Dr. Samprit Banerjee | Sensor integration Awards | Excellence in Innovation

Dr. Samprit Banerjee, Weill Medical College of Cornell University, United States

Dr. Samprit Banerjee is an Associate Professor of Biostatistics at the Weill Medical College of Cornell University, where he has held various academic appointments since 2011. He currently serves as an Associate Professor in both the Division of Biostatistics and the Department of Psychiatry, as well as the Director of the PhD program in Population Health Sciences. Dr. Banerjee’s expertise lies in biostatistics, data science, and epidemiology, with a focus on statistical methods for health research and healthcare policy. He is also a Special Government Employee at the FDA, contributing to the Center for Devices and Radiological Health. Dr. Banerjee has a distinguished academic background, holding a B.Stat and M.Stat from the Indian Statistical Institute, Kolkata, and a PhD in Biostatistics from the University of Alabama at Birmingham. His teaching experience includes directing multiple graduate-level courses in biostatistics, statistical learning, and big data in medicine. Throughout his career, he has mentored numerous junior researchers and contributed to the development of MS and PhD programs in Biostatistics and Data Science. Dr. Banerjee has also served as an elected representative for the Mental Health Statistics Section of the American Statistical Association.

Professional Profile:

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Summary of Suitability for Excellence in Innovation

Samprit Banerjee, PhD, is highly suitable for the “Research for Excellence in Innovation” award based on his extensive academic background, research contributions, and leadership roles in biostatistics, epidemiology, and data science. His expertise in high-dimensional data analysis, machine learning, and multivariate statistics, combined with his significant contributions to medical and healthcare research, makes him a standout candidate.

Education:

1998-2001: B.Stat (Bachelors in Statistics), Indian Statistical Institute, Kolkata, India
2001-2003: M.Stat (Masters in Statistics), Indian Statistical Institute, Kolkata, India
2003-2008: PhD in Biostatistics, Department of Biostatistics, University of Alabama at Birmingham

Work Experience:

Jan 2020 – Present: Associate Professor, Division of Biostatistics, Department of Population Health Sciences, Weill Medical College, Cornell University, New York, NY
May 2023 – Present: Associate Professor of Biostatistics, Department of Psychiatry, Weill Medical College, Cornell University, New York, NY
Jan 2018 – Jan 2020: Associate Professor, Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Medical College, Cornell University, New York, NY
Jan 2018 – Present: Adjunct Associate Professor, Department of Statistics and Data Science, Cornell University, Ithaca, NY
Nov 2020 – Present: Director (Founding) of PhD Program in Population Health Sciences, Department of Population Health Sciences, Weill Medical College, Cornell University, New York, NY
2014 – Present: Special Government Employee, Center for Devices and Radiological Health (CDRH), Food and Drug Administration (FDA), Silver Springs, MD
2022 – 2024: Elected Council of Sections Representative for the Mental Health Statistics Section of American Statistical Association (ASA)

Past Positions:

2016 – 2020: Director (Founding) of MS Program in Biostatistics & Data Science, Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Medical College, Cornell University, New York, NY
May 2011 – Dec 2017: Assistant Professor, Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Medical College, Cornell University, New York, NY
May 2011 – Dec 2017: Adjunct Assistant Professor, Department of Statistical Science, Cornell University, Ithaca, NY
Aug 2008 – May 2011: Instructor, Division of Biostatistics and Epidemiology, Department of Public Health, Weill Medical College of Cornell University, New York, NY
Jun 2005 – Aug 2008: Graduate Research Assistant, Department of Biostatistics, University of Alabama, Birmingham (Supervisor: Dr. Nengjun Yi) – Developed Bayesian methods for detecting gene by gene and gene by environment interactions for QTLs in inbred mice.
Aug 2003 – Jun 2005: Graduate Research Assistant, Department of Biostatistics, University of Alabama at Birmingham (Supervisor: Dr. Varghese George) – Worked on Marginal Structural Models to investigate genetic effects in AIDS and developed Bayesian methods for QTL detection in Human Genetics.

Publication top Notes:

Perioperative comparative effectiveness of anesthetic technique in orthopedic patients

CITED:581

Rearrangements of the RAF kinase pathway in prostate cancer, gastric cancer and melanoma

CITED:556

Mechanism-based epigenetic chemosensitization therapy of diffuse large B-cell lymphoma

CITED:219

Epigenetic repression of miR-31 disrupts androgen receptor homeostasis and contributes to prostate cancer progression

CITED:195

Elevated prefrontal cortex GABA in patients with major depressive disorder after TMS treatment measured with proton magnetic resonance spectroscopy

CITED:156

R/qtlbim: QTL with Bayesian interval mapping in experimental crosses

CITED:153

Introduction Best Nanotechnology for Sensing

The Best Nanotechnology for Sensing Award recognizes outstanding contributions in the field of nanotechnology for sensing applications. This prestigious award aims to honor individuals who have made significant advancements in sensor technology using nanomaterials.

Award Eligibility:

The award is open to researchers, scientists, engineers, and innovators worldwide. There is no age limit for eligibility. Applicants must have a background in nanotechnology or a related field.

Qualifications:

Applicants should possess a Ph.D. or equivalent qualification in a relevant field. They should also have a strong publication record in the area of nanotechnology for sensing.

Requirements:

Submissions must include a detailed research proposal outlining the use of nanotechnology in sensing applications. Applicants should also provide a list of publications related to their work in this field.

Evaluation Criteria:

Submissions will be evaluated based on the significance of the research, the innovation of the approach, and the potential impact on the field of sensing technology.

Submission Guidelines:

All submissions must be sent via email to the award committee. The deadline for submissions is [insert deadline date].

Recognition:

The recipient of the Best Nanotechnology for Sensing Award will receive a cash prize and a certificate of recognition. They will also be invited to present their research at a prestigious conference.

Community Impact:

Winners of the award are expected to contribute to the community by sharing their knowledge and expertise with other researchers in the field.

Biography:

Applicants should provide a brief biography highlighting their academic and professional achievements in the field of nanotechnology for sensing.

Abstract and Supporting Files:

Submissions must include an abstract of the research proposal and any supporting files, such as graphs, charts, or images, that illustrate the research.