CV

Education

• PhD. in Electrical and Computer Engineering, University of California Santa Barbara, (Present)
• M.S. in Electrical and Computer Engineering, University of California Santa Barbara, 2021
• B.Tech. in Electronics and Communication Engineering, Indian Institute of Technology, Roorkee, 2016

Research experience

• Oct’2021 - Present: Graduate Student Researcher, UCSB
  • Developing tools and theoretical frameworks to lower the barriers in deploying deep learning models into real world.
• Sep’2020 - Sep’2021: Graduate Student Researcher, UCSF
  • Developed Medviz - an AWS web portal and visualization tool for deploying machine learning models for processing of large PET/MRI datasets.
• Oct’2019 - Jun’2020: Graduate Student Researcher, UCSB
  • Research on Generalization in Deep Neural Networks: (Thesis).

Work experience

• Summer 2022: Software Engineering Intern, Apple, Cupertino, CA
  • Developed physics based algorithms to improve the Fall Detection feature. Created data processing pipelines to efficiently handle hundreds of hours of time series data.
• Summer 2020: Machine Learning Intern, Briteseed, Chicago, IL
  • Using deep learning and computer vision on hyperspectral image data from surgical tools to detect tissues.
• Jul’2016 - Aug’2019: Engineer, Samsung Research Institute, Delhi, India
  • Developing Audio/Music Applications for enhancing user experience in Samsung Smart TVs.
    • Developed ML based Music Classification Engine, a C++ based audio feature extraction framework with real time classification of audio using SVM and Statistical Analysis.
    • Developed bluetooth music player for visualizing and interacting with music on Samsung Smart TVs.
• Summer 2015: Embedded Systems Intern, VIOS Medical Pvt. Ltd., Bengaluru, India
  • Vios Medical was a U.S. based medical technology company focusing on utilizing medical-grade IoT sensors and Virtual Patient Care Services, acquired by Japan’s Murata Manufacturing Co., Ltd.
    • Characterized different wireless modules used in Vios medical sensors based on energy consumption and connectivity.
    • Developed Vios Software packaging and distribution tool for Linux systems.

Courses and Skills

• Courses
  • Computer Vision, Theoretical Machine Learning, Pattern Recognition, Digital Image Processing, Optimal Estimation and Filtering, Matrix Analysis and Computations.
• Programming Languages
  • C++, Python, C, Julia, Javascript, C#, Verilog, VHDL.
• Frameworks
  • PyTorch, Keras, Tensorflow, MATLAB, openCV, numpy, scikit, ffmpeg, CUDA, ARM Compute Library (ACL).

Publications

Predicting Generalization in Deep Learning via Local Measures of Distortion

A Rajagopal, Vamshi C Madala, S Chandrasekaran, P Larson - arXiv preprint arXiv:2012.06969, 2020

Understanding and Visualizing Generalization in UNets

Rajagopal, A., Madala, V.C., Hope, T.A.; Larson, P.. (2021). Understanding and Visualizing Generalization in UNets. *Proceedings of the Fourth Conference on Medical Imaging with Deep Learning*, in *Proceedings of Machine Learning Research* 143:665-681 Available from https://proceedings.mlr.press/v143/rajagopal21a.html.

Thesis: A Study of Generalization in Deep Neural Networks

Vamshi C Madala. 2021. A study of generalization in deep neural networks. University of California, Santa Barbara.

CNNs Avoid the Curse of Dimensionality by Learning on Patches

V. C. Madala, S. Chandrasekaran and J. Bunk, "CNNs Avoid the Curse of Dimensionality by Learning on Patches," in IEEE Open Journal of Signal Processing, vol. 4, pp. 233-241, 2023, doi: 10.1109/OJSP.2023.3270082.

Scholarships and Awards

• Outstanding Performance Award, Samsung Research Institute, 2018.
• Project of the Year Award for “Music Genre Recognition”, Samsung Research Institute, 2018.
• Kishore Vaigyanik Protsahan Yojana Fellowship, Department of Science and Technology, Govt. of India, 2012.
• Multiple IIT Roorkee Semester Merit Scholarships.