🎓 MS in Electrical & Computer Engineering @ Rutgers (Expected Dec 2025)
💻 Researcher in Implicit Neural Representations (INRs) & Image Denoising
📊 Ex-Software Engineer @ Walmart Global Tech (NLP + ML Systems)

• Bagging-Based INRs for Image Denoising
  Explored bias-variance tradeoffs using SparseMLPs, Fourier mappings, and bagging. Benchmarked against BM3D, DIP, and diffusion models.

• Multimodal Disease Detection
  Combined Vision Transformer (ViT) + BERT for disease detection from chest X-rays + radiology reports.

• Brain MRI Anomaly Detection
  Built tumor detection pipeline with Diffusion Models + VAEs, custom preprocessing for anomaly localization.

• Resume Improvement System
  Fine-tuned Flan-T5 with LoRA + Sentence-BERT + FAISS. Deployed with FastAPI + AWS Lambda.

• Walmart Global Tech – Software Engineer 3

  • Reduced NLP pipeline latency by 40% (BERT → ALBERT optimization).
  • Built dashboards with SQL + Airflow + Looker for real-time monitoring.
  • Designed scalable ML microservices.

• Rutgers & Columbia – Graduate Research Assistant

  • Multi-GPU training for large-scale INR denoising.
  • Analyzed PPG data + NLP pipelines for dementia datasets.

Languages: Python, C++, C, Java, SQL, MATLAB
Libraries/Frameworks: PyTorch, TensorFlow, Keras, SpaCy, FAISS, CUDA, Ray
Tools: Docker, Kubernetes, Airflow, Git, AWS

• LinkedIn
• GitHub
• 📧 manasa.mangipudi@rutgers.edu

⭐️ Check out my pinned projects below!