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Veena Chidurala
Assistant Professor
Scripps Gerontology Center - Fellows, Electrical and Computer Engineering

Veena Chidurala, Ph.D.

Contact Info

513-529-0017
Garland Hall, 260 Q

Education

  • Ph.D., Electrical Engineering, University of North Texas, 2022
  • M.S., Electrical Engineering, University of North Texas, 2016
  • B.Tech., Electronics and Communication Engineering, Jawaharlal Nehru Technological University, Hyderabad, India, 2014

Research Interests

  • Sensor Systems
  • Internet of Things
  • Signal Processing
  • Computer Vision
  • Machine Learning

Research Areas/Applications

  • Assisted Living
  • Smart Buildings
  • Smart Farming

Experience

  • 2023 – Present, Miami University, Assistant Professor, Dept. of Electrical and Computer Engineering
  • 2023, PIC USA, Inc., Computer Vision Engineer
  • 2021, National Renewable Energy Lab, Graduate Intern - Computer Vision and Machine Learning (Summer, Fall, 2021)
  • 2020, Ericsson, Data Scientist Intern (Summer 2020)
  • 2015 – 2022, University of North Texas
    • 2019 - 2022, Teaching Fellow, Dept. of Electrical Engineering
    • 2015 - 2016, 2017 - 2019, Teaching Assistant, Dept. of Electrical Engineering

Selected Honors and Awards

  • 2022, Outstanding Ph.D. Student Award, University of North Texas
  • 2022, First Place, Best Paper Award, IEEE International Conference on IoTaIS
  • 2020, E-Star Make a Difference Award, Ericsson
  • 2019, Outstanding Teaching Assistant Award, University of North Texas

Principal Publications

  • H. Kandula, V. Chidurala, Y. Cao and X. Li, '"Localization of a BLE Device Based on Single-Device RSSI and DOA Measurements," Network, vol. 4, no. 2, 2024.
  • V. Chidurala, X. Wang, X. Li and J. Hamner, '"IoT based Sensor System Design for Real-Time Non-Intrusive Occupancy Monitoring," 2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS), 252–257, 2022. (Received Best Paper Award, First place)
  • D. Kesseli, V. Chidurala, R. Gooch and G. Zhu, '"A Combined Computer Vision and Deep Learning Approach for Rapid Drone-Based Optical Characterization of Parabolic Troughs," Journal of Solar Energy Engineering, vol. 145, no. 2, 2022.
  • V. Chidurala and X. Li, '"Detection of moving objects using thermal imaging sensors for occupancy estimation," Internet of Things, vol. 17, 2022.
  • V. Chidurala and X. Li, '"Occupancy Estimation Using Thermal Imaging Sensors and Machine Learning Algorithms," IEEE Sensors J., vol. 21, no. 6, 2021.