Mandar Gogate
mandar gogate

Dr. Mandar Gogate

Senior Research Fellow

 0131 455 4793

  M.Gogate@napier.ac.uk

  

Biography

Dr Mandar Gogate is an EPSRC Senior Research Fellow at Â鶹ÉçÇø’s ​School of Computing, Engineering & built Environment specialising in real-time multimodal speech enhancement, signal processing, machine learning and artificial intelligence. Mandar graduated with a B.Eng (highest 1st Class Honours with distinction) in Electrical and Electronic Engineering at India’s top Birla Institute of Technology & Science, Pilani. He was awarded a PhD degree in Computing Science by Â鶹ÉçÇø in 2020.

Previously, he worked as an invited Research Scientist at Amazon and ENSTA ParisTech - École Nationale Supérieure de Techniques Avancées, Paris, France where he researched multimodal robotic sensor fusion technologies, incremental learning and dynamic advertising. He has also been an invited visiting research fellow at Sonova AG (Switzerland), Academia Sinica (Taiwan), MIT (Synthetic Intelligence Lab), and University of Oxford (Computational Neuroscience Lab).

His research interests are interdisciplinary, and include: real-time audio-visual enhancement, multimodal sensor fusion, incremental learning, natural language processing, computer vision, sentiment and emotion analysis, privacy-preserving machine learning, explainable artificial intelligence, IoT, wireless sensing and 5G communications. Real-world applications range from cognitive robotics and assistive healthcare technologies to ​​automated social media analytics for security, business intelligence and industry 4.0.

School

Research Groups

Research Areas

Esteem

Conference Organising Activity

  • 2024 Interspeech Conference: International Satellite Workshop on the 3rd COG-MHEAR Audio-Visual Speech Enhancement Challenge, 1 Sep 2024, Greece

 

Spin-outs and Licences

  • Patent: Deep Cognitive Neural Network (DCNN)

 

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70 results

Pruning Deep Neural Networks for Green Energy-Efficient Models: A Survey

Journal Article
Tmamna, J., Ayed, E. B., Fourati, R., Gogate, M., Arslan, T., Hussain, A., & Ayed, M. B. (2024)
Pruning Deep Neural Networks for Green Energy-Efficient Models: A Survey. Cognitive Computation, 16, 2931–2952. https://doi.org/10.1007/s12559-024-10313-0
Over the past few years, larger and deeper neural network models, particularly convolutional neural networks (CNNs), have consistently advanced state-of-the-art performance ac...

DDformer: Dimension decomposition transformer with semi-supervised learning for underwater image enhancement

Journal Article
Gao, Z., Yang, J., Jiang, F., Jiao, X., Dashtipour, K., Gogate, M., & Hussain, A. (2024)
DDformer: Dimension decomposition transformer with semi-supervised learning for underwater image enhancement. Knowledge-Based Systems, 297, Article 111977. https://doi.org/10.1016/j.knosys.2024.111977
Vision-guided Autonomous Underwater Vehicles (AUVs) have gradually become significant tools for human exploration of the ocean. However, distorted images severely limit the vi...

Impact of the Covid-19 pandemic on audiology service delivery: Observational study of the role of social media in patient communication

Journal Article
The Covid-19 pandemic has highlighted an era in hearing health care that necessitates a comprehensive rethinking of audiology service delivery. There has been a significant in...

Statistical Downscaling Modeling for Temperature Prediction

Book Chapter
Ashraf, Z., Kanwal, B., Hussain, I., Dashtipour, K., Gogate, M., & Kanwal, S. (2024)
Statistical Downscaling Modeling for Temperature Prediction. In W. Boulila, J. Ahmad, A. Koubaa, M. Driss, & I. Riadh Farah (Eds.), Decision Making and Security Risk Management for IoT Environments (147-169). Springer. https://doi.org/10.1007/978-3-031-47590-0_8
The application compares the Statistical Downscaling Model (SDSM) and partial least square (PLS) to bridge the gap between (minimum and maximum) daily temperatures of 11 sites...

Federated Learning for Market Surveillance

Book Chapter
Song, P., Kanwal, S., Dashtipour, K., & Gogate, M. (2024)
Federated Learning for Market Surveillance. In W. Boulila, J. Ahmad, A. Koubaa, M. Driss, & I. Riadh Farah (Eds.), Decision Making and Security Risk Management for IoT Environments (199-218). Springer. https://doi.org/10.1007/978-3-031-47590-0_10
The data utilized in market surveillance is highly sensitive; what may be available for machine learning is limited. In this paper, we examine how federated learning for time ...

Multivariate Procedure for Modeling and Prediction of Temperature in Punjab, Pakistan

Book Chapter
Kanwal, B., Ashraf, Z., Mehmood, T., Kanwal, S., Dashtipour, K., & Gogate, M. (2024)
Multivariate Procedure for Modeling and Prediction of Temperature in Punjab, Pakistan. In W. Boulila, J. Ahmad, A. Koubaa, M. Driss, & I. Riadh Farah (Eds.), Decision Making and Security Risk Management for IoT Environments (99-124). Springer. https://doi.org/10.1007/978-3-031-47590-0_6
Climate study often relies upon global climate models (GCM) to project future scenarios of change in climate behavior. This study aims to refine GCM results to fill the gap be...

Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN

Journal Article
The human auditory cortex contextually integrates audio-visual (AV) cues to better understand speech in a cocktail party situation. Recent studies have shown that AV speech en...

Application for Real-time Audio-Visual Speech Enhancement

Presentation / Conference Contribution
Gogate, M., Dashtipour, K., & Hussain, A. (2023, August)
Application for Real-time Audio-Visual Speech Enhancement. Presented at Interspeech 2023, Dublin, Ireland
This short paper demonstrates a first of its kind audio-visual (AV) speech enhancement (SE) desktop application that isolates, in real-time, the voice of a target speaker from...

5G-IoT Cloud based Demonstration of Real-Time Audio-Visual Speech Enhancement for Multimodal Hearing-aids

Presentation / Conference Contribution
Gupta, A., Bishnu, A., Gogate, M., Dashtipour, K., Arslan, T., Adeel, A., Hussain, A., Ratnarajah, T., & Sellathurai, M. (2023, August)
5G-IoT Cloud based Demonstration of Real-Time Audio-Visual Speech Enhancement for Multimodal Hearing-aids. Presented at Interspeech 2023, Dublin, Ireland
Over twenty percent of the world's population suffers from some form of hearing loss, making it one of the most significant public health challenges. Current hearing aids comm...

A hybrid dependency-based approach for Urdu sentiment analysis

Journal Article
In the digital age, social media has emerged as a significant platform, generating a vast amount of raw data daily. This data reflects the opinions of individuals from diverse...

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