Machine Learning Society
Goals and Objectives
- Foster a Strong ML Community
Create an engaging environment where students and professionals collaborate, learn, and grow in the field of Machine Learning and AI. - Encourage Hands-On Learning
Provide members with opportunities to work on real-world ML projects, research papers, and competitions. - Develop Impactful ML Applications
Encourage the development of AI solutions that address real-world problems and participate in UAE AI-related projects, government-led AI programs, and initiatives like the UAE Hackathon and UAE AI and IoT Challenge. - Organize Workshops & Bootcamps
Conduct hands-on sessions on ML fundamentals, deep learning, NLP, and AI applications. - Host AI Competitions & Challenges
Organize Kaggle-style competitions and hackathons to promote skill-building.
Faculty
Leading Students
- Nihar Gandhi – President
- Alina Biju – Vice President / Head of AI & Technical Development
- Mohammad Dakwar – Vice President
- Ashitha Ganesan – Head of Workshops & Events
Affiliated Students
- Kripa Susan Jacob
- Zara Mahreen
- Shiza Shaheem
- Shaik Nadia Tabassum
- Dhiyanesh Thangamani Kumaravelu
- Sandhli Arora
DUNE – Dubai Urban Neural Evolution
Student(s) In-charge: Alina Biju & Nihar Gandhi
Project Overview
DUNE (Dubai Urban Network Evolution) is an interactive AI-driven platform designed to model, analyze, and predict the growth of Dubai’s urban landscape. It combines data science, machine learning, and real estate analytics to provide a dynamic simulation of how urban development impacts property values and city planning.
Key Features
- Real Estate Price Prediction: Uses AI models to estimate property values based on historical data, infrastructure, and urban growth trends.
- Interactive Urban Planning: Users can modify, relocate, or introduce new buildings to see how these changes influence surrounding areas.
- AI-Driven Decision Support: Provides data-backed insights for city planners, investors, and researchers interested in Dubai’s rapid urbanization.
DUNE serves as a research-driven tool to understand city expansion, economic patterns, and urban resilience, offering a forward-looking approach to smart city development.
GCIS AI Chatbot
Student(s) In-charge: Kripa Susan Jacob, Zara Mahreen, Shaik Nadia Tabassum, Shiza Shaheem
Project Overview
The GCIS AI Chatbot is an AI-powered virtual assistant designed to support students in GCIS 123 and GCIS 124. It acts as an interactive learning tool that provides instant explanations of course concepts, clarifies doubts, and guides students through computing principles. The chatbot will be accessible via a web platform and integrated with the university’s learning management system (LMS) for seamless interaction.
Objectives
- Develop an AI chatbot tailored to GCIS 123 and GCIS 124 course materials.
- Provide instant explanations of key computing concepts and theories.
- Assist students with general troubleshooting of technical issues.
- Offer interactive discussions on course topics to enhance learning.
- Deliver curated learning resources based on student needs.
Weekly Workshops
We conduct weekly workshops focused on hands-on learning and real-world applications of machine learning. These workshops cover topics such as fundamentals of ML, deep learning, NLP, computer vision, and real-world ML projects. Sessions are designed to be interactive, often including live coding, model building, and problem-solving exercises. Some workshops also explore advanced topics like LLM-powered applications, AI ethics, and real-time data analysis. The goal is to engage students, enhance their ML skills, and encourage project development through practical learning.
