Back close
Admissions

Dr. Kavya sai yaddanapudi

Assistant Professor, School of Artificial Intelligence, Bengaluru

y_kavya@blr.amrita.edu
Orcid Profile
Google Scholar Profile
Scopus Author ID
Research Interest: Plant electrophysiology, Speech Processing

Bio Publications Research Interest Awards
Bio

Dr. Kavya Sai Yaddanapudi did her bachelor of Technology (2010-2014) from JNTU, Kakinada, Andhra Pradesh. She worked in Industrial study project based on satellite transceivers and jammers in Ananth Technologies Pvt Limited (2013). She did her internship on Missile launchers for (Akash, Nag missiles) in Bharath Dynamics Limited, Bhanur unit, Medak District (2014-2015). She qualified GATE 2015 with 97.8 percentile. She pursued her Master of Technology (2015-2017) in NIT, Jalandhar. Later, she worked in Vignan University for 6 months (2017-18). Dr. Kavya Sai pursued her doctoral studies at NIT Jalandhar, Punjab (2018-2024). She worked on Electrophytographic signals (EPG) of various plant species in different pathologies, stress cases and developed various feature enhancement, sample space reduction and clustering algorithms. She published 4 SCI(E),and 1 Scopus indexed papers in International Q1 journals, 2 International Conferences as first and corresponding author.

Publications

Conference Proceedings

Year : 2024

Early Detection and Classification of Waterlogging Stress in Broccoli Plants Prior to Visual Symptom Appearance Through Electrophysiological Signal Analysis

Cite this Research Publication : Kavya Sai, Neetu Sood, Indu Saini, Early Detection and Classification of Waterlogging Stress in Broccoli Plants Prior to Visual Symptom Appearance Through Electrophysiological Signal Analysis, Lecture Notes in Electrical Engineering, Springer Nature Singapore, 2024, https://doi.org/10.1007/978-981-99-7077-3_53

Publisher : Springer Nature Singapore

Year : 2021

A Review on Plant Stress Detection and Analysis Through Electrophysiological Signals

Cite this Research Publication : Kavya Sai, Neetu Sood, Indu Saini, A Review on Plant Stress Detection and Analysis Through Electrophysiological Signals, AIJR Proceedings, AIJR Publisher, 2021, https://doi.org/10.21467/proceedings.114.22

Publisher : AIJR Publisher

Journal Article

Year : 2024

Sorted sample- wavelet feature clustering based on the range for classification of multiple nutrient deficiencies in tomato plants

Cite this Research Publication : Kavya Sai, Neetu Sood, Indu Saini, Sorted sample- wavelet feature clustering based on the range for classification of multiple nutrient deficiencies in tomato plants, Computers and Electronics in Agriculture, Elsevier BV, 2024, https://doi.org/10.1016/j.compag.2024.109263

Publisher : Elsevier BV

Year : 2023

Time series data modelling for classification of drought in tomato plants

Cite this Research Publication : Kavya Sai, Neetu Sood, Indu Saini, Time series data modelling for classification of drought in tomato plants, Theoretical and Experimental Plant Physiology, Springer Science and Business Media LLC, 2023, https://doi.org/10.1007/s40626-023-00295-z

Publisher : Springer Science and Business Media LLC

Year : 2022

Classification of various nutrient deficiencies in tomato plants through electrophysiological signal decomposition and sample space reduction

Cite this Research Publication : Kavya Sai, Neetu Sood, Indu Saini, Classification of various nutrient deficiencies in tomato plants through electrophysiological signal decomposition and sample space reduction, Plant Physiology and Biochemistry, Elsevier BV, 2022, https://doi.org/10.1016/j.plaphy.2022.07.022

Publisher : Elsevier BV

Year : 2022

Abiotic stress classification through spectral analysis of enhanced electrophysiological signals of plants

Cite this Research Publication : Kavya Sai, Neetu Sood, Indu Saini, Abiotic stress classification through spectral analysis of enhanced electrophysiological signals of plants, Biosystems Engineering, Elsevier BV, 2022, https://doi.org/10.1016/j.biosystemseng.2022.04.025

Publisher : Elsevier BV

Research Interest

Plant electrophysiology- Bioelectric Signaling in Plant Stress Response, Spatiotemporal Mapping of Electrical Activity in Plants, Event Detection in Low-Amplitude Bioelectric Signals, Electrophysiological Signatures of Plant Development Stages, Electrochemical Interfaces for Long-Term Plant Monitoring, Cross-domain Signal Translation (e.g., Plant-to-Machine Interfaces), Multi-Modal Sensing of Plant Stress Responses, AI Models for Stress Classification Based on Plant Signals, Non-Invasive Stress Detection Using Remote Sensing and Bioelectric Monitoring, Physiological Modeling of Stress-Evoked Electrical Responses.

Speech Processing – Speech Biometrics and Speaker Identification, Cross-Lingual and Multilingual Speech Recognition, End-to-End Speech-to-Text Models with Attention Mechanisms, Emotion Recognition from Speech

Awards

Best paper award at International conference of Electrical, Electronics and Automation- springer

Admissions Apply Now