Mohamed Lazhar Bellagha

Doctorate in Computer Science

About Me

Doctor of Computer Science specialized in Audio Information Retrieval, Speaker recognition, signal processing, natural language processing and deep learning.

Bio

Born on
September 6, 1992
Email
bellaghamohamed@gmail.com
Phone
+216 26003324
Address
Rue Ibn El Jazzar Monastir -5000.

Professional experiences

2022/2023
Contractual teacher at the Faculty of Sciences of Monastir. (Machine Learning)
2021/2022
Contractual teacher at the Faculty of Sciences of Monastir. (Machine Learning)
2020/2021
Contractual teacher at the Faculty of Sciences of Monastir. (C programming)
Current research Thesis:
The current research project focuses on Speaker identification and naming in Arabic news broadcasts. Automatic speaker identification is the problem of identifying speakers by their real identities. This is a fundamental task in high-level video analysis, such as semantic indexing and video summarisation, etc.
Master 2 research internship:
2017
we conducted a study on the evolution of different approaches for speaker diarization. As well as a detailed discussion of these approaches and their contributions. The results of this works led to the creation of a speaker diarization system, which automatically identifies "who speak and when" in an audio document.
Project Graduation:
2014
Development of a modeling and diagnostic application with Bayesian networks: a graphical interface for the BNT toolbox (Bayes net Toolbox for Matlab) to facilitate learning and inference tasks.

Education

Doctorate In Computer Science
2022
Earned a doctorate in computer science from the University of Sousse with a very honorable mention.
Masters in Automatic Reasoning Systems
2017
Research Master's Degree in Computer Science (Automatic Reasoning Systems), Faculty of Sciences of Monastir.
License
2014
License in Computer Science, Faculty of Sciences of Monastir.
Baccalaureate
2011
Baccalauréat en informatique, lycée secondaire Ibn mandhour.

Scientific publications

2022
Speaker Naming in Arabic TV programs. M.Bellagha, M.Zrigui; IAJIT 2022.
2021
Using the MGB-2 challenge data for creating a new multimodal Dataset for speaker role recognition in Arabic TV Broadcasts. M.Bellagha, M.Zrigui; kes 2021.
2020
Speaker Naming in TV programs Based on Speaker Role Recognition. M.Bellagha, M.Zrigui; Aiccsa 2020.
2017
Speaker Segmentation Using Adapted GMMs. M.Bellagha,M.Labidi, M.Maraoui. ICEMIS 2017.

TRAINING CERTIFICATE

Scrum Master Certification: by Jim Sullivan

Scrum Methodologies

Learn the foundational knowledge to become proficient with Agile Scrum; Explore User Stories and how they are prioritized in Agile, Velocity, Backlog Refinement, and Market Actions.

Deep Learning Specialization by Younes Bensouda Mourri

Natural Language Processing with Attention Models

Design NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot

Deep Learning Specialization by Andrew Ng

Structuring Machine Learning Projects

build a successful machine learning project and get to practice decision-making as a machine learning project leader.

Deep Learning Specialization by Andrew Ng

Neural Networks and Deep Learning

build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications.

Deep Learning Specialization by Andrew Ng

Sequence Models

build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering.

Deep Learning Specialization by Andrew Ng

Convolutional Neural Networks

build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data.

Machine learning in python with scikit-learn by inria

Machine learning

Deep Learning Specialization by Andrew Ng

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning...

Languages

Arabic
English
French

Others projects

Web:
creating an educational Website For Kids (www.4kidss.com)
Environment: Django / MySQL

Skills

Interest
Artificial intelligence, Bayesian networks, signal processing, Natural language processing, speech processing and deep learning.
Programming languages
c/c++, python, bash.
library
Pytorch, Scikit-learn, TensorFlow, Keras.
Computer clubs
Club de logiciels libres FSM
Web development with python
Django/ MySQl/ HTML/ CSS / Javascript

Contact

bellaghamohamed@gmail.com