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We built a behavior-centric monitoring system that continuously observes how a deployed AI modelβs decisions change over time.
Veyransh β Your AI-powered study partner that organizes notes, predicts performance, and generates smart quizzes to boost academic success. π
EquiHER uses AI to catch diagnostic bias, helping women get faster, fairer, and life-saving care, because healthcare should work equally for everyone.
ATLAS is a cloud-native AI inference engine that optimizes execution and memory usage to reduce latency and improve throughput, enabling scalable and cost-efficient AI deployment.
Real-time phishing detection system combining machine learning, URL risk analysis, and behavioral heuristics to identify scam messages and protect users from digital fraud instantly.
A real-time UPI fraud intelligence system that combines graph analytics and machine learning to identify mule networks, detect anomalies, and trigger adaptive security actions.
Production-grade mission planner that optimizes aircraft patrols and spacecraft operations using a unified constraint-satisfaction framework with real-time replanning and Monte Carlo validation.
An intelligent system that detects cyberattacks in IoT networks by learning traffic patterns and adapting in real time using machine learning.
AtomoraCQ is an engineering acceleration platform that uses quantum algorithms and machine learning to fast-track discovery of climate-resilient materials for sustainable energy and carbon capture.
a webapp for all sutd students
AI powered tool that makes videos accessible to 466M deaf and hard-of-hearing people worldwide. Upload any video or YouTube link, get professionally captioned content in minutes. No skills required.
a dive into how poetry encapsulates emotions in clusters, and keeping a track of words or themes used by poets through mathematical representations.
A deployable Streamlit app that predicts heart disease risk in seconds - helping teams triage patients faster with interpretable probability scores and batch screening.
Leveraging machine learning to identify early chronic disease risk and enable proactive, preventive healthcare.
Objectives are to use machine and deep learning approaches along with transfer learning to classy chest diseases (pneumonia, infiltration etc) total 14 diseases using NIH xray 14 dataset.
Detecting Unstable Orbits and Forecasting Satellite Traffic in LEO
"One Framework, Two Worlds: Unified Mission Planning for Air and Space"
