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Biomedical Informatics and Health AI (BMAI)

Faculty Listing

   
Ahmed, Zeeshan 
zahmed@ifh.rutgers.edu
Assistant Professor –Rutgers Robert Wood Johnson Medical School (RWJMS)-  Tenure Track @ Rutgers Health.Department of Medicine, Division of Cardiovascular Diseases and Hypertension  / Core Faculty Member Rutgers Institute for Health, Health Care Policy and Aging Research (IFH) Rutgers The State University of New Jersey. Our broad goal is the implementation of artificial intelligence (AI) and machine learning (ML) applications to support translational research and precision medicine. More specifically, we implement innovative AI/ML techniques to discover novel biomarkers and predict disease susceptibility using multimodal data.
Anat Kreimer 
kreimer@cabm.rutgers.edu
Assistant Professor - Robert Wood Johnson Medical School (RWJMS)- Department of Biochemistry and Molecular Biology The Kreimer Lab develops predictive models of transcriptional regulation by integrating large-scale genomic datasets to understand how regulatory elements act in specific conditions, cell types, and tissues. By combining computational modeling with high-throughput experimental approaches, the lab aims to uncover the interactions and mechanisms through which genetic variation in non-coding regions influences gene regulation and drives human disease.
Beeri, Michal Schnaider 
mbeeri@ifh.rutgers.edu 
Professor - Robert Wood Johnson Hospital - Neurology . Director, Herbert and Jacqueline Krieger Klein Alzheimer's Research Center at Rutgers Univeristy   


Research statement: Our research focuses on leveraging large-scale longitudinal cohorts that are deeply characterized with granular digital, behavioral, EEG, MRI, and biomarker data to enable early ascertainment of cognitive decline and dementia. We use these rich datasets to monitor disease progression, assess response and risk for adverse events from new medications, and discover novel drug targets for Alzheimer's disease and related dementias.

Chen, Helen 
hc1181@sn.rutgers.edu
Assistant Professor - Rutgers School of Nursing - Division of Nursing Science  Digital health integration to reduce therapeutic inertia in primary care diabetes management through contextualized continuous glucose monitoring reports and mobile health interventions for patients with type 2 diabetes.
Daneault, Jean Francois 
jf.daneault@rutgers.edu
Associate Professor - Rutgers School of Health Professions- Rehabilitation and Movement Sciences Computational and digital health approaches to the management of chronic neurological disorders.
Francis, Ellen 
ellen.francis@rutgers.edu
Assistant Professor -Rutgers School of Public Health -Department of Biostatistics and Epidemiology Pregnancy complications are heterogeneous syndromes with lasting consequences for women and their children. Our lab uses metabolomics to identify metabolic pathways underlying interrelated disorders such as gestational diabetes and hypertensive disorders of pregnancy. We integrate these molecular signatures with clinical markers to identify mechanistically distinct subtypes, improve risk prediction, and understand how pregnancy unveils long-term cardiometabolic vulnerability. Our goal is to inform precision prevention, diagnosis, and prognosis for maternal and child health.
Holmes, Avram 
avram.holmes@rutgers.edu
Associate Professor of Psychiatry - Center for Advanced Human Brain Imaging Research Dr. Holmes' lab studies the fundamental organization of large-scale human brain networks, with a particular focus on higher-level cognition and the intersection of emotion and cognition. Using a multi-scale approach, the lab studies phenomena across levels, from genes and molecules through cells, circuits, networks, and behavior
Johnson, Evan 
wj183@njms.rutgers.edu
Professor -  Rutgers New Jersey Medical School (NJMS) - Division of Infectious Disease, Department of Medicine, Director - Rutgers New Jersey Medical School (NJMS) - Center for Data Science  Data Science, Bioinformatics, and Machine Learning/AI in -omics datasets. Applying our work in infectious disease, cancer, the microbiome, and host-microbe interactions, with a strong focus on TB research. Using ML/AI to integrate complex multi-modal datasets to understand mechanisms and make precision predictions for diseases etiology, prognosis, and treatment.   
Kachroo, Priya 
pk784@shp.rutgers.edu
Assistant Professor - Rutgers School of Health Professions- Department of Health Informatics  Dr. Kachroo leverages machine learning and multi-omic data (genomics, metabolomics, DNA-methylation) to uncover biomarkers and molecular pathways of chronic inflammatory diseases, with a particular focus on respiratory and cardiovascular conditions. She aims to translate computational insights into precision medicine interventions.
Kotsakis, Georgios 
gk567@sdm.rutgers.edu
Professor of Oral Biology - Rutgers School of Dental Medicine, Assistant Dean for Clinical Research - Rutgers School of Dental Medicine  Development of novel machine learning classifiers for population surveillance of periodontitis
Mitrofanova, Antonina 
amitrofa@shp.rutgers.edu

Associate Professor, Health Informatics, Associate Dean for Reseach, Deputy Director BMIHAI Center, IFH 

  Algorithms development, network-based models, mechanism-centric models, machine learning in cancer progression and treatment response
Olarerin-Geroge, Anthony
aolarerin@njms.rutgers.edu
Assistant Professor - Rutgers New Jersey Medical School - Department of Pharmacology, Physiology and Neuroscience Function and regulation of RNA modifications using molecular and computational biology tools;  rRNA functional genomics; CRISPR technology development.
Rawal, Shristi 
shristi.rawal@rutgers.edu
Associate Professor -Rutgers School of Health Professions - Department of Clinical and Preventative Nutrition Science My work centers on advancing cardiometabolic health through epidemiology, implementation science, and mobile health solutions, with special emphasis on pregnancy. I leverage wearable sensors, remote monitoring, and user-centered digital interventions to address complications such as gestational diabetes and hypertensive disorders in pregnancy, as well as to support healthy lifestyle behaviors and cardiometabolic risk reduction in non-pregnant populations, including individuals with Down syndrome.
Saleh, Soha 
salehsh@shp.rutgers.edu
Assistant Professor, Rutgers School of Health Professions - Departmentment of Rehabilitation and Movement Sciences. Assistant Professor - Rutgers Robert Wood Johnson Medical School (RWJMS)- Department of Neurology Dr. Saleh’s research focuses on understanding neural networks involved in motor learning and control, as well as neuroplasticity in individuals with motor and cognitive deficits. Her work uses a multidisciplinary approach that combines structural and functional neuroimaging, electrophysiological techniques, and behavioral assessments, along with advanced signal processing and computational analysis. She examines cognitive-motor interactions and uses neuromodulation strategies to boost neuroplasticity. A key part of her research involves using machine learning and artificial intelligence to create predictive models for recovery patterns and treatment responses with the goal of developing personalized rehabilitation interventions.
Saligan, Leorey N 
ls1684@sn.rutgers.edu
Professor and Vice Dean of Research - Rutgers School of Nursing - Division of Nursing Science Multi-modal approaches to identify mechanisms that influence chronicity and progression of symptoms experienced by individuals with chronic illnesses.
Starkweather, Angela R 
as5303@sn.rutgers.edu  
Dean, School of Nursing  Mechanisms of the transition from acute to chronic pain and comorbid symptoms (anxiety, depression, fatigue, sleep disturbance, cognitive deficits) and development of interventions to reduce the risk of chronicity
Toosizadeh, Nima 
nt496@shp.rutgers.edu
Associate Professor - Rutgers School of Health Professions- Rehabilitation and Movement Sciences Our research integrates biomechanical modeling, signal processing, and machine-learning methodologies with state-of-the-art body-worn sensor technologies (IMU, EMG, ECG, EEG, and fNIRS) to evaluate aging-related conditions and syndromes, including frailty, cognitive impairment, and susceptibility to falls.
Wages, Nathan 
nw369@shp.rutgers.edu
Assistant Professor - Rutgers School of Health Professions - Rehabilitation and Movement Sciences  His work focuses on utilizing pragmatic approaches (e.g., combining human motor unit/neuron recordings with computational modeling) to identify neural, muscular, & sensorimotor mechanisms of weakness, physical function/mobility limitations, & fatigue with aging, injury, illness, & neurodegenerative disease.
Zhang, Lanjing 
lanjing.zhang@rutgers.edu
Research Professor  - Rutgers Ernest Mario School of Pharmacy - Department of Chemical Biology To improve the methodology of AI/machine learning on biology and population health and understand biomarkers and computational biology of cancer and digestive diseases.

 

 

 

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