Research Labs and Funded Projects

Funded Research Projects

Capacity Building for Trustworthy AI in Medical Systems (TAIMS)

The TAIMS research project, funded by an NSF Expanding AI Innovation through Capacity Building and Partnerships grant, is a stepping stone towards building an artificial intelligence institute at Meharry Medical College devoted to foundational and use-inspired advances in Trustworthy AI in Medical Systems.

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Research Labs

Meharry SACS’s research labs serve as expertise areas that reflect faculty interest and strengths. Labs are tied to the classroom, supporting a practical approach to learning, via individual and group projects, that is important to the School’s curriculum.

The following research labs are intentionally multidisciplinary to align with other wet experimental labs or research interests across Meharry’s schools.

Advanced Computing and Analytics Laboratory | Climate Change and Health Intelligence Lab | Clinical Trials and Outcomes Innovation Lab | Data-driven Intelligence and Security for Cyber-physical Systems (DISCS) Lab | Genomics Lab | Geographic Information Systems (GIS) and Visualization Lab | L’OMAR – Laboratory of Omics Mining and Algorithmic Reasoning | mHealth Wearable Sensors Lab | Population Health Informatics and Disparities Research Lab (PHIDRL) | Saha RESONANCE Lab

Advanced Computing and Analytics Laboratory

The Advanced Computing and Analytics Lab (ACAL) is an open access, gathering and collaborative workspace for student success. In this lab, our students work with faculty, researchers, industry experts and other technology thought leaders.

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Climate Change and Health Intelligence Lab

The focus of the Climate Change and Health Intelligence Lab is applying data mining and machine learning to climate change resilience and health intelligence. Specific applications include, but are not limited to, computer vision, natural language processing, time-series analysis and anomaly detection.

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Clinical Trials and Outcomes Innovation Lab

At the Clinical Trials and Outcomes Innovation Lab, under the leadership of Dr. Ashutosh Singhal, we integrate cutting-edge data science methodologies with clinical research to advance health care outcomes. Our mission is twofold: to conduct rigorous clinical trials aimed at improving patient care and to leverage data-driven approaches to address complex health care challenges. We are dedicated to promoting health equity and increasing minority participation in clinical trials through innovative data-driven strategies.

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Data-driven Intelligence and Security for Cyber-physical Systems (DISCS) Lab

Data-driven Intelligence and Security for Cyber-physical Systems (DISCS) Lab, primarily focuses on designing and developing secure AI-based smart cyber-infrastructure for healthcare systems. The lab integrates software-defined networking (SDN), 5G, edge, fog, and cloud technologies along with AI tools for providing efficient and secure data communication and processing for intelligent healthcare and cyber-physical systems.

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Genomics Lab

The focus of the genomics lab is to develop novel next-generation sequencing methods to identify genomic aberrations that cause disease or drug resistance and use our expertise to serve Meharry and the broader scientific community.


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Geographic Information Systems (GIS) and Visualization Lab

The Geographic Information Systems and Visualization Lab applies geospatial and remote sensing data modeling to health care. Faculty explore coverage gaps in population health, climate change effects, and develop algorithms that provide insights and innovative solutions that lead to improved health outcomes, increase accessibility to health care, and healthier communities.

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L’OMAR – Laboratory of Omics Mining and Algorithmic Reasoning

The primary focus of L’OMAR is mining omics (aka multi-omics) data such as genomics (DNA), transcriptomics (RNA), proteomics (proteins), metabolomics (metabolites), metagenomics (microbiomes) etc. to understand human biology computationally. L’OMAR develops algorithmic reasoning techniques leveraging artificial intelligence (AI), machine learning, deep learning and natural language processing (NLP) emphasizing on explanations (XAI) to the predictions and decisions an AI-agent may bring in 1) understanding the biology of diseases, 2) identifying promising drug-targets and drug molecules, and 3) repurposing existing drugs for drawing faster response against future pandemic.

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mHealth Wearable Sensors Lab

The focus of mHealth Wearable Sensors Lab is to design mHealth systems and develop computational methods for efficient processing of multimodal data streams generated from these systems, to produce early insights of life-threating diseases, and provide personalized care to patients. The overarching goal of this lab is to leverage the power of digital health devices (i.e., mHealth apps, wearable devices) to measure an individual’s physiological, psychological, social and environmental state and utilize that information for early diagnosis and prevention of complex human diseases.

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Population Health Informatics and Disparities Research Lab (PHIDRL)

The PHIDRL seeks to address health disparities and predict patient health outcomes with the desire to help patient health outcome improvement. The lab pursues health informatics and machine learning pipelines leveraging multi-modality data to identify patient at risk of severe health outcomes. Current research involves substance use disorders, mental health disorders, maternal health, and cardiovascular conditions among underserved patient population, specifically, to identify social determinant of health factors that are associated with adverse health outcomes.

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Saha RESONANCE Lab

The vision of the RESONANCE Lab is to manage chronic diseases with equitable digital technologies. The lab’s two major research directions are to develop easily accessible and cost-effect technologies that enable self-care management for patients and to understand social and racial disparities in the diagnosis, monitoring and treatment of chronic diseases

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Our research labs are intentionally multidisciplinary to align with other wet experimental labs or research interests across Meharry’s schools.