alain R THIERRY | Data Science and Deep Learning | Excellence in Research

Prof. alain R THIERRY  | Data Science and Deep Learning | Excellence in Research

Director of Research, INSERM U1194, France

Dr. alain R THIERRY, a distinguished biologist, and cancer researcher, is a Director of Research at INSERM and a key figure at the Institut de Recherche en Cancérologie de Montpellier. With an impressive track record in molecular biology, gene therapy, and cancer research, Dr. alain R THIERRY has held numerous influential positions in academia and the biotechnology sector, including roles at NIH and Georgetown University. A prolific author and scientific leader, they have also founded biotech companies like MedinCell and DiaDx. Dr. alain R THIERRYcontinues to drive innovative therapeutic solutions, recognized by international honors and awards.

Publication Profile

Education🎓 

2003: Habilitation à Diriger les Recherches (HDR) in Biology-Health, Université Montpellier II 1987: CES in Human Biology (Oncology), Faculté de Médecine Paris-Sud 1986: PhD in Biochemistry, Cellular & Molecular Pharmacology, Université Montpellier II 1983: MSc in Cellular & Molecular Biology, Université de Clermont-Ferrand II 1983: Diplôme d’Ingénieur, Université Clermont-Fd II 1982: BSc in Biological Sciences & Technology, Université Clermont-Fd

Professional Experience💼 

208-present: Director of Research, INSERM, Institut de Recherche en Cancérologie, Montpellier 2001-2007: Associate Professor, Université Montpellier II2003-2004: Director of R&D, MedinCell SA, Montpellier 1997-2000: Scientific Director, Gene Therapy Dept., Biovector Therapeutics 1992-1996: Scientist, Tumor Cell Biology Lab, NCI/NIH, Bethesda 1992-1994: Adjunct Assistant Professor, Lombardi Cancer Institute, Washington DC 1988-1992: Postdoctoral Fellow, Lombardi Cancer Center, Georgetown University

Awards and Honors🏆 

1994: Federal Technology Award, NIH, USA ($10,000) 2002: Prix National de l’Innovation, Ministry of Education and Research, Paris (€300,000) 2016: Grand Prix de l’Innovation Thérapeutique, Fondation B. Denys & FRM, Montpellier (€50,000) 2022: Finalist, Prix Innovation Unicancer 2022: Innovation Award, Montpellier Université Excellence

Research Focus 🔬 

Molecular Oncology: Pioneer in understanding the molecular pathways of cancer and therapeutic gene delivery Gene Therapy: Focus on targeted gene therapy to treat cancers, with expertise in vectors and delivery systems Circulating DNA: Breakthrough research in non-invasive biomarkers for early cancer detection
Therapeutics Innovation: Key developer of novel therapeutic strategies, including drug delivery systems and cancer diagnostics
Collaborative Research: Strong interdisciplinary collaborations in biotechnology and cancer research

Publication  Top Notes

  • Origins, structures, and functions of circulating DNA in oncology
    AR Thierry, S El Messaoudi, PB Gahan, P Anker, M Stroun
    Cancer and Metastasis Reviews, 2016 | 812 citations
  • Clinical validation of the detection of KRAS and BRAF mutations from circulating tumor DNA
    AR Thierry, F Mouliere, S El Messaoudi, C Mollevi, E Lopez-Crapez
    Nature Medicine, 2014 | 735 citations
  • Nomenclature for synthetic gene delivery systems
    PL Felgner, Y Barenholz, JP Behr, SH Cheng, P Cullis, L Huang, AR Thierry
    Human Gene Therapy, 1997 | 652 citations
  • High fragmentation characterizes tumour-derived circulating DNA
    F Mouliere, B Robert, E Arnau Peyrotte, M Del Rio, M Ychou, F Molina, AR Thierry
    PLOS One, 2011 | 627 citations
  • Circulating cell-free DNA: preanalytical considerations
    S El Messaoudi, F Rolet, F Mouliere, AR Thierry
    Clinica Chimica Acta, 2013 | 602 citations

Conclusion:

This individual is highly suitable for the Best Researcher Award. Their long-standing career in oncology research, leadership in both academic and biotech sectors, and recognition through awards place them in an elite category of researchers. Continued engagement in broader interdisciplinary fields and public communication could further elevate their profile. Overall, their qualifications, contributions, and leadership make them a strong candidate for excellence in research awards.

Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

Dr. Katarina Djordjevic, University of Belgrade, Serbia

Dr. Katarina Đorđević holds a PhD in Physics and is an expert in the physics of condensed matter and photoacoustics. She has significant experience in applying neural networks for material characterization, supervised machine learning, and solving inverse problems. Dr. Đorđević is skilled in numerical testing and developing measurement procedures, as well as utilizing computational intelligence algorithms in various applications. Her work involves a blend of theoretical and practical approaches, leveraging advanced computational techniques to enhance understanding and innovation in material sciences.

 

Professional Profiles:

Google Scholar

Intelligence 🚀

Dr. Katarina Đorđević, PhD in Physics, is a renowned expert with extensive experience in the physics of condensed matter, photoacoustics, and the application of neural networks in material characterization. Her diverse expertise spans multiple cutting-edge fields, making her a leading figure in both theoretical and applied physics.

🌟 Physics of Condensed Matter:

Dr. Đorđević’s work in condensed matter physics delves into the intricate properties of matter in various states, contributing to a deeper understanding of material behavior under different conditions.

🔊 Photoacoustics:

She is well-versed in photoacoustics, a technique that combines light and sound to probe the properties of materials. This innovative approach allows for non-invasive, highly precise material characterization.

🤖 Neural Networks & Material Characterization:

Leveraging neural networks, Dr. Đorđević has advanced the field of material characterization. Her research utilizes these artificial intelligence systems to analyze and predict material properties with unprecedented accuracy.

💻 Supervised Machine Learning:

A significant portion of her work involves supervised machine learning, where she trains models to recognize patterns and make predictions based on extensive datasets. This has vast applications in materials science and beyond.

🔄 Inverse Problem Solving:

Dr. Đorđević excels in solving inverse problems, which involve determining unknown causes from known consequences. This is crucial in many scientific and engineering disciplines, where direct measurement is challenging or impossible.

🔢 Numerical Testing & Measurement Procedures:

Her expertise extends to numerical testing and developing precise measurement procedures, ensuring accuracy and reliability in experimental physics.

🧠 Computational Intelligence Algorithms:

She applies advanced computational intelligence algorithms to tackle complex problems in physics and material science, driving innovation and efficiency in her research.Dr. Katarina Đorđević’s multidisciplinary approach and profound knowledge make her a standout scientist, continually pushing the boundaries of what is possible in physics and computational intelligence. 🌍🔬✨

📖 Publications Top Note :

1. Photoacoustic Measurements of the Thermal and Elastic Properties of n-type Silicon Using Neural Networks

Authors: КL Djordjević, DD Markushev, ŽМ Ćojbašić, KL Djordjević
Journal: Silicon 12 (6), 1289-1300, 2020
Citations: 21

2. Computationally Intelligent Description of a Photoacoustic Detector

Authors: MI Jordovic-Pavlovic, AD Kupusinac, KL Djordjevic, SP Galovic, …
Journal: Optical and Quantum Electronics 52, 1-14, 2020
Citations: 19

3. Development and Comparison of Techniques for Solving the Inverse Problem in Photoacoustic Characterization of Semiconductors

Authors: M Nesic, M Popovic, K Djordjevic, V Miletic, M Jordovic-Pavlovic, …
Journal: Optical and Quantum Electronics 53, 1-16, 2021
Citations: 17

4. Photoacoustic Optical Semiconductor Characterization Based on Machine Learning and Reverse-Back Procedure

Authors: КL Djordjevic, SP Galovic, MI Jordovic-Pavlovic, MV Nesic, MN Popovic, …
Journal: Optical and Quantum Electronics 52, 1-9, 2020
Citations: 16

5. Influence of Data Scaling and Normalization on Overall Neural Network Performances in Photoacoustics

Authors: КLj Djordjević, MI Jordović-Pavlović, ŽM Ćojbašić, SP Galović, MN Popović …
Journal: Optical and Quantum Electronics 54 (501), 31-35, 2022
Citations: 14*

6. Photothermal Response of Polymeric Materials Including Complex Heat Capacity

Authors: KL Djordjevic, D Milicevic, SP Galovic, E Suljovrujic, SK Jacimovski, …
Journal: International Journal of Thermophysics 43 (5), 68, 2022
Citations: 14

7. Estimation of Linear Expansion Coefficient and Thermal Diffusivity by Photoacoustic Numerical Self-Consistent Procedure

Authors: MV Nesic, MN Popovic, SP Galovic, KL Djordjevic, MI Jordovic-Pavlovic, …
Journal: Journal of Applied Physics 131 (10), 2022
Citations: 13

8. Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials

Authors: A Terzić, N Đorđević, M Mitrić, S Marković, K Đorđević, VB Pavlović
Journal: Science of Sintering 49 (1), 23-37, 2017
Citations: 13

9. Inverse Problem Solving in Semiconductor Photoacoustics by Neural Networks

Authors: KL Djordjevic, DD Markushev, ŽM Ćojbašić, SP Galović
Journal: Inverse Problems in Science and Engineering 29 (2), 248-262, 2021
Citations: 11

10. Use Neural Network in Photoacoustic Measurement of Thermoelastic Properties of Aluminum Foil

Authors: К Lj Djordjević, SP Galović, MN Popović, MV Nešić, IP Stanimirović, ZI …
Journal: Measurement, 111537, 2022
Citations: 10