Prof. Lotfi Chaari | Artificial Intelligence | Best Researcher Award

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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 

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

 

Dr.Pouya Farshbaf Aghajani | Artificial Intelligence | Best Scholar Award

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Dr.Pouya Farshbaf Aghajani | Artificial Intelligence | Best Scholar Award  🏆

Master of Science at University of Tehran, Iran🎓

Pouya Farshbaf Aghajani is a Food Engineer specializing in food science, sustainable resource extraction, and innovative food safety technologies. He completed his Master’s in Food Engineering from the University of Tehran with the highest GPA in his class and holds a Bachelor’s degree in Biosystem Engineering from the University of Tabriz. Pouya has contributed to numerous research publications in food technology and advanced ultrasound applications, emphasizing resource efficiency and quality improvement.

Professional Profile 

🎓 Education

  • Master of Science in Food Engineering (Food Science and Chemistry) – University of Tehran (2020–2023)
    Ranked 1st, GPA: 3.54/4
    Thesis on ultrasound-assisted cultivation of Chlorella vulgaris for sustainable oil extraction.
  • Bachelor of Science in Biosystem Engineering (Food Engineering) – University of Tabriz (2016–2020)
    Ranked 4th in GPA

🏢 Work Experience

  • Scientific Research Association, University of Tehran – Teacher, offering training in international publications, software applications, and biomechanics.
  • ISI Journal Reviewer – Certified reviewer for journals like Food Chemistry, providing expert evaluations.
  • Assistant Editor-in-Chief – Frontiers in Food, Drug, and Natural Sciences, overseeing technical content.

🧬 Skills

  • Technical Skills: Proficient in SOLIDWORKS, SPSS, Python, MATLAB, and laboratory tools like GC, HPLC, SEM, and freeze dryers.
  • Soft Skills: Effective in teaching, team collaboration, time management, and problem-solving.

Awards and Honors 🏆

  • Ranked 1st among master’s students, University of Tehran (2021)
  • National graduate full scholarship, University of Tehran (2020)
  • Ranked in the top 10% among undergraduate students, University of Tabriz (2019)

📚 Teaching Experience

Instructor at the University of Tehran’s Scientific Research Association, teaching scientific writing, biomechanics applications, and English (IELTS-focused).

🔬 Research Focus

Pouya’s research centers on energy conservation, food safety, ultrasound technology, and artificial intelligence applications in food engineering. His work includes sustainable oil extraction, algae research, and quality assessment techniques aimed at improving food safety and processing efficiency.

Conclusion 

Pouya Farshbaf Aghajani is a strong candidate for the Best Scholar Award due to his academic excellence, impactful research, and dedication to advancing sustainable food engineering. With a demonstrated ability to innovate and lead, coupled with a commitment to teaching and mentorship, Pouya exemplifies the qualities of an outstanding scholar. Addressing areas for further growth, such as gaining international experience and expanding funding acquisition skills, would further solidify his scholarly influence. Nonetheless, his current achievements and strengths make him an excellent candidate for this prestigious award

📚 Publilcation 

  • “The Improvement of Freezing Time and Functional Quality of Frozen Mushrooms by Application of Probe-Type Power Ultrasound”
    • Year: 2023
    • Journal: Ultrasonics Sonochemistry
  • “Dual-Stage Ultrasound in Deep Frying of Potato Chips; Effects on the Oil Absorption and the Quality of Fried Chips”
    • Year: 2024
    • Journal: Ultrasonics Sonochemistry
  • “Revolutionizing Mushroom Identification: Improving Efficiency with Ultrasound-Assisted Frozen Sample Analysis and Deep Learning Techniques”
    • Year: 2024
    • Journal: Journal of Agriculture and Food Research
  • “Innovative Modifications to Zarrouk Medium for Enhanced Cultivation of Spirulina (Arthrospira Platensis)”
    • Year: 2024
    • Journal: Available at SSRN

Pritha N | Deep learning | Best Researcher Award

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Mrs Pritha N  | Deep learning  |  Best Researcher Award 

 

 

Assistant professor at  Panimalar Engineering College, India

 

👨‍🏫N. Pritha  With over 16.8 years of teaching experience, this dedicated educator specializes in Information and Communication Engineering. They hold a PhD from Anna University, Chennai.

Professional Profile:

🎓 Education:

🎓 PhD in Information and Communication Engineering, Anna University
🎓 M.E. in Applied Electronics, Sathyabama University (CGPA: 8.1)
🎓 B.E. in Electronics & Communication Engineering, Adhiparasakthi College of Engineering (76%)
🎓 Diploma in Electronics & Communication Engineering, Bakthavatchalam Polytechnic (83%)

💼 Work Experience:

  • 🏫 Lecturer at Adhiparasakthi College of Engineering (5.11 years)
    🏫 Assistant Professor (HOD Incharge) at John Bosco Engineering College (9 months)
    🏫 Assistant Professor at Panimalar Engineering College (10 years)

🏆 Awards and Honors:

🏅 2nd Topper in FDP on Embedded, IoT, AI, & HPC (2021)
🏅 5% Topper and Silver certification in NPTEL’s Machine Learning course (2023)

 

🔬 Research Focus:

N. Pritha’s research spans several critical areas in electronics and communication engineering. Her primary focus includes the design and optimization of RF and Microwave Engineering systems, exploring innovative techniques in Machine Learning, Deep Learning, and Artificial Neural Networks. She has contributed significantly to the development of multiband antennas for wireless applications, anomaly detection models in sensor networks, and enhancing the efficiency of digital multipliers like Wallace Tree and Dadda multipliers. Her work emphasizes low power, high-speed, and area-efficient solutions, contributing to advancements in embedded systems, IoT, and AI-driven applications.

Publications: