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 Edinburgh Napier University’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 Edinburgh Napier University 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.

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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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52 results

Cognitively Inspired Feature Extraction and Speech Recognition for Automated Hearing Loss Testing

Journal Article
Nisar, S., Tariq, M., Adeel, A., Gogate, M., & Hussain, A. (2019)
Cognitively Inspired Feature Extraction and Speech Recognition for Automated Hearing Loss Testing. Cognitive Computation, 11(4), 489-502. https://doi.org/10.1007/s12559-018-9607-4
Hearing loss, a partial or total inability to hear, is one of the most commonly reported disabilities. A hearing test can be carried out by an audiologist to assess a patient’...

A novel deep learning driven, low-cost mobility prediction approach for 5G cellular networks: The case of the Control/Data Separation Architecture (CDSA)

Journal Article
Ozturk, M., Gogate, M., Onireti, O., Adeel, A., Hussain, A., & Imran, M. A. (2019)
A novel deep learning driven, low-cost mobility prediction approach for 5G cellular networks: The case of the Control/Data Separation Architecture (CDSA). Neurocomputing, 358, 479-489. https://doi.org/10.1016/j.neucom.2019.01.031
One of the fundamental goals of mobile networks is to enable uninterrupted access to wireless services without compromising the expected quality of service (QoS). This paper r...

DNN driven speaker independent audio-visual mask estimation for speech separation

Conference Proceeding
Gogate, M., Adeel, A., Marxer, R., Barker, J., & Hussain, A. (2018)
DNN driven speaker independent audio-visual mask estimation for speech separation. In Proceedings of the Annual Conference of the International Speech Communication Association (2723-2727). https://doi.org/10.21437/Interspeech.2018-2516

Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection

Conference Proceeding
Ieracitano, C., Adeel, A., Gogate, M., Dashtipour, K., Morabito, F., Larijani, H., …Hussain, A. (2018)
Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection. https://doi.org/10.1007/978-3-030-00563-4_74
Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology (ICT) systems. The extent of damage an individual hacker...

Exploiting Deep Learning for Persian Sentiment Analysis

Conference Proceeding
Dashtipour, K., Gogate, M., Adeel, A., Ieracitano, C., Larijani, H., & Hussain, A. (2018)
Exploiting Deep Learning for Persian Sentiment Analysis. In Advances in Brain Inspired Cognitive Systems. , (597-604). https://doi.org/10.1007/978-3-030-00563-4_58
The rise of social media is enabling people to freely express their opinions about products and services. The aim of sentiment analysis is to automatically determine subject’s...

A Survey on the Role of Wireless Sensor Networks and IoT in Disaster Management

Book Chapter
Adeel, A., Gogate, M., Farooq, S., Ieracitano, C., Dashtipour, K., Larijani, H., & Hussain, A. (2019)
A Survey on the Role of Wireless Sensor Networks and IoT in Disaster Management. In T. S. Durrani, W. Wang, & S. M. Forbes (Eds.), Geological Disaster Monitoring Based on Sensor Networks (57-66). Singapore: Springer. https://doi.org/10.1007/978-981-13-0992-2_5
Extreme events and disasters resulting from climate change or other ecological factors are difficult to predict and manage. Current limitations of state-of-the-art approaches ...

A comparative study of Persian sentiment analysis based on different feature combinations

Conference Proceeding
Dashtipour, K., Gogate, M., Adeel, A., Hussain, A., Alqarafi, A., & Durrani, T. (2019)
A comparative study of Persian sentiment analysis based on different feature combinations. https://doi.org/10.1007/978-981-10-6571-2_279
In recent years, the use of internet and correspondingly the number of online reviews, comments and opinions have increased significantly. It is indeed very difficult for huma...

Toward's Arabic multi-modal sentiment analysis

Conference Proceeding
Alqarafi, A., Adeel, A., Gogate, M., Dashitpour, K., Hussain, A., & Durrani, T. (2019)
Toward's Arabic multi-modal sentiment analysis. https://doi.org/10.1007/978-981-10-6571-2_290
In everyday life, people use internet to express and share opinions, facts, and sentiments about products and services. In addition, social media applications such as Facebook...

A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition

Conference Proceeding
Gogate, M., Adeel, A., & Hussain, A. (2018)
A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition. https://doi.org/10.1109/SSCI.2017.8285377
The curse of dimensionality is a well-established phenomenon. However, the properties of high dimensional data are often poorly understood and overlooked during the process of...

Deep learning driven multimodal fusion for automated deception detection

Conference Proceeding
Gogate, M., Adeel, A., & Hussain, A. (2018)
Deep learning driven multimodal fusion for automated deception detection. https://doi.org/10.1109/SSCI.2017.8285382
Humans ability to detect lies is no more accurate than chance according to the American Psychological Association. The state-of-the-art deception detection methods, such as de...

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