Vaddadi Venkatesh

• Model-Based Deep Learning for Inverse Problems

• Medical Image Analysis: Reconstruction, Segmentation, and Classification

• Efficient Deep Learning for Real-Time Applications

K. R. Gujarati, L. Bathala, V. Venkatesh, R. S. Mathew and P. K. Yalavarthy, "Transformer-based Automated Segmentation of the Median Nerve in Ultrasound Videos of Wrist-to-Elbow Region," in IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, doi: 10.1109/TUFFC.2023.3330539.

Ayoob, A. K., Vaddadi, V., Yalavarthy, P. K., & Janakiram, C. (2023). Tooth detection and numbering in panoramic radiographs using an artificial intelligence approach. Population Medicine, 5, https://doi.org/10.18332/popmed/164270.

2024

• 1. • • Presented my research work in the EECS Research Students Symposium., Organized by IISc Bangalore, 4-5 Apr, (2024).

Vaddadi Venkatesh. (2024). "Novel and Efficient Model-Based and Deep Learning based Models for Medical Imaging." In Book of Abstracts, EECS 2024, Indian Institute of Science, p. 53. Retrieved from https://eecs.iisc.ac.in/EECS2024/resources/BookofAbstracts_final.pdf 

• 1. • • One of the Instructors for the One-Day Workshop on "Python Libraries for Machine Learning" at Siemens Healthineers, Organized by IISc Bangalore, Feb, 2024. 

2023

• 1. • • Venkatesh Vaddadi, Raji Susan Mathew, and Phaneendra K. Yalavarthy. "SpiNet-QSM: Model-based Deep Learning with Schatten p‐norm Regularization for Improved Quantitative Susceptibility Mapping,", Poster Presentation, Medical Image Computing Workshop, Organized by IISc Bangalore, 24-25 Feb, (2023). [Best Poster Award]

M.Tech: Design Analysis of Algorithms, Data structures, Operating systems, and  Machine Learning

Ph.D. : Numerical Linear Algebra, Numerical Optimization, Machine Learning, Medical Imaging, Data Analysis and Visualization, Research Methods.

• TANUH: Translational AI for Networked Universal Healthcare
  Research Staff Member—Sep 2025 to Present

  1. • • Developing a deep learning-based framework for breast cancer screening, enabling early detection and risk assessment through mammography analysis. Designing robust pipelines for accurate lesion detection and clinical decision support. Aiming to improve diagnostic efficiency and enable real-world deployment. 

• American Express
  Data Scientist, Intern—Jan 2025 to Jul 2025

  1. • • Developed automated end-to-end pipelines for financial document processing. Fine-tuned Florence-2 with custom prompts and chain-of-thought reasoning for precise table detection from heterogeneous financial documents. Leveraged LLaMA-based large language models with custom prompt engineering for accurate document classification across diverse financial document types.

IISc Bangalore: 

• DS 261(3:1):  Artificial Intelligence for Medical Image Analysis Aug-Dec,   2023         GitHub 

UOH Bangalore: 

• 1. • • Basics of Machine Learning Jan-Apr,   2018

       • Compression Algorithms Aug-Dec,   2018

Aster Health Academy: 

• AI in Healthcare: Theory to Practice 1.0       Nov,2023 - Mar,2024

• AI in Healthcare: Theory to Practice 2.0       Mar,2024 - Aug,2024

• AI in Healthcare: Theory to Practice 3.0       Aug,2024 - Dec,2024