My research focuses on developing new methodology for analyzing high dimensional dependent data.
Dependence is a natural phenomenon occurring in several real life scenario, specifically in data observed over time or in a spatial context. Ignoring this underlying spatial and temporal dependence structure leads to incorrect result for inference and prediction problem. The severity of dependence may drastically affect the behavior of the estimators. Moreover the behavior of the observations nay change over time or based on geographical location. It is important to include any such structure affecting the data generating process in the model. Data can be observed in both temporal and spatial context, and often both spatial and temporal dependence affect each other. I am interested in such interesting dynamics of data and modelling and analyzing them with minimal assumptions on the structure.
The other aspect of my research deals with analyzing high dimensional data. With the advancement of modern technology, we have access to high dimensional and high resolution data. The classical statistical set-up allows analysis only for the case where the sample size is larger than the dimension of the observation, which is not very realistic in most of the modern statistical problems. One way of dealing with high dimensionality is to use the natural smooth structure of the data generating process and treat the data as functions. Some interesting examples include satellite images, financial transaction data, demographic curves etc. Statistical analysis if these data pose challenges both in terms of availability of mathematical tools to analyze them , as well as computational cost to deal with the high dimensionality of the observations. I am interested in developing computationally efficient statistical methodologies to analyze these data specially in the context of dependence.
Publications:
Palak Shah, Sean Agbor-Enoh, Pramita Bagchi, Christopher R. deFilippi, Angela Mercado, Gouqing Diao, Dave JP Morales, Keyur B. Shah, Samer S. Najjar, Erika Feller, Steven Hsu, Maria E. Rodrigo, Sabra C. Lewsey, MD, Moon Kyoo Jang, Charles Marboe, Gerald J. Berry, Kiran K. Khush, Hannah A. Valantine. (2022) “Circulating MicroRNAs in Cellular and Antibody-Mediated Heart Transplant Rejection,” Journal of Heart and Lung Transplantation. Vol: 41, No: 10.
James Cameron and Pramita Bagchi (2022) Test for heteroscedasticity in functional linear models. Test. [pdf]
Shashank S. Sinha, Carolyn M. Rosner, Behnam N. Tehrani, Aneel Maini, Alexander G. Truesdell, Seiyon Ben Lee, Pramita Bagchi, James Cameron, Abdulla A. Damluji, Mehul Desai, Shashank S. Desai, Kelly C. Epps, Christopher deFilippi, M. Casey Flanagan, Leonard Genovese, Hala Moukhachen, James J. Park, Mitchell A. Psotka, Anika Raja, Palak Shah, Matthew W. Sherwood, Ramesh Singh, Daniel Tang, Karl D. Young, Timothy Welch, Christopher M. O’Connor, Wayne B. Batchelor. “Cardiogenic Shock From Heart Failure Versus Acute Myocardial Infarction: Clinical Characteristics, Hospital Course, and 1-Year Outcomes” (2022) Circulation: Heart Failure, Vol: 15, No: 6.
Hooman Bakhshi, Pramita Bagchi, Zahra Meyghani, Behnam Tehrani, Xiaoxiao Qian, Parveen K. Garg, Bharath Ambale-Venkatesh, Harpreet S. Bhatia, Yoshiaki Ohyama, Colin O. Wu, Matthew Budoff, Matthew Allison, Michael H. Criqui, David A. Bluemke, Joao A.C. Lima, and Christopher R. deFilippi. (2021) “Association of coronary artery calcification and thoracic aortic calcification with incident peripheral arterial disease in the Multi-Ethnic Study of Atherosclerosis (MESA),” European Heart Journal Open, Vol: 1 (3).
Y. Alicia Hong, Yee Soo, Pramita Bagchi, Hee-soon Juon, Daisy Le, Sojung Claire Ki. (2021), “Social media-based intervention to promote HBV screening and liver cancer prevention among Korean Americans: Results of a pilot study,” Digital Health, Vol: 8. [pdf]
Janusz Wojtusiak, Pramita Bagchi, Sri Durbha, Hedyeh Mobahi, Reyhaneh Mogharab Nia and Amira Roess. (2021) COVID-19 Symptom Monitoring and Social Distancing in a University Population. Journal of Healthcare Informatics Research, Vol: 5(1), page:114-131
Pramita Bagchi and Holger Dette (2020). "A Test for Separability in Covariance Operators of Random Surfaces."The Annals of Statistics, Vol: 48(4), page: 2303–2322. [pdf]
Pramita Bagchi and Subhra Sankar Dhar (2020). "A Study on the Least Square Estimator of Multivariate Isotonic Regression Function." Scandinavian Journal of Statistics, Vol: 47(4), page: 1192-1221.
Pramita Bagchi, Vaidotas Characiejus and Holger Dette (2018), "A Simple Test for White Noise in Functional Time Series." Journal of Time Series Analysis, Vol 39, page: 54 - 74 . [pdf]
Pramita Bagchi, Moulinath Banerjee and Stilian Stoev (2016). "Inference for Monotone Functions Under Short-and Long-Range Dependence: Confidence Intervals and New Universal Limits." Journal of the American Statistical Association, Vol: 111(516), page: 1634-1647. [pdf]
Belinda Needham, Bhramar Mukherjee, Pramita Bagchi, Catherine Kim, Arnab Mukherjee, Namratha R. Kandula, and Alka M. Kanaya. (2017) "Acculturation Strategies and Symptoms of Depression: The Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study." Journal of Immigrant and Minority Health, In press. [pdf]
Belinda Needham, Bhramar Mukherjee, Pramita Bagchi, Catherine Kim, Arnab Mukherjee, Namrantha R. Kandula, Alka M. Kanaya. (2017). “Acculturation Strategies among South Asian Immigrants: The Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study.” Journal of Immigrant and Minority Health. Vol: 19(2), page: 373-380 [pdf]
Belinda Needham, Catherine Kim, Bhramar Mukherjee, Pramita Bagchi, Frazk Z. Stanczyk, and Alka M. Kanaya. (2015) “Endogenous Sex Steroid Hormones and Glucose in Non-diabetic South Asians: The Metabolic Syndrome and Atherosclerosis in South Asians Living in America Pilot Study.” Diabetic Medicine Vol: 32, page: 1193-2000. [pdf]
Parichoy Pal Choudhury, Pramita Bagchi, Sebanti Sengupta and Anurag Basu (2010), "On Eect of Compromised Nodes on Security of Wireless Sensor Network",Ad Hoc & Sensor Wireless Networks, Vol: 9(3:4), page: 255-273.
Research Grants:
Collaborative Research: Empirical Frequency Band Analysis for Functional Time Series.
Funding Agency: National Science Foundation, Date: 9/1/2022 – 8/31/2025
PI: Pramita Bagchi, Co-PI: David Straus, External PI: Scott Bruce
Clinical Data Analytics, Protein and Genomic Biomarkers in Heart Failure, Mechanical Support, and Cardiac Transplantation.
Funding Agency: INOVA Hospital, Date: 1/1/2020 – 3/31/2023
PI: Pramita Bagchi