Natacha Esber | Syndrome | Top Researcher Award

Dr. Natacha Esber | Syndrome | Top Researcher Award

Science And Research Director at KAT6 Foundation, United States

Dr. Natacha Esber is a board-certified Internal Medicine physician with extensive clinical, academic, and research experience across the United States. With a career spanning over two decades, she has served in key roles in federal healthcare services, academia, and nonprofit scientific leadership. As Co-Founder and Science and Research Director of the KAT6 Foundation, Dr. Esber is an internationally recognized advocate and researcher in the field of rare genetic disorders, particularly KAT6A/KAT6B syndromes. She currently holds appointments with the Veterans Health Administration and ICE Health Service Corps and serves as an Adjunct Clinical Assistant Professor at Touro College of Osteopathic Medicine.

🔹Professional Profile:

Scopus Profile

🎓Education Background

  • Doctor of Medicine (MD) – Saint Joseph University, Beirut, Lebanon (1997–2004)
  • Internal Medicine/Infectious Diseases Residency – Saint Joseph University, Lebanon (2004–2007)
  • Internal Medicine Residency (PGY1) – University of Kansas School of Medicine, Wichita, KS (2008–2009)
  • Internal Medicine Residency (PGY2–3) – Memorial Hospital of Rhode Island, Brown University (2009–2011)

💼 Professional Development

Dr. Esber has served as an Internal Medicine Physician and Clinical Director for multiple federal contractors, including STG International, InGenesis, and SI2, providing care across ICE Health Service Corps and Veterans Health Administration centers in New York and New Jersey. Since 2017, she has led research for the KAT6 Foundation, advancing epigenetic understanding of neurodevelopmental disorders. Her prior hospitalist roles include appointments at Hackensack UMC at Pascack Valley, Englewood Hospital, Women and Infants Hospital, and Kent Hospital. Dr. Esber has consistently combined frontline clinical care with strategic leadership and academic mentoring.

🔬Research Focus

Dr. Esber’s research focuses on genetic neurodevelopmental disorders, epigenetics, histone modification, DNA methylation episignatures, and translational diagnostics. Her leadership in rare disease research aims to bridge molecular insights with clinical application for underserved conditions such as KAT6A syndrome.

📈Author Metrics:

  • First and co-author of peer-reviewed articles in journals including Science AdvancesEpigenomicsHuman MutationHuman Genetics and Genomics Advances, and DNA.
  • Notable citations for work on DNA methylation biomarkers and chromatin remodeling in neurodevelopmental disorders.
  • Contributor to National Organization for Rare Disorders (NORD) reviews and clinical references.

🏆Awards and Honors:

  • Senior Resident of the Year (2011) – Memorial Hospital of Rhode Island, Brown University
  • Contributor to multiple high-impact publications in epigenetics and neurodevelopment
  • Certified ICD-10 Consultant and holder of multiple active state medical licenses (NY, NJ, PA)

📝Publication Top Notes

1. Research Themes in KAT6A Syndrome: A Scoping Review
Authors: Tripathy T, St John M, Wright J, Esber N, Amor DJ
Journal: DNA, 5(2):21
DOI: https://doi.org/10.3390/dna5020021
Published: April 27, 2025
Citation:
Tripathy, T., St John, M., Wright, J., Esber, N., & Amor, D.J. (2025). Research Themes in KAT6A Syndrome: A Scoping Review. DNA, 5(2), 21. https://doi.org/10.3390/dna50200212. DNA Methylation Episignatures are Sensitive and Specific Biomarkers for Detection of Patients with KAT6A/KAT6B VariantsAuthors: Vos N, Reilly J, Elting M.W., Esber N, Alders M.M., Sadikovic B
Journal: Epigenomics, 15(6):351–367
DOI: 10.2217/epi-2023-0079
Citation:
Vos, N., Reilly, J., Elting, M.W., Esber, N., Alders, M.M., & Sadikovic, B. (2023). DNA methylation episignatures are sensitive and specific biomarkers for detection of patients with KAT6A/KAT6B variants. Epigenomics, 15(6), 351–367. https://doi.org/10.2217/epi-2023-00793. Functional Correlation of Genome-wide DNA Methylation Profiles in Genetic Neurodevelopmental Disorders

Authors: Levy M.A., Relator R., McConkey H., Esber N, et al.
Journal: Human Mutation, 43(11):1609–1628
DOI: 10.1002/humu.24446
Citation:
Levy, M.A., Relator, R., McConkey, H., Esber, N., et al. (2022). Functional correlation of genome-wide DNA methylation profiles in genetic neurodevelopmental disorders. Human Mutation, 43(11), 1609–1628. https://doi.org/10.1002/humu.24446

4. Novel Diagnostic DNA Methylation Episignatures Expand and Refine the Epigenetic Landscapes of Mendelian Disorders

Authors: Levy M.A., Relator R., Esber N, McConkey H., et al.
Journal: Human Genetics and Genomics Advances, 3(1):100075
DOI: 10.1016/j.xhgg.2021.100075
Citation:
Levy, M.A., Relator, R., Esber, N., McConkey, H., et al. (2022). Novel diagnostic DNA methylation episignatures expand and refine the epigenetic landscapes of Mendelian disorders. Human Genetics and Genomics Advances, 3(1), 100075. https://doi.org/10.1016/j.xhgg.2021.100075

5. Deficient Histone H3 Propionylation by BRPF1-KAT6 Complexes in Neurodevelopmental Disorders and Cancer

Authors: Yang X.J., Esber N, et al.
Journal: Science Advances, 6(4):eaax0021
DOI: 10.1126/sciadv.aax0021
Citation:
Yang, X.J., Esber, N., et al. (2020). Deficient histone H3 propionylation by BRPF1-KAT6 complexes in neurodevelopmental disorders and cancer. Science Advances, 6(4), eaax0021. https://doi.org/10.1126/sciadv.aax0021

Conclusion:

Dr. Natacha Esber is highly deserving of the Top Researcher Award based on:

  • Her pioneering role in epigenetic diagnostics of neurodevelopmental syndromes,
  • A strong scholarly record in reputable journals,
  • Foundational contributions to understanding and supporting KAT6-related disorders,
  • And her unique blend of clinical, academic, and nonprofit leadership.

Verdict: Strongly Recommended
Her career exemplifies the mission of translational science—transforming molecular discovery into clinical benefit, especially for marginalized populations. Recognizing her with a Top Researcher Award would be both timely and well-justified.

Shurun Wang | Brain function connectivity analysis | Best Researcher Award

Dr. Shurun Wang | Brain function connectivity analysis | Best Researcher Award

Postdoctoral researcher at  University of Science and Technology, China📝

Dr. Shurun Wang is a postdoctoral researcher at the School of Information Science and Technology, University of Science and Technology of China (USTC), specializing in biomedical signal analysis and brain function connectivity analysis. He holds a Ph.D. from the School of Electrical Engineering and Automation, Hefei University of Technology, where he also earned his MSc and BSc degrees. Dr. Wang has actively contributed to academic research and is passionate about advancing understanding in brain connectivity and biomedical systems through his work. He has received several prestigious awards, including the National Scholarship for Doctoral Students and the Outstanding Doctoral Dissertation Award from the Anhui Province Robotics Society.

Profile    

Orcid Profile

Google Scholar Profile 

Education 🎓

Dr. Shurun Wang has a robust academic background in Electrical Engineering and Automation. He completed his Ph.D. at the School of Electrical Engineering and Automation, Hefei University of Technology, in Hefei, China, from 2019 to 2024, where he specialized in biomedical signal analysis and brain function connectivity. During his doctoral studies, he also had the opportunity to enhance his research through a one-year visiting student program at the Graduate School of Medicine, Juntendo University, Tokyo, Japan, from April 2023 to April 2024. Prior to his Ph.D., Dr. Wang earned both his M.Sc. (2016–2019) and B.Sc. (2012–2016) degrees in Electrical Engineering and Automation, also from Hefei University of Technology, where he gained a strong foundation in electrical systems and automation technologies.

Professional Experience 💼

Dr. Shurun Wang is currently a Postdoctoral Researcher at the School of Information Science and Technology, University of Science and Technology of China (USTC), where he conducts cutting-edge research in biomedical signal analysis and brain function connectivity analysis. Prior to his postdoctoral role, he completed his Ph.D. at the School of Electrical Engineering and Automation, Hefei University of Technology. During his doctoral studies, Dr. Wang also undertook a one-year research stint as a visiting student at the Graduate School of Medicine, Juntendo University, Tokyo, Japan.

Research Interests 🔬

Dr. Wang’s primary research interests lie in biomedical signal analysis, particularly focusing on brain function connectivity. His work aims to develop advanced computational techniques to enhance the understanding of neural systems and brain activity patterns. This research is vital for applications in medical diagnostics, neuroengineering, and cognitive neuroscience, with potential contributions to improving treatments for neurological disorders and enhancing brain-machine interfaces.

Author Metrics 🏆

Dr. Wang has published extensively in top-tier journals and conferences, contributing to the fields of biomedical signal processing and neural networks. His work has gained recognition for its innovation and impact on both theoretical advancements and practical applications.

Awards and Recognition 🏆

  • National Scholarship for Doctoral Students
  • Outstanding Doctoral Dissertation Award from Anhui Province Robotics Society
  • Xplore New Automation Award 2018 of PHOENIX CONTACT

Academic Service

Dr. Wang has contributed significantly to the academic community by reviewing for over 10 reputable journals, including:

  • IEEE Transactions on Instrumentation and Measurement
  • IEEE Transactions on Neural Networks and Learning Systems
  • Scientific Reports
  • Applied Artificial Intelligence

Publications Top Notes 📚

  1. Title: A novel approach to detecting muscle fatigue based on sEMG by using neural architecture search framework
    Authors: S Wang, H Tang, B Wang, J Mo
    Journal: IEEE Transactions on Neural Networks and Learning Systems
    Volume: 34, Issue: 8, Pages: 4932-4943
    Year: 2021
    Citations: 28
    Summary: This paper proposes a novel method for detecting muscle fatigue from surface electromyographic (sEMG) signals by employing a neural architecture search (NAS) framework. The study demonstrates that using NAS can efficiently identify optimal deep learning architectures for accurate and real-time fatigue detection, making it a significant contribution to health monitoring technologies.
  2. Title: Analysis of fatigue in the biceps brachii by using rapid refined composite multiscale sample entropy
    Authors: S Wang, H Tang, B Wang, J Mo
    Journal: Biomedical Signal Processing and Control
    Volume: 67, Article Number: 102510
    Year: 2021
    Citations: 24
    Summary: This study focuses on the analysis of muscle fatigue in the biceps brachii using rapid refined composite multiscale sample entropy (rRCMSE), a novel method to quantify the complexity of sEMG signals during fatigue. The research provides a reliable approach for muscle fatigue assessment in clinical and rehabilitation settings.
  3. Title: A double threshold adaptive method for robust detection of muscle activation intervals from surface electromyographic signals
    Authors: H Tang, S Wang, Q Tan, B Wang
    Journal: IEEE Transactions on Instrumentation and Measurement
    Volume: 71, Article Number: 1-12
    Year: 2022
    Citations: 5
    Summary: This paper introduces a double-threshold adaptive method to improve the robustness of detecting muscle activation intervals from sEMG signals. The method enhances the reliability and accuracy of muscle activation detection, which is crucial for fatigue monitoring and rehabilitation applications.
  4. Title: Continuous estimation of human joint angles from sEMG using a multi-feature temporal convolutional attention-based network
    Authors: S Wang, H Tang, L Gao, Q Tan
    Journal: IEEE Journal of Biomedical and Health Informatics
    Volume: 26, Issue: 11, Pages: 5461-5472
    Year: 2022
    Citations: 4
    Summary: This paper proposes a deep learning-based model that estimates human joint angles continuously from sEMG signals. The model uses a temporal convolutional attention mechanism to process multiple features, enabling precise real-time joint angle estimation for applications in rehabilitation and prosthetics.
  5. Title: Optimizing graph neural network architectures for schizophrenia spectrum disorder prediction using evolutionary algorithms
    Authors: S Wang, H Tang, R Himeno, J Solé-Casals, CF Caiafa, S Han, S Aoki, …
    Journal: Computer Methods and Programs in Biomedicine
    Volume: 257, Article Number: 108419
    Year: 2022
    Citations: Not specified
    Summary: This paper focuses on optimizing graph neural network (GNN) architectures for predicting schizophrenia spectrum disorder. By using evolutionary algorithms, the study improves model accuracy, highlighting the potential of AI in mental health diagnosis and prognosis.

Conclusion

Dr. Shurun Wang is an outstanding candidate for the Best Researcher Award, owing to his remarkable contributions to biomedical signal analysis, brain function connectivity, and innovative health technologies. His research in detecting muscle fatigue, improving neurodiagnostic systems, and exploring neural systems for mental health prediction has the potential to revolutionize the field. With his continued dedication to advancing computational techniques in health sciences, Dr. Wang is poised to make even greater strides in improving medical diagnostics, neuroengineering, and treatment methodologies for neurological disorders.