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Career

· Assistant Professor, Shyama Prasad Mukherjee College (Current)2025–
· Master's degree, Economics, 7.2 CGPA, Chaudhary Charan Singh University2018–2020
· Bachelor of Arts - BA, Economics & Business Laws, 7.4 CGPA, Delhi University2015–2018

Publications (17)

Speech Emotion Recognition Using Spectrogram & Phoneme Embedding
Interspeech · 2018
151
cited
Deep Learning based Emotion Recognition System Using Speech Features and Transcriptions
arXiv.org · 2019
61
cited
Deceptive Reviews Detection Using Deep Learning Techniques
International Conference on Applications of Natural Language to Data Bases · 2019
41
cited
Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition
arXiv.org · 2019
14
cited
Addressing Unseen Word Problem in Text Classification
International Conference on Applications of Natural Language to Data Bases · 2018
13
cited
Anomaly Detection in Mobile Networks
2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW) · 2020
13
cited
Bidirectional Transformer Based Multi-Task Learning for Natural Language Understanding
International Conference on Applications of Natural Language to Data Bases · 2019
10
cited
Emoception: An Inception Inspired Efficient Speech Emotion Recognition Network
Automatic Speech Recognition & Understanding · 2019
8
cited
Learning Discriminative features using Center Loss and Reconstruction as Regularizer for Speech Emotion Recognition
AffComp@IJCAI · 2019
8
cited
Exploiting SIFT Descriptor for Rotation Invariant Convolutional Neural Network
IEEE India Conference · 2018
5
cited
From Fully Supervised to Zero Shot Settings for Twitter Hashtag Recommendation
arXiv.org · 2019
5
cited
MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation
arXiv.org · 2019
3
cited
EndTimes at SemEval-2021 Task 7: Detecting and Rating Humor and Offense with BERT and Ensembles
International Workshop on Semantic Evaluation · 2021
1
cited
Semantic Slot Prediction on low corpus data using finite user defined list
ICON · 2020
1
cited
ICNN: INPUT-CONDITIONED FEATURE REPRESENTATION LEARNING FOR TRANSFORMATION-INVARIANT NEURAL NETWORK
2019
Input-conditioned convolution filters for feature learning
Advances in Mobile Multimedia · 2020
Visual Context-aware Convolution Filters for Transformation-invariant Neural Network
arXiv.org · 2019
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