Kirti Kumari
Indian Institute of Information Technology Ranchi, Siksha O Anusandhan University Institute of Technical Education and Research
About
Kirti Kumari is currently working as an Assistant Professor in the Department of CSE, Indian Institute of Information Technology Ranchi, Jharkhand, India. Before joining IIIT Ranchi, she worked as an Assistant Professor in the Department of CSE at Siksha “O” Anusandhan Deemed to be University, Bhubaneswar, Odisha. She has obtained a Ph.D. degree in Computer Science & Engineering from the Department of CSE of the NIT Patna, India. Her research interests include machine learning, deep learning, natural language processing, and social networks. She has published articles in different Journals, including Soft Computing, Future Generation Computer Systems, Transaction of Emerging Telecommunication Technology, Mulitmedia Systems and Signal Image and Video Processing.
Employment
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Indian Institute of Information Technology Ranchi Assistant Professor2021 - Present
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Siksha O Anusandhan University Institute of Technical Education and Research Assistant Professor2020 - 2021
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (9)
- Lightweight emotion classification in Urdu: A multi-head attention and hybrid approach Save
- Multilabel Emotion Recognition in Urdu Using Attention-Based Hybrid Model and Fractional Order Backpropagation Save
- A fast and efficient large-scale near duplicate image retrieval system using double perceptual hashing Save
- Mobile Health Save
- Multi-modal cyber-aggression detection with feature optimization by firefly algorithm Save
- Bilingual Cyber-aggression detection on social media using LSTM autoencoder Save
- Multi-modal aggression identification using Convolutional Neural Network and Binary Particle Swarm Optimization Save
- Identification of cyberbullying on multi‐modal social media posts using genetic algorithm Save
- Towards Cyberbullying-free social media in smart cities: a unified multi-modal approach Save