[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.9.0″ _module_preset=”default” background_color=”RGBA(0,0,0,0)”][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_row _builder_version=”4.9.0″ _module_preset=”default”][et_pb_column type=”4_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_text admin_label=”Core Members” _builder_version=”4.9.0″ _module_preset=”default” header_font_size=”60px”]<\/p>\n
Core Members<\/h1>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_column type=”1_2″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_toggle title=”Parul Agarwal ” admin_label=”Parul ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n
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Associate Professor<\/p>\n
parul.agarwal@mountsinai.org<\/a><\/p>\n Parul Agarwal, PhD<\/strong> is a collaborative biostatistics faculty in the Department of Population Health Science and Policy and a teaching faculty in the Graduate School of Biomedical Sciences at Mount Sinai. She also provides statistical support to the Tisch Cancer Institute and is a quantitative scientist in the Otolaryngology division. She is trained in health outcomes research and advanced statistical methodologies. She leverages large administrative claims databases, survey databases, electronic health records and clinical trials data in her cancer research.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Asem Berkalieva ” admin_label=”Asem Berkalieva ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Senior Biostatistician<\/p>\n Asem.Berkalieva@mountsinai.org<\/a><\/p>\n Asem Berkalieva, MA<\/strong> serves as Senior Biostatistician within the TCI-BCI. She holds an MA in Biostatistics from University of California at Berkeley. Her role is multifaceted, including leadership of a long-term collaborative contract, overseeing all aspects of clinical trials from the initial design and protocol development to the critical phases of conduct, monitoring, and analysis. Asem is also a primary reviewer for the Biostatistics Design and Analysis Workshop. Her research interests include areas such as cluster randomized trial design, cost effectiveness analysis, and methods for health disparities research. Her contributions extend to pivotal committee roles, including her position as Primary Reviewer for the Biostatistics Design and Analysis Workshop as well as Lead Statistician for the Gastrointestinal Disease Focus Group. Furthermore, Asem plays a central role in leading a collaborative contract with the Breast Oncology group and supporting research endeavors of investigators from the Cancer Prevention and Control and Cancer Clinical Investigation programs. Her most recent accomplishment includes the statistical design and presentation of five clinical trials across various disease groups this year.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Karni Bedirian ” admin_label=”Karni Bedirian ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Biostatistician I<\/p>\n Karni.Bedirian@mountsinai.org<\/a><\/p>\n Karni Bedirian, MSc<\/strong>\u00a0serves as Biostatistician I within the TCI-BCI.\u00a0She holds an MSc in Biostatistics from New York University. Her role will be focused on projects related to the Stroke Pre-Clinical Network (SPAN) and Microscopy and Advanced Imaging Core. Karni’s research interests incorporate cutting-edge areas such as longitudinal & survival analysis to study patterns of disease and health in populations, non-parametric statistics, machine learning, and programming approaches to analyze epigenomic data underlying the genetic basis of diseases. Her recent accomplishments include developing a Shiny web application to visualize chromatin interaction data (http:\/\/shiny.immgen.org\/DNARchitect\/<\/a>).<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Marcio Diniz” admin_label=”Marcio Diniz” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″ hover_enabled=”0″ sticky_enabled=”0″]<\/p>\n Co-Director<\/p>\n Marcio.Diniz@mountsinai.org<\/a><\/p>\n Marcio Diniz, PhD<\/strong> is an Associate Professor in the Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai. He currently co-directs the Biostatistics Shared Resource at Tisch Cancer Institute. Previously, he was an Associate Professor of the Department of Medicine at Cedars-Sinai Medical Center and member of the Biostatistics Shared Resource at Samuel Oschin Cancer Institute. His research area is focused on design of adaptive clinical trials. He has developed statistical tools to design more efficient trials reducing the number of patients in phase I trials and false positive results in phase II trials.<\/p>\n As a biostatistician for the last 10 years, he has dedicated himself to the design and analysis of clinical data using a spectrum of study designs, from pilot studies to community intervention trials, in a variety of clinical areas, including cancer, cardiology, psychiatry, gerontology, health services and gastroenterology. He has extensive experience providing statistical support to clinical investigators using conventional statistical and novel methods. Throughout he has continuously promoted the adoption of good practices to ensure statistical rigor and reproducible research.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Weijia Fu ” admin_label=”Weijia Fu ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Biostatistician II<\/p>\n Weijia.Fu@mountsinai.org<\/a><\/p>\n Weijia Fu, MSc<\/strong>\u00a0serves as Biostatistician II within the TCI-BCI-SRF. She holds an MSc in Biostatistics from University of Washington in Seattle. Her role is multifaceted, including supporting faculty statistical methodological development for analysis of multi-omics data. Weijia has experience analyzing high dimensional data, large-scale population-level data and has expertise in statistical computing in Python and R. She also supports investigators from the Radiation Oncology and Multiple Myeloma groups through long term collaboration contracts and provides grant analysis support for investigators in the Cancer Immunology and Cancer Prevention and Control programs. Her recent accomplishments include an identification of cell-type-specific associations from bulk omics data, a revealing of novel mechanisms for prostate cancer survival through a transcriptome-wide association study, and a construction of Docker for data simulators.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Himanshu Joshi ” admin_label=”Himanshu Joshi ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Assistant Professor<\/p>\n Himanshu.Joshi@mountsinai.org<\/a><\/p>\n Himanshu Joshi<\/strong>, MBBS, MPH, PhD<\/strong> is an Assistant Professor at Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai. He aims to apply advances in data science and epidemiology for predictive models aiming at improving patient outcome and at gaining insights about disease. Dr Joshi has extensive research experience in computational oncology and multi-omics integrative approaches. Secondly, Dr. Joshi has been contributing to design national and international clinical trials at the Tisch Cancer institute and for the AIDS Malignancy Consortium. His focus is on incorporation of novel model-driven approaches in clinical trial design to improve flexibility and resource-efficiency.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Hulya Kocyigit” admin_label=”Hulya Kocyigit” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Post-doctoral Fellow<\/p>\n Hulya.Kocyigit@mountsinai.org<\/a><\/p>\n Hulya Kocyigit, PhD<\/strong> is a Post-doctoral Fellow at Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Lihua Li ” admin_label=”Lihua Li ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Associate Professor<\/p>\n Lihua.Li@mountsinai.org<\/a><\/p>\n Lihua Li<\/strong>, PhD<\/strong> is an associate professor in Department of Population Health Science and Policy and Department of Geriatrics and Palliative Medicine, Icahn school of Medicine at Mount. She is an experienced biostatistician and health services researcher, with a focus of the development and application of innovative statistical and economic methods to study cancer and aging related diseases. Her research in cancer treatment assesses the effectiveness of treatment options and provides insights for physician\u2019s practice in cancer care. Her research in cancer also includes cancer prevention and disparity in cancer care, as well as healthcare cost associated with cancer treatment\/care.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Madhu Mazumdar” admin_label=”Madhu Mazumdar” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″ hover_enabled=”0″ sticky_enabled=”0″]<\/p>\n Director<\/p>\n madhu.mazumdar@mountsinai.org<\/a><\/p>\n Madhu Mazumdar, PhD<\/strong> is a professor of biostatistics at Icahn School of Medicine at Mount Sinai in New York City (NYC). She is the Associate Director, Quantitative data Sciences, Tisch Cancer Institute and is co-director of TCI-BSR In these roles, she facilitates algorithm refinement for easy use by core users of all quantitative cores such as Microscopy and Advanced Imaging core, Pathology and Biorepository core, Cancer Advanced Genomics Technology Core, and Human Immune Monitoring core. She also organizes training in emerging computational methodologies such as artificial intelligence and machine learning, computer-aided drug development, methods for forecasting anticancer medications and treatment combinations based on multi-omics data, and clinical trial matching system.<\/p>\n Dr. Mazumdar learned how to become a biostatistician at her first job at Memorial Sloan-Kettering Cancer Center by discovering the nuances of cancer biology and conducting clinical trials. She served as the lead statistician on many investigative teams where molecular targets of drug resistance were sought and dose-intensive chemotherapy or new chemotherapeutic agents were evaluated in sequential Phase I\/II\/III clinical trials. She was then recruited to be the founding chief of the Division of Biostatistics and Epidemiology at Weill Cornell Medical College (WCMC). This new division obtained the Clinical and Translational Science Award (CTSA) grant and Dr. Mazumdar directed its biostatistics core with five other institutions. Through this experience she emerged as an avid team scientist and an effective leader. Strengthened by ELAM training and inspired by the Affordable Care Act and its goals of making healthcare affordable to all through optimization of cost and data-driven decision making, she became the founding Director of the Institute for Healthcare Delivery Science (I-HDS) at MSHS in NYC.<\/p>\n She received her master\u2019s degree in statistics from University of Delhi, India, master\u2019s degree in mathematics from University of Pittsburgh, and PhD in mathematical statistics from Penn State University, and he fellowship in Executive Leadership in Academic Medicine (ELAM) from Drexel University.\u00a0Dr. Mazumdar is a Fellow of the American Statistical Association, and a recipient of the Team Science Award and the Elizabeth L. Scott Award for Mentoring.<\/p>\n Dr. Mazumdar leads efforts to make biostatistics and data science diverse, equitable, and inclusive through novel models of teaching, mindful recruitment, targeted conference planning, and advising as a board member. Individualized mentorship is a cornerstone of her career, and she has personally mentored over one hundred professionals, a majority of whom are women along with many people of color and those who identify as LGBTQ+. She has advised them on how to conduct the highest quality research, how to gracefully advance their careers, and how to balance work and life. She loves cooking and hosting social events to bring people from different backgrounds together.<\/p>\n <\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Francesca Petralia” admin_label=”Francesca Petralia” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Assistant Professor<\/p>\n francesca.petralia@mssm.edu<\/a><\/p>\n Francesca Petralia, PhD<\/strong> received her PhD in Statistics from Duke University in 2013. She then joined the department of Genetics and Genomic Sciences at Mount Sinai where she develops statistical methods for the analysis of bulk, single-cell and spatial <\/span>transcriptomics<\/span> data. Specifically, she\u202fdeveloped multiple network <\/span>models which<\/span> characterize the associations across markers measured in high-throughput data, for the data-driven identification of key molecular drivers and pathways activated in disease. Such co-expression networks can provide functional insights into how genes and proteins interact with each other, enhancing systems-level multi-<\/span>omic<\/span> understanding of complex diseases. Additionally, she developed advanced statistical methods to characterize the tumor microenvironment based on bulk and single-cell <\/span>transcriptomics<\/span> data.\u202fIn the past years, she has applied\u202fthese new tools to analyze <\/span>large scale<\/span> proteogenomic<\/span> data to gain insights of complicated diseases. Dr. Petralia\u202fhas been leading multiple high-profile cancer projects as a member of the NCI\u2019s CPTAC (Clinical Proteomic Tumor Analysis Consortium).\u202f<\/span><\/span>\u00a0<\/span><\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Xiaoyu Song ” admin_label=”Xiaoyu Song ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Associate Professor<\/p>\n xiaoyu.song@mountsinai.org<\/a><\/p>\n Xiaoyu Song, DrPH<\/strong>\u00a0Associate Professor (Adjunct): Dr. Song\u2019s research interests are on developing statistical methods for -omic data analysis and applying them for understanding the molecular and cellular mechanisms for complex human diseases. Dr. Song have developed many statistical tools for the association, prediction, integration, and network analysis of genomic, epigenomic, transcriptomic, proteomic, and phenotypic data, and have applied them for analysis of data from cancer and other complex diseases. Dr. Song has an impressive track record on research, having authored over 50 research manuscripts in esteemed journals, shared\u00a0seven widely-used software tools, and played a significant role in securing NIH funding for ten research projects.\u00a0She is also a devoted mentor who have mentored and will continue mentoring junior faculty, research staff,\u00a0postdoctoral researchers,\u00a0and students at Mount Sinai.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Grace Van Hyfte ” admin_label=”Grace Van Hyfte ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Biostatistician II<\/p>\n Grace.VanHyfte@mountsinai.org<\/a><\/p>\n Grace Van Hyfte, MSc<\/strong> serves as Biostatistician II within the TCI-BCI. She holds an MSc in Statistics from Western Michigan University. Her role is multifaceted, including leadership of long-term collaborative contracts, overseeing all aspects of clinical trials from the initial design and protocol development to the critical phases of conduct, monitoring, and analysis. Grace’s research interests encompass cutting-edge areas such as group sequential designs for early phase clinical trials, longitudinal biomarker and time to event joint modeling in myeloproliferative disorders, causal Inference methods in NCDB and Medicare administrative databases, and time-to-event data analysis methods, particularly addressing competing risks in cancer treatment and progression of disease. Her contributions extend to pivotal committee roles, including her position as Primary Reviewer for the Biostatistics Design and Analysis Workshop and the TCI Data Safety and Monitoring Committee as well as Lead Statistician for the Lung, Liver and Bone Marrow Transplant Disease Focus Groups. Furthermore, Grace plays a central role in leading collaborative contracts with Lung Cancer, and Myeloproliferative Neoplasms groups supporting research endeavors of investigators from the Cancer Immunology and Cancer Clinical Investigation programs. Her recent accomplishments include the development of an innovative Rshiny app for sample size calculations in randomized phase II selection trials.\u00a0<\/p>\n [\/et_pb_toggle][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_toggle title=”Seungjun Ahn ” admin_label=”Seungjun Ahn ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Assistant Professor<\/p>\n Seungjun.Ahn@mountsinai.org<\/a><\/p>\n Seungjun Ahn, PhD<\/strong> is an assistant professor working for the Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai. He represents TCI-BCI in collaborating with pei-wang-lab<\/a>, Cancer genomics technology core<\/a>, and human immune monitoring center<\/a>. He received his PhD in Biostatistics from the University of Florida and was a NIH NIAAA T32 pre-doctoral fellow. His main research interests are in the area of differential network analysis, -omics data analysis, and causal mediation analysis.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Melanie Besculides” admin_label=”Melanie Besculides” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Assistant Professor<\/p>\n Melanie.Besculides@mountsinai.org<\/a><\/p>\n Melanie Besculides, DrPH, MPH<\/strong> is an evaluation scientist specializing in mixed-methods research. She has evaluated digital tools such as machine learning based clinical decision support systems, examining their usefulness and acceptability in clinical workflows. Dr. Besculides is involved in cancer research including work to improve access to care across the cancer continuum for traditionally minoritized populations. She has developed program logic models, timelines, and plans for knowledge transfer to ensure research leads to action. Dr. Besculides is also involved in a mixed methods study of the effects of radiotherapy treatment for breast and pelvic cancers on women\u2019s sexual health.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Mu-Hsun (Theresa) Chen” disabled_on=”on|on|on” admin_label=”Mu-Hsun (Theresa) Chen” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″ disabled=”on”]<\/p>\n Biostatistician II<\/p>\n mu-hsun.chen@mountsinai.org<\/a><\/p>\n Mu-Hsun (Theresa) Chen, MSc<\/strong>\u00a0serves as Biostatistician II within the TCI-BCI. She holds an MSc in Applied Statistics from Villanova University. Her role will be multifaceted, including supporting long-term collaborative contracts and analysis of clinical trial data. Theresa’s research interests encompass cutting-edge areas such as adaptive clinical trial design, machine learning and multivariate analysis, bootstrap methods, and programming approaches to ensure reproducible science. Her most recent accomplishment includes conducting simulation studies for power analysis of multivariate methods for design of Phase II clinical trials, including adaptive sample size re-estimation approaches.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Bart Ferket” admin_label=”Bart Ferket” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″ hover_enabled=”0″ sticky_enabled=”0″]<\/p>\n Co-Director<\/p>\n bart.ferket@mountsinai.org<\/a><\/p>\n Bart Ferket, MD PhD<\/span><\/span><\/strong>\u00a0serves as Co-Director for the Clinical Informatics <\/span>within the TCI-BSR <\/span>and <\/span>he <\/span>is<\/span> appointed as an Associate Professor in the <\/span>Institute for Healthcare Delivery Science and <\/span>Department of Population Health Science<\/span>.<\/span>\u00a0He <\/span>received his MD from the University of Amsterdam and an MSc in Clinical Epidemiology from the Netherlands Institute for Health Sciences. <\/span>He <\/span>holds a PhD in Clinical Epidemiology and Radiology with a focus on Medical Decision Making from the Erasmus University<\/span> Medical Center in Rotterdam.<\/span>\u00a0<\/span>H<\/span>is research <\/span>employs mathematical modeling and computer simulation techniques to estimate health and economic outcomes <\/span>for\u00a0chronic diseases <\/span>based on<\/span> data from clinical trials, population cohort studies, electronic health records<\/span>,<\/span> and administrative claims<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Mayuri Jain ” admin_label=”Mayuri Jain ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Biostatistician I<\/p>\n Mayuri.Jain@mountsinai.org<\/a><\/p>\n Mayuri Jain, MPH<\/strong> serves as a Biostatistician-I within the TCI-BCI. She holds an MPH from Boston University. Her role is multifaceted and encompasses various responsibilities, including supporting of a long-term collaborative contract, overseeing all aspects of clinical trials from the initial design and protocol development to the critical phases of conduct, monitoring, and analysis, along with the additional task of reviewing other clinical trial protocols. Mayuri\u2019s research interests include areas such as cluster randomized crossover trial design, Time to Event Bayesian Optimal Interval Phase 1\/2 design, causal inference methods such as propensity score matching, methods for analyzing data from population based surveys such as National Health Interview Survey (NHIS) and MarketScan. Her contributions extend to pivotal committee roles, including her position as Primary Reviewer for the Biostatistics Design and Analysis Workshop and the TCI Data Safety and Monitoring Committee as well as well as Lead Statistician for the Pediatrics and Neuro\/Sarcoma\/Melanoma Disease Focus Group. Furthermore, Mayuri plays a central role in supporting collaborative contracts with Radiation Oncology and Multiple Myeloma groups supporting research endeavors of investigators from the Cancer Prevention and Control and Cancer Clinical Investigation programs. Her most recent accomplishment includes designing the phase \u00bd trial using Time to event Bayesian optimal interval design for patients with myelofibrosis.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Nicklas Klepser” admin_label=”Nicklas Klepser” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″ hover_enabled=”0″ sticky_enabled=”0″]<\/p>\n Project Coordinator<\/p>\n Nicklas.Klepser@mountsinai.org<\/a><\/p>\n Nicklas Klepser, MPH<\/strong> is currently working as a project coordinator within the Department of Population Health Science & Policy at the Icahn School of Medicine at Mount Sinai. He <\/span>graduated with a bachelor\u2019s degree in economics with a minor in mathematics from Kalamazoo College and a <\/span>Master of Public Health<\/span> from the University of Haifa. He has worked as a program assistant at <\/span>Genemarkers<\/span> LLC. where he helped start and <\/span>operate<\/span> the production of SARS-CoV-2 test kits and contributed to research projects. Nicklas has also worked as a project manager for Point-of-Care Consultants where he conducted research and drafted reports for clients including state medical associations and biotechnology companies.\u00a0<\/span><\/span><\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Deukwoo Kwon” admin_label=”Deukwoo Kwon” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″ hover_enabled=”0″ sticky_enabled=”0″]<\/p>\n Associate Professor<\/p>\n Deukwoo.Kwon@mountsinai.org<\/a><\/p>\n Dr. Deukwoo Kwon, PhD<\/strong>\u00a0is an Associate Professor (Adjunct) at ISMMS and is the Associate Director for AIDS Malignancy Consortium grant from NCI. He is also an Associate Professor in the Division of Clinical and Translational Sciences, Department of Internal Medicine at McGovern Medical School, The University of Texas Health Science Center at Houston. He earned his Master\u2019s and PhD in statistics from Texas A&M University and worked at the National Cancer Institute (NCI) for six years. At NCI, Dr. Kwon worked on various epidemiologic studies, including radiation exposure assessment, uncertainty analysis, and measurement error models in a dose-response relationship. Before joining UTHealth at Houston in August 2022, he worked at the University of Miami and Icahn School of Medicine at Mount Sinai. He gained extensive experience developing optimal statistical designs and conducting analyses for cancer clinical trials and observational studies. He has achieved significant expertise by utilizing survival analysis, longitudinal data analysis, cancer registry data analysis, Bayesian inference, and high-dimensional data analysis for his collaborative work.<\/p>\n <\/p>\n [\/et_pb_toggle][et_pb_toggle title=”John Mandeli” admin_label=”John Mandeli” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Associate Professor<\/p>\n john.mandeli@mssm.edu<\/a><\/p>\n John Mandeli, PhD<\/strong> is an Associate Professor in the Department of Environmental Medicine and Public Health at Mount Sinai.<\/p>\n He holds a PhD in Statistics from Cornell University. Dr. Mandeli is a member of the Protocol Review and Monitoring Committee (PRMC).<\/p>\n He plays a significant role in securing NIH funding for several grants. As senior faculty, he also serves as a mentor to junior faculty.<\/p>\n Dr. Mandeli has several publications on the mathematical construction of new statistical designs.<\/p>\n Current collaborations include several grants in Immunotherapy for: Prostate Cancer, Lung Cancer, Lymphoma, and patients with PTEN-Altered Advanced Solid Malignancies.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Erin Moshier” admin_label=”Erin Moshier” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Managing Director<\/p>\n Erin.Moshier@mountsinai.org<\/a><\/p>\n Erin Moshier, MSc<\/strong>\u00a0serves as the Managing Director within the TCI-BCI. She holds an MSc in Biostatistics from Columbia University’s Mailman School of Public Health. Her responsibilities include project delegation and tracking metrics, oversight of staff statisticians’ workload, training and supervision of staff statisticians, facilitating support for cancer investigators through long-term collaborative contracts and leading contract and protocol development and review initiatives. Erin’s research interests encompass areas such as Model Assisted Bayesian Optimal Interval Designs for Early Phase Clinical Trials, Longitudinal Biomarker and Time to Event Joint Modeling, and methods to address biases in observational Electronic Health Record (EHR)-based studies. Her leadership extends to pivotal committee roles, including her position as Co-Chair and Primary Reviewer for the Biostatistics Design and Analysis Workshop, as well as Lead Statistician for the Hematology and Breast Disease Focus Groups. Furthermore, Erin plays a central role in leading collaborative contracts with Multiple Myeloma, Breast Oncology, Breast Surgery, and Radiation Oncology supporting research endeavors of investigators from the Cancer Immunology and Cancer Clinical Investigation programs. Her most recent accomplishment includes promoting use of the Time to event Bayesian optimal interval Phase \u00bd design for an early phase trial exploring novel treatments for patients with myeloproliferative neoplasms.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Simon Sheng ” admin_label=”Simon Sheng ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Biostatistician I<\/p>\n Tianxiang.Sheng@mountsinai.org<\/a><\/p>\n Simon Sheng, MSc<\/strong> serves as Biostatistician I within the TCI-BCI-SRF. He holds an MSc in Biostatistics from Boston University. His role is multifaceted, including two long-term collaborative contracts, where he offers statistical support to cancer investigators. His research interests encompass investigating racial bias in healthcare and its impact on patient outcomes, evaluating the effectiveness of novel tools in cancer treatment, analyzing survival rates and time-to-event models, utilizing longitudinal and mixed-effects models, and conducting studies with large databases like NCDB. Additionally, Simon holds an important position in Cancer Prevention and Control, and Cancer Clinical Investigation programs. His latest achievement involves utilizing mixed-effects models for analyzing disparities in serious illness communication.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Lewis Tomalin” admin_label=”Lewis Tomalin” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Assistant Professor<\/p>\n lewis.tomalin@mountsinai.org<\/a><\/p>\n Lewis Tomalin, PhD<\/strong> is an Assistant Professor working for the Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai. He represents TCI-BCI in collaborating with BINGS<\/a>. \u00a0He has extensive expertise applying Biostatistical and Bioinformatic methods to a broad range of biomedical fields including Cardiovascular Disease, Dermatology and Viral Infection, with an emphasis on immunology. He specializes in the analysis of longitudinal high-throughput data, such as RNA-seq and mass-cytometry, utilizing advanced methods such as linear-mixed effects models and machine-learning.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Chen Yang ” admin_label=”Chen Yang ” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Biostatistician II<\/p>\n Chen.Yang@mountsinai.org<\/a><\/p>\n Chen Yang, PhD<\/strong> serves as Biostatistician II within the TCI-BCI-SRF. He holds a PhD in Statistics from Western University in Canada. His role includes statistical modelling, simulation, and data analysis. Chen’s research interests encompass cutting-edge areas such as multi-state modelling, propensity score methods for survival analysis, machine learning-based propensity score methods, and sample size methods for Stepped-Wedge clustered trial design to support research endeavors of investigators from the Cancer Prevention and Control program.<\/p>\n [\/et_pb_toggle][et_pb_toggle title=”Wei Zhang” admin_label=”Wei Zhang” _builder_version=”4.9.0″ _module_preset=”default” title_level=”h3″]<\/p>\n Biostatistician II<\/p>\n Wei.Zhang@mountsinai.edu<\/a><\/p>\n Wei Zhang, PhD<\/strong> serves as Biostatistician II within the Department of Population Health Science and Policy. He holds an PhD. in Mathematics with emphasis on Statistics from Florida Atlantic University and has over 2 years of postdoctoral training from Hospital for Special Surgery, Weill Cornell Medical College and the George Washington University. His role will be multifaceted, including supporting long-term collaborative contracts and analysis of clinical trial data. Wei’s main research interests are in the area of survival analysis, missing data imputation, statistical genomics, complex survey design and machine learning methods. His most recent accomplishment includes conducting simulation studies for examining propensity score weighting method in complex survey data with survival outcomes.\u00a0<\/span><\/p>\n [\/et_pb_toggle][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ disabled_on=”on|on|on” _builder_version=”4.9.0″ _module_preset=”default” disabled=”on”][et_pb_row _builder_version=”4.9.0″ _module_preset=”default”][et_pb_column type=”4_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_text admin_label=”Team table” _builder_version=”4.9.0″ _module_preset=”default”]<\/p>\n![\"\"](\"https:\/\/labs.icahn.mssm.edu\/tcibci\/wp-content\/uploads\/sites\/505\/2023\/09\/Asem_Berkalieva-226x300.jpg\")
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