Ph.D. Scholar in AI at IIT Delhi • Researcher in Efficient AI • Enthusiast in LLMs, NAS, and Model Compression

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Ph.D. Scholar, IIT Delhi
Working on Efficient AI & Accelerating LLMs
Collaborated with Samsung Research and Cadence India

• 🧠 VTrans – 10× speed-up for LLM fine-tuning + 50% compression
• 🚀 TVA-prune – 60% GPU inference speed-up for LLaMA/Mistral
• 🤖 DCA-NAS – 5× faster hardware-aware NAS on distributed GPUs

Student Researcher, IIT Dhanbad

• Worked on tempo and rhythm extraction in polyphonic music using ML
• Published findings in IEEE conference

Intern, Aerospace Dept., IISc Bangalore

• Designed algorithms for fuel-efficient lunar landings
• Benchmarked efficiency on TMS320C6748 DSP

• Languages: Python, C, Java, MATLAB
• Frameworks: PyTorch, TensorFlow, OpenCV
• AI: CNNs, RNNs, GANs, LLMs, ViTs, Multimodal, NAS
• Research Interests: Efficient AI, Model Compression, Pruning, Quantization, NAS
• Other: LoRA, Few-shot Learning, Post-Training Quantization, Deployment

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