researcher = {
"name" : "Muhammad Idrees",
"affiliation" : "FAST-NUCES Islamabad · CS Undergraduate",
"location" : "Rawalpindi, Pakistan 🇵🇰",
"focus" : ["Machine Learning", "HPC / CUDA", "Generative AI", "NLP"],
"mission" : "Build AI systems that are efficient, scalable, and universally accessible",
"status" : "Open to Research Collaborations · PhD Opportunities · Internships",
"contact" : "muhammad.idrees2k25@gmail.com",
}I'm an undergraduate AI/ML researcher working at the intersection of deep learning, high-performance computing, and generative AI. My work spans from low-level CUDA kernel optimization to building multi-agent LLM pipelines. I care about making models that actually work — fast, interpretable, and deployable.
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🧠 Machine Learning & NLP
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🖥️ High-Performance Computing
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🤖 Generative AI
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🔬 Currently Exploring
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Hybrid ML pipeline using BERT + T5 transformers to analyze text and auto-generate reading comprehension questions and quizzes. Designed as a full AI-powered educational tool. |
Designed a 182K-parameter DAE achieving 24.62 dB PSNR and 0.8225 SSIM. Accompanied by a full 10-page LNCS-format research report with 45+ ablation experiments. |
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Architected a modular multi-agent pipeline for AI video generation. Specialized LLM agents handle scriptwriting, scene planning, and synthesis — with Gemini primary and Groq fallback. |
Fully offline autonomous agent that joins live Google Meet sessions, transcribes speech, marks attendance, answers questions, and auto-generates structured PDF notes. Zero API keys. |
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Vanilla RNN encoder-decoder for low-resource Eng→Urdu NMT. Empirical study on vanishing gradients, sequence bottlenecks, and training instability in under-resourced language pairs. |
Production-grade MLB fan engagement platform using Google Cloud AI. Built real-time predictive models and personalized content pipelines for live game enhancement. |
Languages
ML / Deep Learning
Generative AI & LLMs
HPC & Systems
Cloud & MLOps
🎓 Stanford Code in Place — Section Leader 2025 |
Selected from a global pool to mentor students in Python & computational thinking for Stanford's international CS program |
🔬 CERN Beamline for Schools (BL4S) 2025 |
Competed in CERN's international physics competition, proposing an original experiment applying HPC and ML concepts |
☁️ Google Cloud × MLB Hackathon 2025 |
Built a production-grade AI fan engagement platform on GCP with real-time predictive models |
📄 LNCS Research Report — Denoising Autoencoder 2025 |
Produced a full 10-page academic paper with 45+ ablation figures on CIFAR-10 image denoising |
| ✍️ AI Research Writing on Medium | Publishing technical deep-dives on ML, NLP, and systems for a global audience |
Explore research articles, tutorials, and ML deep-dives on Medium →
Machine Learning · HPC · Generative AI
Rawalpindi, Pakistan → Open to Remote Research & PhD Opportunities Worldwide
