Erfan Esmaeili, Ph.D.

Machine learning researcher and engineer experienced in model training, evaluation, and deployment. Ph.D. in theoretical physics.

Erfan Esmaeili

Selected Projects

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LLM Inference Benchmarking

Comparing LLM inference engines (vLLM, TGI) in latency and throughput.

vLLM TGI FastAPI Docker

RAG QA Engine

Deployed a retrieval-augmented QA engine focused on a history topic.

  • • Database hosted on Milvus Cloud. Two-stage RAG (reranking).
  • • Local version used SPLADE and open source models. The deployed version used OpenAI API for text embeddings and llm inference.
Milvus OpenAI text encoder Streamlit

QLoRA adaptation

Adapting open LLMs with LoRA and QLoRA for text summarization.

  • • Multi-GPU training
  • • Low Rank Adaptation of quantized models
QLoRA Llama

Papers & Preprints

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Text Embedding is Not All You Need: Attention Control for Text-to-Image Semantic Alignment with Text Self-Attention Maps (CVPR 2025)

Using text-encoder information to optimize cross-attention layers in Stable Diffusion. Our training-free attention control method improves text-image alignment.

Generate What Matters: Steering Diffusion Models for Targeted Data Generation to Improve Classification (ICLR 2026 under review)

Steering diffusion models to generate effective samples that improve ViT classification accuracy in low-data medical domains.

PDF

7 papers in theoretical physics

On electromagnetic gauge fields, general relativity, celestial holography, and p-form symmetries.

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Skills

Machine Learning Methods

  • Transformer models; Diffusion models
  • LLM evaluations; prompt engineering
  • Retrieval augmented generation
  • Reinforcement learning
  • Instruction tuning, SFT, RLHF
  • PEFT/LoRA/QLoRA

Systems & Tools

  • PyTorch; HF Transformers & Diffusers
  • FastAPI; Docker; basic Kubernetes
  • vLLM/TGI for quick serving prototypes
  • Python (fluent), Bash; learning C++/CUDA

Research & Analysis

  • Probability and statistics
  • Mathematical modeling
  • Strong analytical thinking;
  • First principles thinking

Contact

Email: efakhabi@purdue.edu