Center for Biostatistics

The Center for Biostatistics at the Icahn School of Medicine at Mount Sinai (ISMMS) reflects the Institutional commitment to advancing interdisciplinary translational and patient-oriented research by providing state-of-the-art statistical support to investigators.

Mission

The Center for Biostatistics at ISMMS is committed to promoting excellence in statistics and data science in the domains of education and collaborative research. We aim to foster and promote an equitable and inclusive academic culture through our MS in Biostatistics Program and graduate-level coursework, Grand Rounds seminars, consultation services, mentoring relationships, and federally-funded statistical training programs, where all students, trainees, and investigators are adequately supported in their efforts to enhance their methodologic proficiency. Through our research collaborations and partnerships, our renowned statisticians and data scientists develop highly innovative statistical methodologies and find novel applications of existing methodologies all aspects of statistical education, to support investigators in clinical and basic science research and to develop highly innovative statistical methodologies in order to translate complex data into knowledge for the betterment of public health.

The Center for Biostatistics is the academic home for the ISMMS biostatisticians and data scientists, and provides a structure to support the professional growth of its members, and students, and trainees and to foster mutually rewarding collaborative relationships with colleagues at Mount Sinai. In alignment with Mount Sinai’s Road Map for Action as well as our department’s continued commitment to antiracism, the Center for Biostatistics strives to promote and sustain diversity, equity, and inclusion in education and training, mentorship, and research. Our members make every effort to ensure that our approach to the collection and analysis of data does not perpetuate racism or further stigmatize racial/ethnic minoritized groups. We also work diligently to transform the demographic landscape of our field through local, institutional, and national service aimed at increasing the recruitment, retention, and advancement of women, BIPOC, LGBTQIA+, and other marginalized groups in statistics and data science.

Vision

We envision a world in which all individuals regardless of racial or social background are free from disease through innovations in population health science.

Biostatistics Cores

To foster collaborations that stimulate translational and clinical research across the Mount Sinai Health System, the Center has established Biostatistics Cores. The cores are designed to support the statistical needs of Departments and Institutes, and to assist in the development of research agendas. . Cores include junior and senior faculty members and Masters level statisticians at varying levels of effort as dictated by specific departmental needs. The goals of the biostatistics cores are to promote collegial interactions, facilitate strong academic relationships, initiate long-term thematic collaborations, and give biostatisticians the opportunity to develop new methodologies in specific clinical areas.

Statistical Consultation Resources

In close collaboration with the Mount Sinai Clinical and Translational Science Award (CTSA), the Center for Biostatistics offers a fee-for-service statistical consultation resource. The Statistical Consultation Service is a flexible, comprehensive and accessible resource aimed at providing and facilitating long-term collaborative and short-term consultative advice in study design and biostatistics, from the planning stages through interpretation and dissemination of study results. Consultations cost $125 per hour.

To request a Biostatistics, Epidemiology, and Research Design (BERD) statistics consultation, please complete a Request for Service form online.

For more information about BERD, please contact Yvette Hutson at yvette.hutson@mountsinai.org.

Stat-Chat is a walk-in consultation service meant to resolve easy problems and answer quick questions regarding data analysis, study design, model interpretation, etc. All faculty, fellows, residents, staff, and medical students are welcome to use this resource for quick statistics-related questions. Stat-Chat is offered once per week with two statisticians available for an hour on a first-come first-served basis. To request a STAT-CHAT consultation, please complete a request form online.

Meet Our Team

Faculty

  • Emilia Bagiella, PhD – Director
  • Mayte Suarez-Farinas, PhD – Associate Director
  • Emma Benn, DrPH
  • Natalia Egorova, PhD
  • Usha Govindarajulu, PhD
  • Bian Liu, PhD
  • Junxiu (Juju) Liu, PhD
  • Shelley Liu, PhD
  • Jessica Overbey, DrPH
  • Umut Ozbek, PhD
  • Lewis Tomalin, PhD
  • Alan Weinberg, MS

Post-Doctoral Fellows

  • Milagros Sanchez-mayor
  • Zainab Al-Taie, PhD

MS Biostatisticians

  • Helena Chang, MS
  • Yitong Chen, MS o Richa Deshpande, MPH
  • Elianna Kaplowitz, MPH
  • Ditian Li, MS
  • Sydney Lu, MS
  • Yuxia Ouyang, PhD
  • Samantha Raymond, MPH
  • Eric Reynolds, MS
  • Guillaume Stoffels, MS
  • Kelly Wang, MPH
  • Zhan Zhao, MA

Programmers

  • Kevin Brea
  • Ju-Hsin (Judy) Chen

Administrative Assistant

  • Yvette Hutson

Educational Programs

Our educational programs include those for degrees, courses, and summer learning.

The Master of Science in Biostatistics program provides students with the fundamental skills required for conducting high-quality clinical and translational research. The curriculum emphasizes strong quantitative training, critical thinking skills, and practical strategies for addressing complex challenges of clinical research.

The Theory and Methods Track is for students whose goal is to work as biostatisticians or data analysts in a clinical, research, or industry setting. It can also be used as a stepping stone to pursuing a PhD in Biostatistics or Epidemiology. Applicants do not need to have a background related to a health or clinical field, but strong quantitative experience is preferable.

The Clinical Applications Track is designed for clinical and translational investigators who want to acquire knowledge of quantitative methods in clinical research. A strong quantitative background and a degree in Medical Sciences (MD, DDS, DMD, ND or DO) are required for this program. The program consists of at least 34 credits that must be completed in one full-time year of study that consists of both a course requirement and a capstone requirement.

The sensitivity and availability of omics technologies have enabled the genomic, transcriptomic and proteomic characterization of disease phenotypes, at the tissue and even the single cell level. This has allowed identification of disease subtypes that respond well to specific treatment and thus opened up opportunities for development of precision/personalized medicine strategies for optimizing treatments for individual patients. Analysis of single-nucleotide polymorphisms (SNPs) and interpretation of its role in disease phenotypes and treatment outcomes have been widely studied. To date, analysis of SNP data is still crucial for understanding the phenotypes and outcomes. However, it is now becoming clear that the future of precision medicine will rely on the integration of genomic and transcriptomic data with clinical data, as well as the application of advanced statistical methods and machine learning, to unravel the complex interactions between genetics, gene-expression and disease-phenotypes.

Thus, new genomic science educational initiatives need to be continually updated to educate the clinical and translational workforce on how to effectively interpret and apply the findings from genomics studies. Patients of providers who have participated in these educational initiatives also benefit as it allows for more rapid integration of genomic study findings into the clinical care setting. In order to hasten the incorporation of genomic findings into medical practice many institutions developed genomic medicine programs, some of which are well documented thanks to efforts by the National Human Genome Research Institute (NHGRI). These earlier courses primarily targeted the participants already in genetics and genomics research.

With the CREiGS Short Course, we offer an innovative, hybrid educational program for doctoral students, residents, postdoctoral scholars, and faculty engaged in clinical and translational research with limited background in the analysis

of genetics/genomics data. Ultimately, those participating in CREiGS will have the opportunity to increase their scientific knowledge, methodologic rigor, and research capacity.