2. Profile
  3. Runa Bhaumik

Runa Bhaumik PhD

Runa Bhaumik
Designation
  • Research Assistant Professor
  • University of Illinois at Chicago
Contact Information
  • rbhaumik [at] uic.edu
  • (312) 413-4455
  • School of Public Health / Psychiatric Institute (SPHPI)
    1601 W. Taylor St.
    SPHPI MC 912
    Chicago IL 60612
  • Room #:513
Website

Dr. Runa Bhaumik is a research assistant professor at Biostatistical Research Center, in the Department of Psychiatry. Her research focuses on Longitudinal Data Analysis, Multivariate Statistical analysis, Graph Theory, Natural Language Processing, and applications of Machine Learning Algorithms to Neuroscience and other fields.

  • psychiatry

    Multivariate Statistical analysis, Graph Theory, Machine Learning, Neuroscience
  • Transdiagnostic Brain-Behavior Profiling to Enhance Cognitive Behavioral Therapy Response (PI: Heide Klumpp)

    The goal of this study is to employ well-validated paradigms to test emotion-regulating and emotiongenerating in the context of negative stimuli, reward processes, and fear systems in MDD and gSAD to delineate common and disorder-specific mechanisms of change and predictors of CBT outcome. Role: Co-Investigator.

  • Menstrual cups, maturation of the adolescent vaginal microbiome, and STI/HIV risk (PI : Supriys Mehta)

    The goal of this project is to study the mechanisms by which menstrual cup use lead to reduced BV and STIs, and the effect of menstrual cup use on evolution of the adolescent vaginal microbiome. Role: Co-Investigator.

  • Dimensional RDoC Modeling across the Range of Negative Mood Dysfunction (PI : Scott Langenecker)

    The goal of this project is to use advanced modeling and stratification techniques, with our expertise in biostatistics and statistical machine learning, to devise across-diagnosis subgroups that share core dimensions of dysfunction, which will link the neurophysiological abnormalities to disease risk and potentially provide more refined treatment targets.  We will pursue, an iterative strategy of (a) cross-modality scale development and consolidation for each subdomain (e.g., PCA, ICA), (b) illness vs well characterization via standard and novel techniques (e.g., support vector), (c) subtyping using scale and disease characteristics for each subdomain (cluster, ICA).

  • Advancing Clinical Outcomes, Biomarkers and Treatments for Severe TBI (PI: Pape) Source of Support: DoD, U.S. Army Medical Research and Materiel Command, Joint Warfighter Medical Research Program

    This umbrella grant includes two research projects. The purpose of Project #1 is to advance the treatment of patients with severe TBI by making outcome assessments more comparable, accurate, and meaningful. This will be achieved by conducting both single and multi-faceted Rasch analyses of 5 widely-used TBI outcome assessments. The purpose of Project #2 is to identify specific miRNA, derived from whole blood and microparticles, associated with recovery from severe TBI with and without rTMS treatment.

  • Dulal Bhaumik, Fei Jie, Rachel Nordgren, Runa Bhaumik, and Bikas K. Sinha, A mixed-effects model for detecting disrupted connectivities in heterogeneous data, IEEE Transactions on Medical Imaging, 2018 ( in print).

    Natania A. Crane, Alvaro Vergés, , Masoud Kamali, Runa Bhaumik, Kelly A. Ryan, David F. Marshall, Erika F. H. Saunders, , Michelle T. Kassel, Anne L. Weldon, Melvin G. McInnis, Scott A. Langenecker, Developing Dimensional, Pandiagnostic Inhibitory Control Constructs With Self-Report and Neuropsychological Data,Assessment (2018), https://doi.org/10.1177/1073191118754704

    Pandey GN, Rizavi HS,Bhaumik R, Ren X. Innate immunity in the postmortem brain of depressed and suicide subjects: role of Toll-like receptors. Brain, Behavior and Immunity (under revision), 2018.

    Pandey GN, Rizavi HR, Zhang H, Bhaumik R, Ren X. Abnormal protein and mRNA expression of inflammatory cytokines in the prefrontal cortex of depressed and suicide subjects. Journal of Psychiatry and Neuroscience (In Press), 2018.

    Runa Bhaumik, Ashish Pradhan, Soptik Das, Dulal K. Bhaumik, Predicting Autism Spectrum Disorder using Domain-Adaptive Cross-Site Evaluation. Neuroinformatics (2018),

    DOI: 10.1007/s12021-018-9366-0

    Heide Klumpp, Runa Bhaumik , Kerry L. Kinney, Jacklynn M. Fitzgerald, Principal component analysis and neural predictors of emotion regulation, Behavioural Brain Research 338 (2018) 128–133(2017).

    Natania A. Crane, Lisanne M. Jenkins,  Runa Bhaumik, Catherine Dion, Jennifer R. Gowins, Brian J. Micky, Jon-Kar Zubieta, Scorr A. Langenecker, Multidimensional prediction of treatment response to antidepressants with cognitive control and functional MRI, Brain January 2017 DOI: 10.1093/brain/aww326

    R. Bhaumik, J.Gowins, R. Jacobs, L. Jenkins, A. Barba, D. K.Bhaumik, S.A. Langenecker, Multivariate Pattern Analysis Strategies in Detection of Remitted Major Depressive Disorder using Resting State Functional Connectivity, Neuroimage-clinical, 2016.

    Hooriyah S. Rizavi, Xinguo Ren , Hui Zhang ,  Runa Bhaumik, Ghanshyam N. Pandey, Abnormal gene expression of proinflammatory cytokines and their membrane-bound receptors in the lymphocytes of depressed patients, Psychiatry Res. 2016 Apr 22;240:314-320. doi: 10.1016/j.psychres.2016.04.049.

    Ghanshyam N. Pandey, Hooriyah S. Rizavi, Hui Zhang, Runa Bhaumik, Xinguo Ren, The Expression of the Suicide-Associated Gene SKA2 Is Decreased in the Prefrontal Cortex of Suicide Victims but Not of Nonsuicidal Patients Feb 2016 · The International Journal of Neuropsychopharmacology

    Caveney A, Pandey AS, Langenecker SA, Gabriel L, Ortiz JA, Huq N, Bhaumik R Thompson BG, Giordani BJ, Auer DL, Morgenstern L. Neurocognitive Decline and Recovery in Patients Undergoing Microsurgical vs Endovascular Treatment of Unruptured Intracranial Aneurysms. Neurosurgery. 2015 Aug; 62 Suppl 1:217. doi: 10.1227/01.neu.0000467120.07828.a0

    Marc S. Atkins, Elisa S. Shernoff, Stacy L. Frazier, Sonja K. Schoenwald, Elise Cappella, Ane Marinez-Lora, Tara G. Mehta, Davielle Lakind,  Runa Bhaumik, Dulal Bhaumik. Re-Designing Community Mental Health Services for Urban Children: Supporting Schooling to Promote Mental Health (JCCP, 2015)

    Lambert, B.,  Bhaumik, R. , Zhao, W., Bhaumik, D. “Detection and Prediction Limits for Identifying Highly Confusable Drug Names from Experimental Data”, Journal of Biopharmaceutical Statistics, 2015

    Ren X, Rizavi HS, Khan MA, Bhaumik R., Dwivedi Y, Pandey GN. Alteration of cyclic-AMP response element binding protein in the postmortem brain of subjects with bipolar disorder and schizophrenia. J Affect Disord 152-154:326-33, 2014 [Epub 2013 Oct 5] PMID: 24148789.

    Kapur, K.,Bhaumik, R., Tang, X.C., Hur, K., Moritz, T.E., Domenic J. Reda, D.J., and Bhaumik, D.K., ``Sample Size Determination for Longitudinal Binary Data.”, Statistics in Medicine, 2014.

    Ghanshyam N. Pandey, Ph.D., Hooriyah S. Rizavi, M.S., Xinguo Ren, M.D., Runa Bhaumik, Ph.D., Yogesh Dwivedi, Ph.D., Toll-like receptors in the depressed and suicide brain,J Psychiatr Res. 2014 Jun;53:62-8. doi: 10.1016/j.jpsychires.2014.01.021. Epub 2014.

    D. Bhaumik, K. Kapur, R.Bhaumik and D. Reda, Sample Size Determination for Testing the Mean of a Lognormal Distribution, Journal of Environmental Statistics, 2013.

    B. Mobasher, R. Burke, R. Bhaumik and C. Williams. Towards Trustworthy Recommender Systems: An Analysis of Attack Models and Algorithm Robustness. ACM Transactions on Internet Technology, Vol. 7, No. 2, May 2007.

    B. Mobasher, R. Burke, R. Bhaumik, and JJ. Sandvig. Attacks and Remedies in Collaborative Recommendation. IEEE Intelligent Systems, Vol. 22, no. 3, pp. 56-63, May/June, 2007

Title Description Investigator(s) Category Status
Menstrual cups, maturation of the adolescent vaginal microbiome, and STI/HIV risk The goal of this project is to study the mechanisms by which menstrual cup use lead to reduced BV and STIs, and the effect of menstrual cup use on evolution of the adolescent vaginal microbiome.   Biostatistical Research Program On-going
Passive, Mobile Assessment of Sleep, Circadian Timing, and Keyboard Dynamics to Prospectively Predict Depression Severity, Cognition, Emotion Processing, and Emotion Regulation R21 MH121852-01 This study combines actigraphy with the smartphone app ‘BiAffect’ to understand digital behaviors, sleep, and circadian patterns on cognitive function and emotion processing in individuals with major depressive disorder or insomnia.    Clinical Cognitive Affective Neuroscience Lab Completed
Transdiagnostic Brain-Behavior Profiling to Enhance Cognitive Behavioral Therapy R01 MH112705-01  NIH/NIMH The study examined mechanisms of change that underlie CBT, and identify predictors of CBT response, in patients with major depressive disorder or social anxiety disorder. Clinical Cognitive Affective Neuroscience Lab Completed