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TruthLens – Illuminating truth in real time: AI-powered, community-verified misinformation detection with explainable transparency.
A Neural Network powered speech emotion recognition system that analyzes voice signals to detect human emotions in real time
Supply chains optimized by quantum AI in seconds
Veritas AI: An autonomous agent crew that scrapes prediction markets to create a RAG-powered chatbot for tracking misinformation and public belief in real-time.
The Chat-GPT for Chip Architects
Automated MRI tumor detection platform using AI and image processing to deliver fast, reliable, and accessible healthcare.
Quick AI insights for balanced eating.
An intelligent AIOps platform that combines real‑time stats with AI‑guided RCA to auto‑diagnose incidents, explain causal chains, and predict issues early.
Hybrid ML+NLP trading system combining FinBERT sentiment analysis with technical indicators for superior risk-adjusted returns.
Suspicious detection or anomalous transactions in synthetic Web3/crypto datasets. It is designed for fraud detection tasks in blockchain ecosystems where labeled fraud data is scarce.
Minimal, original solver for Capacitated Vehicle Routing with optional Time Windows.
As generative AI use expands, so do privacy risks from data harvesting to deepfakes. We must use AI itself as a defense—to detect, prevent, and mitigate these privacy breaches.
AI flags policy-violating reviews with 90%+ accuracy using BERT. ReactJS and FastAPI enable real-time moderation for platforms like Google Maps.
Peanut BERTer is an AI-powered system that automatically filters out low-quality online reviews while preserving genuine customer feedback so you can make better decisions on where to shop and eat.
PonyTune combines rule-based heuristics with HuggingFace embeddings to deliver a fast, interpretable, and high-performing NLP classification pipeline.
Legal Lens leverages LLMs to flag TikTok features requiring geo-specific compliance, scanning feature descriptions and automating legal checks with fast, auditable, and reliable screening.
I leveraged on three models to compare flagging reviews for a comprehensive approach
RevGuard: An ML-powered system that protects online reviews by detecting spam, ads, and irrelevant content, ensuring users see trustworthy, relevant, and policy-compliant location feedback.
Our system filters spam, ads, and irrelevant TikTok reviews using a teacher-student model, delivering cleaner feedback, boosting merchant visibility, and building user trust at scale.
Uses NER models to redact sensitive PII data from CSV files.
TokTok, who’s there? Only relevant reviews.
We built a pipeline that cleans reviews and fine-tunes RoBERTa to flag spam, ads, and irrelevant content—surfacing only high-quality, trustworthy insights for businesses and users.
AI-powered moderation that automatically filters ads, rants, and spam from reviews to restore trust and ensure genuine content. Powered by Gemma-3.
