Dr. Minh-Khang Le | Artificial Intelligence Awards | Best Researcher Award

Dr. Minh-Khang Le | Artificial Intelligence Awards | Best Researcher AwardΒ 

Dr. Minh-Khang Le, Cedars-Sinai Medical Center, United States

Minh-Khang Le, M.D., Ph.D., is a Postdoctoral Research Scientist in the Department of Pathology and Computational Biomedicine at Cedars-Sinai Medical Center in Los Angeles, California. He obtained his Doctor of Medicine degree from the University of Medicine and Pharmacy at Ho Chi Minh City, graduating in the top 10% of his class, and completed his Ph.D. in Pathology at the University of Yamanashi in Japan. His research focuses on integrating histopathology, molecular profiles, and clinicopathological features to characterize human cancers, particularly lymphoid and hematopoietic neoplasms. Dr. Le has contributed to several projects involving histopathology, molecular analyses, and the development of clinicopathological machine-learning models. As a strong advocate for the transformative potential of artificial intelligence in pathology, he aims to enhance the understanding and treatment of cancer. In addition to his postdoctoral position, he has held research roles at various institutions, including the University of Iowa Hospitals and Clinics and the University of Oklahoma Health Sciences Center. Dr. Le’s work has led to impactful advancements in digital pathology and cancer research.

Professional Profile:

SCOPUS

Researcher Suitability Summary for Best Researcher Award:Β 

Minh-Khang Le is an exemplary candidate for the Best Researcher Award, showcasing a profound commitment to advancing the field of digital pathology and computational biomedicine. His research is particularly focused on integrating histopathological and molecular profiles to enhance the understanding and characterization of human cancers, especially lymphoid and hematopoietic neoplasms. This multidisciplinary approach not only reflects his extensive knowledge but also his dedication to translating complex data into meaningful clinical insights.

Education πŸŽ“

  • Postdoctoral Research Scientist
    Cedars-Sinai Medical Center, Department of Computational Biomedicine and Pathology
    July 2024 – Present
    8700 Beverly Blvd, Los Angeles, CA, USA
  • Ph.D. Student
    University of Yamanashi, Department of Pathology
    April 2020 – March 2024
    GPA: 3.5/4.0
    1110 Shimokato, Chuo, Yamanashi, Japan
  • Doctor of Medicine
    University of Medicine and Pharmacy at Ho Chi Minh City
    October 2013 – September 2019
    Degree Classification: Good (Top 10% of the Course)
    Ho Chi Minh City, Vietnam

Work Experience πŸ’Ό

  • Postdoctoral Research Scientist
    Cedars-Sinai Medical Center, Department of Computational Biomedicine and Pathology
    July 2024 – Present
  • Part-time Researcher
    New Energy and Industrial Technology Development Organization (NEDO)
    April 2022 – Present
  • Part-time Researcher
    Department of Pathology, The University of Iowa Hospitals and Clinics, Iowa, USA
    April 2022 – Present
  • Research Assistant
    Department of Pathology, University of Yamanashi
    April 2020 – Present
  • Teaching Assistant
    Department of Pathology, University of Yamanashi
    April 2020 – Present
  • Part-time Researcher
    Department of Neurosurgery, The University of Oklahoma Health Sciences Center, Oklahoma, USA
    April 2021 – March 2022

Achievements, Awards, and Honors πŸ†

  • Top 10% of the Course in Doctor of Medicine program at the University of Medicine and Pharmacy at Ho Chi Minh City
  • GPA of 3.5/4.0 in Ph.D. studies at the University of Yamanashi

PublicationΒ Top Notes:

Clinical implication of PRAME immunohistochemistry in differentiating melanoma in situ and dysplastic nevus in non-acral nevus-associated melanoma in situ: An institutional experience and meta-analysis

A Novel Artificial Intelligence-Based Parameterization Approach of the Stromal Landscape in Merkel Cell Carcinoma: A Multi-Institutional Study

Comprehensive analysis of distinct circadian clock subtypes of adult diffuse glioma and their associations with clinicopathological, genetic, and epigenetic profiles

CXCL5 expression is associated with active signals of macrophages in the microenvironment of papillary thyroid carcinoma

Severe asthmatic airways have distinct circadian clock gene expression pattern associated with WNT signaling

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Dr. Akmal Jahan Mohamed Abdul Cader, South Eastern University, Sri Lanka.

Dr. Akmal Jahan Mohamed Abdul Cader is a distinguished academic and researcher currently serving as a Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka. With extensive experience in higher education, he is a Visiting Research Fellow at QUT, Australia. His research interests include artificial intelligence, data science, and document image analysis. Dr. Cader has published numerous high-impact articles and is actively involved in academic development and curriculum design. He is committed to advancing education and research in the field of computer science.Β πŸ“šπŸ’»πŸŒ

Publication ProfilesΒ 

Googlescholar

Education and Experience

  • Visiting Research FellowΒ – QUT Momentum Visiting Fellow, QUT, Australia (2021 – Present)Β πŸŽ“
  • Senior LecturerΒ (Computer Science) – South Eastern University of Sri Lanka (2020 – Present) 🏫
  • Sessional AcademicΒ – School of Electrical Engineering & Computer Science, QUT (2016 – 2019)Β πŸ“–
  • LecturerΒ (Computer Science) – South Eastern University of Sri Lanka (2012 – 2015)Β πŸ§‘β€πŸ«
  • Assistant LecturerΒ – South Eastern University of Sri Lanka (2010 – 2012)Β πŸ”
  • DemonstratorΒ in Computer Science – South Eastern University of Sri Lanka (2009 – 2010)Β πŸ‘¨β€πŸ”¬

Suitability For The Award

Dr. Mac Akmal Jahan Mohamed Abdul Cader, Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka, is a highly accomplished academic and researcher, making him an exemplary candidate for the Best Researcher Award. With a career spanning over a decade, Dr. Cader has consistently demonstrated leadership in research, teaching, and academic development, particularly in the fields of artificial intelligence, computer science, and digital technologies. His research contributions, coupled with his active involvement in academic service, professional organizations, and international collaborations, solidify his standing as a leading figure in his domain.

Professional Development

Dr. Cader has participated in several professional development programs focused on effective communication, teaching and learning, and project-based learning. He has completed various certifications at QUT, enhancing his skills in pedagogy and curriculum development. His commitment to continuous improvement in education is evident in his active engagement in workshops and training sessions aimed at promoting best practices in teaching. As a Fellow of the Higher Education Academy, he champions high standards in academic instruction and student engagement.Β πŸ…πŸ“ˆπŸ“š

Research Focus

Dr. Cader’s research primarily focuses on artificial intelligence, data science, and document image analysis. He explores the synthesis and application of synthetic metals, aiming to develop innovative solutions in electronics and energy storage. His work on TCNQ chemistry has significant implications for biotechnology and medicine, including the construction of electrochemical sensors and drug delivery systems. By synthesizing novel compounds, he contributes to advancements in both theoretical and practical aspects of computer science and materials research.Β πŸ”¬βš™οΈπŸŒ

Awards and Honors

  • Senate Honours Award for High Impact PublicationsΒ – SEUSL (2022 & 2023)Β πŸ†
  • Queensland University of Technology Postgraduate Award (QUTPRA)Β (2015)Β πŸ“œ
  • Faculty Write Up (FWU) ScholarshipΒ – QUT, Australia (2019)Β πŸ“š
  • Effective Communication in Teaching and LearningΒ – QUT, Australia (2019)Β πŸ—£οΈ
  • Foundation of Teaching and LearningΒ – QUT (2018)Β πŸŽ“

Publication Top NotesΒ 

  • Locating tables in scanned documents for reconstructing and republishingΒ | Cited by: 46 | Year: 2014Β πŸ“„πŸ”
  • Plagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14)Β | Cited by: 37 | Year: 2014Β πŸ“ŠβœοΈ
  • AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based AssignmentsΒ | Cited by: 34 | Year: 2014Β πŸ“„πŸ›‘οΈ
  • Plagiarism detection tools and techniques: A comprehensive surveyΒ | Cited by: 23 | Year: 2021Β πŸ”ŽπŸ“š
  • Fingerprint Systems: Sensors, Image Acquisition, Interoperability and ChallengesΒ | Cited by: 11 | Year: 2023Β πŸ–οΈπŸ“·
  • Contactless finger recognition using invariants from higher order spectra of ridge orientation profilesΒ | Cited by: 10 | Year: 2018Β βœ‹πŸ“
  • Accelerating text-based plagiarism detection using GPUsΒ | Cited by: 10 | Year: 2015Β βš‘πŸ’»
  • Contactless multiple finger segments based identity verification using information fusion from higher order spectral invariantsΒ | Cited by: 9 | Year: 2018Β πŸ–οΈπŸ”—