Dr. Razvan Pirloaga | Spectral Imaging | Best Researcher Award

Dr. Razvan Pirloaga | Spectral Imaging | Best Researcher Awardย 

Dr. Razvan Pirloaga, National Institute of Research and Development for Optoelectronics INOE, Romania

Razvanโ€“Gabriel Pรฎrloagฤƒ, is a research scientist specializing in remote sensing. He is currently affiliated with the National Institute of Research & Development for Optoelectronics in Mฤƒgurele, Romania, where he has been working since 2018. Previously, he served as a junior researcher at the Institute of Geodynamics in Bucharest. Razvan holds a Ph.D. in Physics from the University of Bucharest, focusing on cloud studies using passive and active remote sensing techniques. His academic journey also includes a Masterโ€™s degree in Physics, where he studied the connection between temperature variation and solar activity, and a Bachelor’s degree in Science, focusing on aerosol loading in the atmosphere. Proficient in English, he has expertise in Microsoft Office, R, LaTeX, and Python. Outside of academia, he is an avid snowboarder, motorcycle enthusiast, and sports fan, with a passion for football, tennis, and table tennis.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Razvan-Gabriel Pรฎrloagฤƒ is a highly suitable candidate for the Best Researcher Award based on his extensive research experience and academic background in remote sensing and atmospheric studies. With over a decade of work in research institutions, including his current role as a Research Scientist at the National Institute of Research & Development for Optoelectronics, he has demonstrated expertise in cloud studies, aerosol analysis, and environmental monitoring.

๐ŸŽ“ Education

  • Ph.D. in Physics (2019โ€“2024) โ€“ The University of Bucharest, Romania
    ๐Ÿ“Œ Thesis: “Contributions to cloud studies using a synergy between passive and active remote-sensing”
    ๐ŸŽ“ Scientific Coordinators: Dr. Bogdan Antonescu, Prof. Dr. Sabina ศ˜tefan

  • Masterโ€™s Degree in Physics (2013โ€“2015) โ€“ The University of Bucharest, Romania
    ๐Ÿ“Œ Thesis: “Connection between long-term variation of annual temperature and solar activity on mid-latitudes of the Northern Hemisphere”
    ๐ŸŽ“ Scientific Coordinators: Prof. Dr. Sabina ศ˜tefan, Dr. Venera Dobricฤƒ

  • Bachelorโ€™s Degree in Science (2009โ€“2012) โ€“ The University of Bucharest, Romania
    ๐Ÿ“Œ Thesis: “Determination of aerosol loading of the atmosphere using remote sensing”
    ๐ŸŽ“ Scientific Coordinator: Prof. Dr. Sabina ศ˜tefan

๐Ÿ’ผ Work Experience

  • Research Scientist (Oct 2023 โ€“ Present)
    ๐Ÿ“Œ National Institute of Research & Development for Optoelectronics, Romania
    ๐Ÿ”ฌ Remote Sensing Department

  • Junior Researcher (July 2018 โ€“ Sept 2023)
    ๐Ÿ“Œ National Institute of Research & Development for Optoelectronics, Romania
    ๐Ÿ”ฌ Remote Sensing Department

  • Junior Researcher (March 2013 โ€“ June 2018)
    ๐Ÿ“Œ Institute of Geodynamics, Romania
    ๐ŸŒ Natural Fields Department

๐Ÿ† Achievements, Awards & Honors

  • ๐Ÿ“œ Published Research in Remote Sensing, Cloud Studies, and Aerosol Analysis
  • ๐Ÿ… Certificate of Proficiency in English (C2) โ€“ No. 26058/18.07.2019
  • ๐Ÿ›ฐ๏ธ Contributions to Remote Sensing & Atmospheric Science through Ph.D. research
  • ๐Ÿ“– Scientific Contributions under renowned mentors in atmospheric physics

Publicationย Top Notes:

An Overview of the ASKOS Campaign in Cabo Verde

Ground-Based Measurements of Wind and Turbulence at Bucharestโ€“Mฤƒgurele: First Results

Ground-Based Measurements of Cloud Properties at the Bucharestโ€“Mฤƒgurele Cloudnet Station: First Results

Population Bias on Tornado Reports in Europe

Prof. Kristen Meiburger | Muscle Sonography | Best Researcher Award

Prof. Kristen Meiburger | Muscle Sonography | Best Researcher Awardย 

Prof. Kristen Meiburger, Politecnico di Torino, Italy

Dr. Kristen M. Meiburger is an Associate Professor of Biomedical Engineering at the Department of Electronics and Telecommunications, Politecnico di Torino, Italy, a position she has held since February 2025. She earned her Masterโ€™s Degree in Biomedical Engineering from Politecnico di Torino in 2010, followed by a Ph.D. in Biomedical Engineering in 2014 from the Scuola Interpolitecnica di Dottorato at the same institution. Over the years, she has progressed through various academic roles, including Research Assistant, Postdoctoral Researcher, and Tenure-track Assistant Professor. Her research primarily focuses on ultrasound imaging, biomedical signal processing, and computational modeling in biomedical engineering. Dr. Meiburger has actively contributed to international research collaborations, including serving as a Visiting Ph.D. Student at the University of Texas at Austin and a Visiting Researcher at the University of Toronto. She is a member of the IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (UFFC) and the IEEE Engineering in Medicine and Biology Society (EMBS). Her contributions have been recognized with several prestigious awards, such as the Gruppo Nazionale di Bioingegneria (GNB) Masterโ€™s Thesis Award and the Politecnico di Torino Ph.D. Quality Award.

Professional Profile:

ORCID

Suitability of Dr. Kristen M. Meiburger for the Best Researcher Award

Dr. Kristen M. Meiburger is an accomplished biomedical engineer specializing in ultrasound imaging, biophotonics, and medical image processing. Her research contributions, international collaborations, and prestigious academic trajectory position her as a strong candidate for the Best Researcher Award. Below are key factors supporting her nomination.

๐ŸŽ“ Education & Work Experience

  • 2010 โ€“ Masterโ€™s Degree in Biomedical Engineering, Politecnico di Torino ๐Ÿ‡ฎ๐Ÿ‡น
  • 2011 (Jan โ€“ Dec) โ€“ Research Assistant in Biomedical Engineering, Politecnico di Torino ๐Ÿ”ฌ
  • 2012 (Jan) โ€“ 2014 (Dec) โ€“ Ph.D. in Biomedical Engineering, Scuola Interpolitecnica di Dottorato, Politecnico di Torino ๐ŸŽ“
  • 2013 (Oct) โ€“ 2014 (Apr) โ€“ Visiting Ph.D. Student, Ultrasound Imaging & Therapeutics Lab, University of Texas at Austin ๐Ÿ‡บ๐Ÿ‡ธ
  • 2015 (Jan โ€“ Mar) โ€“ Scholarship Holder in Biomedical Engineering, Politecnico di Torino ๐ŸŽ–๏ธ
  • 2015 (Apr โ€“ May, Aug โ€“ Sep) โ€“ Visiting Researcher, Biomedical Simulation Lab, University of Toronto ๐Ÿ‡จ๐Ÿ‡ฆ
  • 2016 (Mar) โ€“ 2018 (July) โ€“ Post-Doc Research Assistant in Biomedical Engineering, Politecnico di Torino ๐Ÿ”
  • 2018 (July) โ€“ 2021 (Dec) โ€“ Non-Tenure-Track Assistant Professor in Biomedical Engineering, Politecnico di Torino ๐Ÿ‘ฉโ€๐Ÿซ
  • 2021 (Dec) โ€“ 2022 (Jan) โ€“ Research Assistant in Biomedical Engineering, Politecnico di Torino ๐Ÿ”ฌ
  • 2022 (Feb) โ€“ 2025 (Jan) โ€“ Tenure-Track Assistant Professor, Politecnico di Torino ๐Ÿ“š
  • 2025 (Feb โ€“ Present) โ€“ Associate Professor of Biomedical Engineering, Politecnico di Torino ๐Ÿ›๏ธ

๐Ÿ† Achievements & Recognitions

  • Published and presented research at multiple national and international conferences ๐ŸŒ
  • Contributed significantly to ultrasound imaging and biomedical research ๐Ÿ“Š
  • Played an active role in international research collaborations with universities in the U.S. ๐Ÿ‡บ๐Ÿ‡ธ and Canada ๐Ÿ‡จ๐Ÿ‡ฆ

๐ŸŽ– Awards & Honors

  • ๐Ÿ… IEEE Memberships โ€“ Member of IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (UFFC) & IEEE Engineering in Medicine and Biology Society (EMBS)
  • ๐Ÿ† Masterโ€™s Thesis Award โ€“ Awarded by Gruppo Nazionale di Bioingegneria (GNB)
  • ๐Ÿฅ‡ Ph.D. Quality Award โ€“ Recognized by Politecnico di Torino for outstanding research work

Publicationย Top Notes:

CAROTIDNet: A Novel Carotid Symptomatic/Asymptomatic Plaque Detection System Using CNN-Based Tangent Optimization Algorithm in B-Mode Ultrasound Images

Softmax-Driven Active Shape Model for Segmenting Crowded Objects in Digital Pathology Images

Generative models for color normalization in digital pathology and dermatology: Advancing the learning paradigm

Segmentation and Multi-Timepoint Tracking of 3D Cancer Organoids from Optical Coherence Tomography Images Using Deep Neural Networks

Impact of artificial intelligenceโ€based color constancy on dermoscopical assessment of skin lesions: A comparative study