Shakeel Ahmad Sheikh

Doctoral Student

Inria Research

Founder [Kashmir Guidance]






Knowledge knocks at the door of action: it enters if the door is opened, but leaves if it does not receive a reply ”.
[Imam Sufyan Al Thawri (RA)]



Software is Eating the World, but AI is Going to Eat Software
[Jensen Huang (CEO, Nvidia)]

My name is Shakeel Ahmad Sheikh and I belong to one of the most beautiful valleys on earth known as Kashmir. Currently I am pursuing my doctoral (PhD) studies in the MULTISPEECH Team of LORIA-INRIA, working on the thesis "Identifying Disfluency in Speakers with Stuttering, and its Rehabilitation, using Deep Learning" under the supervision of Prof Dr. Slim Ouni and Dr. Md Sahidullah at the Department of Informatics and Mathematics, Faculty of Sciences, Université De Lorraine, Nancy, France.

I did my MS from the Institute of Graduate Studies in Science & Engineering, Faculty of Sciences, Istanbul University in 2019 with the thesis title "Intelligent Clustering of Authentic Islamic Texts based on Contextual Similarity using Deep Learning Techniques". I also did my Master M1 Informatics from École Nationale Supérieure d'informatique et de Mathématiques Appliquées de Grenoble , (Grenoble INP-Université Grenoble Alpes) , France 2019. During my M1 Informatics at Grenoble INP Ensimag, I worked as a research internee in the Getalp Team of LIG lab under the supervision of Prof Dr. Laurent Besacier. During this research Internship, I worked on the project Neural Machine Translation (NMT) in Low Resource Setting Using Pre-Trained Contextual Embeddings (BERT EMBEDDINGS), OpenNMT-py-BERT.

I did my bachelors (B.Tech Computer Science & Engineering) from University of Kashmir, Srinagar in 2015.

You can contact me at my university e-mail address shakeel-ahmad.sheikh@loria.fr or at my personnel e-mail shakeelzmail608@gmail.com.

News

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Publications and Projects


Identifying Disfluency in Speakers with Stuttering, and its Rehabilitation, using Deep Learning

PhD Thesis (2019-2022), LORIA-INRIA, Universite De Lorraine

S.A.Sheikh, Identifying Disfluency in Speakers with Stuttering, and its Rehabilitation, using Deep Learning [Link]


Stuttering Detection Using Data Augmentation, Class-balanced Loss and Multi-contextual Deep Learning

Submitted to IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS

Shakeel.A.Sheikh, , Md Sahidullah, Fabrice Hirsch, Slim Ouni, [Preprint]


End-to-End and Self-Supervised Learning for ComParE 2022 Stuttering Sub-Challenge

Submitted to ACM Multimedia 2022

Shakeel.A.Sheikh, , Md Sahidullah, Fabrice Hirsch, Slim Ouni, [Preprint]


Robust Stuttering Detection via Multi-task and Adversarial Learning

Accepted in EUSIPCO 2022

Shakeel.A.Sheikh, , Md Sahidullah, Fabrice Hirsch, Slim Ouni, [Preprint]


Introducing ECAPA-TDNN and Wav2Vec2.0 Embeddings to Stuttering Detection

Submitted to IEEE SLT 2022

Shakeel.A.Sheikh, , Md Sahidullah, Fabrice Hirsch, Slim Ouni, [Preprint]


Machine Learning for Stuttering Identification: Review, Challenges & Future Directions

under review in Neural Networks

Shakeel.A.Sheikh, , Md Sahidullah, Fabrice Hirsch, Slim Ouni, [Preprint]


StutterNet: Stuttering Detection Using Time Delay Neural Network

Accepted in EUSIPCO 2021, Dublin, Ireland

Shakeel.A.Sheikh, , Md Sahidullah, Fabrice Hirsch, Slim Ouni, [StutterNet Paper], [Slides], [Video]


Neural Machine Translation (NMT) in Low Resource Setting Using Pre-Trained Contextual Embeddings (BERT)

Internship Project (2019), LIG Lab, Grenoble INP Ensimag- Universite De Grenoble

S.A.Sheikh, Neural Machine Translation (NMT) in Low Resource Setting Using Pre-Trained Contextual Embeddings (BERT) [Link]


Intelligent Text Clustering of Islamic Religious Texts Using Deep Learning Techniques

MS thesis (2019), University of Istanbul

S.A.Sheikh, Intelligent Text Clustering of Islamic Religious Texts Using Deep Learning Techniques [Link]


NachOS Operating System

NachOS v2.0, an improved version of the original NachOS.

S.A.Sheikh , J. Vazquez, E. Sanara, NachOS Operating System, improved version of the original NachOS Class Project [Report, Code (Git)].


Balloon Popping Robair, The Robair intelligently identifies balloons and pops them off.

Robair: Machine Learning Based Robot.

S.A.Sheikh , J. Vazquez, E. Sanara, C. Marshal, Balloon Popping Robair, The Robair intelligently identifies balloons and pops them off while avoiding the other things like walls, human legs etc Class Project [Demo, Code, Ppt ].


Text Embedding Techniques for Sentiment Analysis: A Review.

A Review on Deep Learning based Embeddings.

S.A.Sheikh , K.M.Shafi, Text Embedding Techniques for Sentiment Analysis: A Review .

Research Interests

Curriculum Vitae


Europe Diaries

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Paris

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Nancy

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Nancy

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France

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Paris

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Le Syndicat

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Old Prague

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Charles Bridge

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Dresden, Germany

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Prague

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Pahalgam, Kashmir

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Hamburg, Germany

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