support from Dr. Shrinivasa Mayya D, Principal of Srinivas Institute of Technology. The guidance of Prof. Sudarshan K, Head of the Department, ISE & CSD, and Prof. Nagaraja Hebbar, Head of the Department, AI-DS, played an important role in the smooth conduct of the program. The event was also supported by Dr. Praveen Shenoy, IIC Coordinator, and Prof. Rakesh Mallya. Additional support was provided by Prof. Archana D, ACODE Advisor, Prof. Ajay Pinto, AADE Advisor, and Prof. Sowmya, AISE Advisor. The program was successfully coordinated by Prof. Aparna N, Prof. Sahana B, and Prof. Ganapathi Sharma.

Overall, Day 5 strengthened students’ understanding of advanced algorithms and ensemble methods, helping them see how combining models can improve accuracy, robustness, and decision-making in machine learning applications.