Srivani Inturi
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Email: srivani.inturi@ucdenver.edu
Office Address: 1380 Lawrence Street, LW-822, Denver, CO 80204
About
I’m Srivani Inturi, and my area of focus is to study algorithms in Deep Learning with the aim of handling big data with self-improving learning and making decisions whenever it detects a change in pattern. I have a strong background in Big Data, Deep Learning, and Data mining. I was curious to learn how artificial intelligence might advance our understanding of our space during my graduation. I significantly contributed to the detection of ionospheric scintillations and the prediction of TEC that influences GPS radio waves to provide users with an alert system. I have a proven track record of publications in IEEE journals and a patent in this area. Having this expertise gives me enthusiasm to work on applied applications of artificial intelligence on ionospheric physics.
Here is a link to my resume.
Current Projects
- Spatial and Temporal Forecasting of the Upper Atmosphere using Deep-Learning (funded by ORS@CU Denver, (4/23)), co-advisor: Mark Golkowski, Ph.D.
Publications
- Briand, C., Clilverd, M., Inturi, S., & Cecconi, B. (2022). Role of hard X-ray emission in ionospheric D-layer disturbances during solar flares. Earth, Planets and Space, 74(1), 41. [link]
- Rao, T. V., Sridhar, M., Ratnam, D. V., Harsha, P. B. S., & Srivani, I. (2021). A bidirectional long short-term memory-based ionospheric foF2 and hmF2 models for a single station in the low latitude region. IEEE Geoscience and Remote Sensing Letters, 19, 1-5. [link]
- Ram Sandeep, D., Prabakaran, N., Madhav, B. T. P., Vinay, D., Sri Hari, A., Jahnavi, L., … & Inturi, S. (2021). Sequential Nonlinear Programming Optimization for Circular Polarization in Jute Substrate-Based Monopole Antenna. In International Conference on Intelligent and Smart Computing in Data Analytics: ISCDA 2020 (pp. 215-221). Springer Singapore. [link]
- Srivani, I., Prasad, G. S. V., & Ratnam, D. V. (2019). A deep learning-based approach to forecast ionospheric delays for GPS signals. IEEE Geoscience and Remote Sensing Letters, 16(8), 1180-1184. Chicago [link]
Patents
- I. Srivani, D. Venkata Ratnam, Senior Member, IEEE, G. Siva Vara Prasad, “Hybrid forecasting of ionospheric delays based on PCA-LSTM Deep Learning method using GPS Observations,” 2019, India Patent application Published, Application no. 201941003447 A