Team Photo
Team Members
Aarush Patil
C S Anvitha
Sumaiya Parveen
Dhanya Shree D
Field Notes
The team explored three interconnected thesis areas: 1. Industrial Sustainability & Emission Management (Methane Focused) - Investigating how real-time monitoring and AI-driven analytics can help industrial operations identify, quantify, and reduce methane leaks and emissions at the source. 2. Predictive Maintenance Using Spiking Neural Networks - Exploring the use of biologically-inspired spiking neural networks (SNNs) for energy-efficient, edge-deployable predictive maintenance in industrial machinery, where traditional deep learning is too power-hungry. 3. Attitude Adjustment for CubeSats - Investigating lightweight algorithms for orientation and attitude control in small-form-factor satellites (CubeSats), where computational resources are severely constrained.
Domains
Also in ABC 2026
Vigil
Cross-source signal correlation layer for manufacturing maintenance — correlates alarm logs, sensor trends, and operator observations in real-time to flag developing failures before they happen.
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Creator intelligence platform bridging the gap between creators and brands — data-driven insights, authenticity assessment, portfolio management, and campaign performance tracking.
AgentOps
Explored AI-driven agentic solutions across Finance, Real Estate, EdTech, and MSME verticals — focused on identifying meaningful problems and validating real user pain points.
EdgeDaemon
Using AI to reconstruct, analyze, and improve decision-making processes — taking past decisions, reasoning, and outcomes to reconstruct how a decision was made and identify areas for improvement.
VoxNova
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EquationX
Explored the intersection of Cybersecurity, AI & ML, and Network Security — building intelligent systems that detect and respond to network threats.
Horizon
Startup & problem-solving exploration across ML, Generative AI, and Medical domains — applying Mom Test principles, Reddit community research, and JEPA model exploration to discover real user pain points.