Prof. Lotfi Chaari | Artificial Intelligence | Best Researcher Award

Institut National Polytechnique de Toulouse (Toulouse INP),France🎓

Dr. Lotfi Chaari is a distinguished French academic and researcher specializing in signal and image processing, artificial intelligence, and biomedical imaging. Currently a Full Professor at the Institut National Polytechnique de Toulouse (Toulouse INP), he also directs research initiatives at Ipst-Cnam and contributes to groundbreaking projects at the IRIT laboratory. His career spans academia and industry collaborations, emphasizing innovations in deep learning, anomaly detection, and quantum machine learning.

Professional Profile

ORCID

Education 🎓:

2017: Habilitation à Diriger la Recherche (HDR), Toulouse INP, France
2010: PhD in Signal and Image Processing, University of Paris-Est Marne-la-Vallée, France
2008: Master of Science in Telecommunication, SUP’COM, Tunisia
2007: Telecommunication Engineering Degree, SUP’COM, Tunisia

Work Experience 💼:

2024 – Present: Full Professor, Toulouse INP, France (Ipst-Cnam)
2012 – 2024: Associate Professor, Toulouse INP, France (Ipst-Cnam)
2010 – 2012: Post-doctoral Fellow, INRIA Grenoble-Rhône Alpes, France

Skills 🔍:

Artificial Intelligence & Machine Learning: Proficient in deep learning, anomaly detection, and Bayesian optimization.
Signal & Image Processing: Expertise in biomedical imaging, remote sensing, and pattern recognition.
Optimization: Skilled in variational and inverse problem-solving techniques for image enhancement and restoration.

Awards and Honors 🏆:

2023: HOPE Best Workshops Paper Award
2022: Nutrients Best Paper Award
2019: Elevated to IEEE Senior Member status

Memberships 🤝:

Editorial Positions: Associate Editor for Digital Signal Processing Journal and IEEE Open Journal of Signal Processing
Conference Leadership: Founder and General Chair, International Conference on Digital Health Technologies (ICDHT)
Technical Program Committee Member: Contributed to renowned conferences like IEEE ICIP, IEEE ICASSP, and ISIVC

Teaching Experience 👩‍🏫:

Dr. Chaari is a passionate educator who has developed advanced courses in signal processing, machine learning, and artificial intelligence. He actively supervises PhD students and promotes interdisciplinary research.

Research Focus 🔬:

Dr. Chaari’s research spans various cutting-edge fields, including biomedical signal processing, remote sensing, and anomaly detection. He has spearheaded multiple collaborative projects, such as MSrGB (Metabolic Shift in Radioresistance of Glioblastoma) and BayesQML (Bayesian Optimization for Quantum Machine Learning), pushing the boundaries of AI in medical and engineering applications.

Conclusion

Dr. Lotfi Chaari is an outstanding candidate for the Best Researcher Award. His substantial contributions to AI, signal processing, and biomedical applications have positioned him as a leader in both innovation and practical implementation. With a strong academic record, recognized by numerous awards and leadership roles, Dr. Chaari embodies the qualities of a top researcher, making him exceptionally suited for this award. Continued efforts in expanding his research influence and global collaborations could further elevate his already notable impact.

📚 Publilcation

Title: “mid-DeepLabv3+: A Novel Approach for Image Semantic Segmentation Applied to African Food Dietary Assessments”
Topic: Semantic segmentation for dietary assessments
Year: 2023
Journal: Sensors
DOI: 10.3390/s24010209
Title: “Non-smooth Bayesian learning for artificial neural networks”
Topic: Bayesian learning in neural networks
Year: 2022
Journal: Journal of Ambient Intelligence and Humanized Computing
DOI: 10.1007/s12652-022-04073-8
Title: “Bayesian Optimization Using Hamiltonian Dynamics for Sparse Artificial Neural Networks”
Topic: Bayesian optimization for sparse neural networks
Year: 2022
Conference: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
DOI: 10.1109/isbi52829.2022.9761469
Title: “A Convolutional Neural Network for Artifacts Detection in EEG Data”
Topic: CNN for detecting artifacts in EEG data
Year: 2022
Source: Lecture Notes in Networks and Systems
DOI: 10.1007/978-981-16-7618-5_1
Title: “Bayesian Optimization for Sparse Artificial Neural Networks: Application to Change Detection in Remote Sensing”
Topic: Bayesian optimization for sparse neural networks in remote sensing
Year: 2022
Source: Lecture Notes in Networks and Systems
DOI: 10.1007/978-981-16-7618-5_4
Title: “Efficient Bayesian Learning of Sparse Deep Artificial Neural Networks”
Topic: Bayesian learning in sparse deep neural networks
Year: 2022
Source: Lecture Notes in Computer Science
DOI: 10.1007/978-3-031-01333-1_7
Title: “Drowsiness Detection Using Joint EEG-ECG Data With Deep Learning”
Topic: Drowsiness detection using EEG and ECG data
Year: 2021
Conference: 2021 29th European Signal Processing Conference (EUSIPCO)
DOI: 10.23919/eusipco54536.2021.9616046

Mr Cicil Denny | AI and Machine Learning | Best Researcher Award

🌟 Cicil Melbin Denny J is a versatile Data Analyst with a strong background in Artificial Intelligence, Machine Learning, and Software Engineering. With hands-on experience in programming languages like Python, Java, C++, and JavaScript, and advanced skills in AI, ML, and Deep Learning frameworks such as PyTorch and TensorFlow, Cicil excels in tackling complex data problems. Notably, he led a research project on Semantic Segmentation for Underwater Imagery (SUIM), achieving an impressive mIoU of 84.83%, which was published in the prestigious “Results in Engineering” journal. Cicil’s technical prowess extends to data analytics tools like MySQL and NoSQL, and he is adept at using PowerBI and Tableau for business insights. His proficiency in network administration, cloud services (AWS, Azure, Google Cloud), and cybersecurity underlines his comprehensive skill set. Recognized for his problem-solving attitude and effective communication skills, Cicil is well-equipped to contribute to product analysis and support, making him a valuable asset in any tech-driven environment. 📊💡🤖

professional profile:

📚 Education:

B.Tech in CSE with specialization in Artificial Intelligence and Machine Learning, CGPA: 8.25 (Completed 6 Semesters)

Higher Education (2019-20): Mathematics, Biology, CGPA: 8.38

💼 Work Experience:

Research Internship at Vellore Institute of Technology, Chennai (May 2023 – July 2023)

Worked on Semantic Segmentation for Underwater Imagery (SUIM) using Swin Transformer, ConvMixer, and UNet architectures. Achieved mIoU metrics of 84.83% and published in “Results in Engineering” Journal – 2024 by Elsevier.

🔍 Skills:

Programming Languages: Python, Java, C++, C, JavaScript, PHP

Data Analytics: MySQL, NoSQL, PowerBI, Tableau

AI & ML: PyTorch, TensorFlow, Machine Learning, Deep Learning, Computer Vision

Software Engineering: DevOps, Software Design and Debugging, Test Development

Networking: TCP/IP, DNS, DHCP, VLANs, VPNs, Firewalls

Virtualization & Cloud: VMware, VirtualBox, AWS, Azure, Google Cloud

Other Tools: Jupyter Notebook, MATLAB, LTspice, CISCO, Unity Engine, MS Excel

🏆 Certifications:

TensorFlow Developer Certificate (2023: Zero to Mastery)

Deep Learning A-Z™ 2023: Neural Networks, AI & ChatGPT Bonus

Artificial Intelligence Analyst – IBM

Introduction to Artificial Intelligence – LinkedIn Learning

Artificial Intelligence – Verzeo

Introduction to Financial Modeling

Digital Marketing Fundamentals with Live Projects

The A-Z Digital Marketing Course

🔬 Research Focus:

🔬 Cicil Melbin Denny J’s research focuses on cutting-edge technologies in AI and Machine Learning. He has extensively worked on Semantic Segmentation for Underwater Imagery using advanced architectures like Swin Transformer, ConvMixer, and UNet, achieving high accuracy. His work on IoT botnet detection leverages autoencoders, LSTM-CNN, and DNN to enhance cybersecurity. Additionally, he explores route mapping algorithms, blockchain technology, and cryptocurrency trends. Cicil’s dedication to innovation is evident through his projects on malware detection using ML algorithms and IoT-based accident intimation systems, aiming to improve safety and security in various domains. 🌊🤖🔒🌐

👩‍🏫 Teaching & Knowledge Sharing:

Advanced skills in AI, ML, Deep Learning, and Computer Vision with hands-on experience.

Prepared detailed reports and suggested improvements on QA patterns for Amazon Warehouses.

publications🌟