Madhu Vamsi

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Madhu Vamsi A.
Research Intern
Machine Intelligence and Reselience Lab
IIT Gandhinagar

Email: madhumarvel143 At gmail.com

Google Scholar , Linkedin


Education

  1. Bachelor of Technology in Computer Science and Engineering (Hons) -Pursuing

Research Interests

  1. Deep Leaning
  2. Machine Learning
  3. High Performance Computing
  4. Data Science
  5. Computer Vision

Achivements

  1. Best paper award in 5th IEEE international conference on Advanced Computing and communication systems 2019
  2. 1st Runner Up in Smart India Hackathon 2019 for the problem of Department of Atomic Energy
  3. Awarded top 5 and 200 dollars in IEEE maker fair SS12 held at National Green University, Colombo, Srilanka
  4. Best paper award in International conference (ICRDE) Coimbatore
  5. Awarded 1st prize in Project Expo competition held in Kalasalingam university on the memory of Dr. A. P. J. Abdul Kalam.
  6. Awarded by Silver in Machine Learning in NPTEL by IIT Madras. (Top 2%)

Publications

  1. Awasthi, Akash, A. Madhu Vamsi, Vibhuti Duggal, P. Deepalakshmi, and Surendra Rao. "3D Visualization and Localization of Radiation Source in External Radiotherapy Using Inverse linear Boltzmann Transport Equation." In 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS), pp. 123128. IEEE, 2019. Link
  2. A. Madhu Vamsi , Akash Awasthi, P. Deepalakshmi, P.Nagraj, P. Anup Raj: IOT Based Autonomous Inventory Management for Warehouses, EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2018), 13 – 15 December 2018. EAI/Springer Innovations in Communication and Computing. Springer. (Under Process)
  3. Akash Awasthi, A. Madhu Vamsi ,P.Deepalakshmi, P. Nagraj: " Movable barcode scanning system using IOT smart glass technology" International Journal of Intelligent Enterprise. (Accepted)

Projects

  1. MSME project with grant of 6 lakh Rs. Project title: Autonomous smart storage using deep learning for fruit preservation ID No: TEMP/IDEA/160
  2. Community Service Project in semester curriculum on the topic: Deep Learning (RCNN) based mobile robot for warehouse keeping.
  3. 3D visualization and localization of radiation source using inverse Boltzmann transport equation Link