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Hess, Christopher

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Christopher Hess, MD, PhD

Developing and translating biomedical imaging to diagnose and treat neurological disease

Dr. Hess’s research interests lie in the development and translational application of magnetic resonance imaging techniques for diagnosis and treatment monitoring in neurologic disease. His scientific background is in MRI acquisition, reconstruction and image analysis, focusing on diffusion and high-field MRI. His primary clinical interests are in neurovascular disease, dementia, brain development, and epilepsy.

Goodarzi, Hani

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Hani Goodarzi, PhD

Identification and characterization of key regulatory programs that underlie cancer progression

The Goodarzi laboratory employs a systems biological and multidisciplinary approach that integrates computational and experimental strategies to identify and characterize key regulatory programs that underlie cancer progression.

Arnaout, Rima

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Rima Arnaout, MD

Improving the resolution and accuracy of cardiovascular phenotypes to develop novel insights and therapies

Dr. Arnaout’s lab is currently developing computational methods to bring precision phenotyping to echocardiography, and also using the zebrafish animal model to study cardiovascular developmental gene function and to model human cardiovascular disease.

Raj, Ashish

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Ashish Raj, PhD

Mathematical modeling and data science in neurology and radiology

Ashish’s team develops novel image processing and analysis algorithms for MRI. His lab also works to model brain connectivity networks using graph theory, and investigates how these networks are disrupted with disease and trauma.

Baranzini, Sergio

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Sergio Baranzini, PhD

Genetics and molecular mechanisms underlying complex neurological disease

Dr Baranzini’s current research involves immunological studies using the EAE model, sequencing of whole genomes and transcriptomes from patients with multiple sclerosis and developing bioinformatics tools to integrate this information with that coming from other high throughput technologies. Dr Baranzini uses a combination of “wet lab” methods including DNA microarrays, proteomics, and laser capture microdissection, in combination with “dry lab” analytical approaches encompassing bioinformatics, complexity theory, and mathematical modeling.

Adler-Milstein, Julia

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Julia Adler-Milstein, PhD

Examining the use of IT in healthcare delivery

Dr. Adler-Milstein’s research assesses the progress of health IT adoption; the impact of such adoption on healthcare costs and quality; and the relationships between market, organizational, and team structure and health IT use. A core focus of her work is on health information exchange and interoperability.

Grinberg, Lea

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Lea Grinberg, MD, PhD

Computational approaches to imaging the human brain at the macro and micro level

The Grinberg Lab processes whole human brains for state-of-the-art quantitative histological analysis, digitize all of the results, and precisely registers to MRI. They are developing advanced tools for analysis of microscopic images that enable more comprehensive and higher-throughput studies of human brain tissue.

Brown, William

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William Brown, III, PhD, DrPH

Using informatics, mHealth, and New Media-based technologies to promote health among vulnerable populations and in underserved communities

Dr. Brown uses knowledge engineering, health informatics, comparative-effectiveness research, semantic harmonization, and integration of datasets (including EHR) to examine health disparities and develop patient-centered health information tools.

Sweet-Cordero, Alejandro

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Alejandro Sweet-Cordero, MD

Functional genomics to identify novel cancer therapeutics

The lab seeks to discover new therapeutic approaches to target the genetic mutations and altered signaling networks that are specific to cancer cells. Using functional genomics applied to mouse and human systems, we work to understand the transcriptional networks that regulate the outcome of specific oncogenic mutations and to understand how cancers become resistant to chemotherapy. This work relies heavily on computational genomic analysis, generating and using high-throughput datasets and next-generation sequencing for gene and network discovery. Our primary disease focus is lung cancer and pediatric sarcomas.

Kober, Kord

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Kord Kober, PhD

‘Omics data to understand mechanisms underlying common symptoms in chronic conditions

Dr. Kober uses ‘omics data (i.e., genotype and expression arrays, DNAseq — genome, exome, RNAseq, methylation arrays) to improve our understanding of the molecular mechanisms underlying common symptoms (e.g., fatigue, pain) or treatment failure experienced by patients with chronic medical conditions (e.g., cancer, HIV infection).

Tosun, Duygu

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Duygu Tosun, PhD

Developing algorithmic approaches for multi-modal data analysis

Dr. Tosun develops new algorithmic approaches for processing and analysis of multi-disciplinary/modal data including neuroimages, genetics, proteomics, as well as cognitive functioning measures in a unified framework. The primary aim is to identify multi-disciplinary/modality biomarkers for detecting the changes associated with disease specific neuropathology, improving understanding of pathophysiological progression and potentially providing a means of monitoring the efficacy and regional specificity of drug therapy for neurodegenerative diseases.

Majumdar, Sharmila

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Sharmila Majumdar, PhD

Developing image processing and analytics for musculoskeletal research

Dr. Majumdar’s research work on imaging, particularly magnetic resonance and micro computed tomography, and development of image processing and analysis tools, has been focused in the areas of osteoporosis, osteo-arthritis and lower back pain. Her research is diverse, ranging from technical development to clinical trials.

Nagarajan, Srikantan

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Srikantan Nagarajan, PhD

Brain imaging analysis and brain computer interfaces for diagnosis and assessment in various patient populations

Dr. Nagarajan has multiple research interests, including understanding human brain plasticity associated with learning and disease, and determining neural mechanisms of controlling speech. He focuses on the development and refinement of multimodal structural and functional brain imaging and brain computer interfaces, for diagnosis and assessment in various patient populations. His current translational research program includes conducting multimodal brain imaging studies in people with Autism, Dementia, Tinnitus, Brain Tumors, Epilepsy, Traumatic Brain Injury, Stroke and Voice Disorders.

Lupo, Janine

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Janine Lupo, PhD

Developing novel methods for MRI data collection and analysis in neurological research

Dr. Lupo is focused on developing novel methods for acquisition, reconstruction, post-processing, and quantitative analysis of magnetic resonance brain images. Using a combination of multiparametric structural, physiological, and metabolic MRI techniques, her goal is to quantitatively characterize heterogeneity within malignant brain tumors, monitor response to novel treatment regimens, and investigate the long-term effects of therapy on healthy brain tissue structure and cognitive function. Many of the methodologies we develop initially to evaluate patients with brain tumors are also being applied to other neurological diseases.

Xu, Duan

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Duan Xu, PhD

Developing new MRI techniques

Dr. Xu’s research focuses on investigating new MRI techniques with primary applications in pediatric neuroradiology. Another research focus is the development of new techniques on ultrahigh field MR scanners for small animal imaging, both in vivo and ex vivo. Techniques include high resolution MR anatomic, diffusion, and spectroscopy are being developed in collaboration with various colleagues in Neurodevelopment Biology, Neurology, Pediatrics, Neonatology, and Physiology.

Kalendarian, Elsbeth

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Elsbeth Kalendarian, DDS, MPH, PhD

Developing electronic dental health records for the information age

Elsbeth works on development and implementation of the Dental Diagnostic System (DDS) in EHR, and is providing leadership in the creation of international standards in dental health records.

Lazar, Ann

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Ann Lazar, MS, PhD

A Tailored Approach to Reducing Oral Health Disparities

Dr. Lazar is working to develop an analysis framework and software tools to help understand how patient characteristics interact with dental treatments in order to improve treatment decisions for individual patients and develop targeted treatments to reduce oral health disparities.

Blum, Michael

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Michael Blum, MD

Cardiology and Digital Health Technology

Dr. Blum is a cardiologist who specializes in the care of patients with congestive heart failure, valvular heart disease and preventative cardiology. He is dedicated to the early detection of heart disease and prevention through a heart-healthy lifestyle that includes diet, exercise and stress reduction. He has a special research interest in clinical decision support technology, social media and collaborative workspaces and their impact on the quality, effectiveness, and cost of care delivery.

Gansky, Stuart

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Stuart Gansky, MS, DrPH

Oral health and health disparities

Dr. Gansky’s research concentrates on oral health, health disparities, applied statistical analyses and related method­ological issues. Balancing these components is essential to successful and practical population health research. Methodological examination helps ground health research and build convincing argu­ments, while collaborative health research generates opportunities for innovative statistical practice and provides challenges for developing ways to solve real world problems.

Jain, Ajay

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Ajay Jain, PhD

Predictive computational modeling focused on algorithmic approaches for drug discovery

The Jain lab focuses on computational chemistry and computational biology. The primary research areas are in structure-based drug discovery, rational approaches for predictive pharmacology, and applications involved in cancer. Researchers at academic and non-profit institutions are encouraged to download and make use of our software.

Sim, Ida

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Ida Sim, PhD, MD

Developing infrastructure to enable the translation of clinical and mobile data into knowledge to improve health

Dr. Sim’s group works to create an open software architecture that provides shared analysis, data presentation, and evaluation modules to support systematic and shared learning in mobile health. She also leads international efforts to build a single global portal for sharing individual participant-level data from clinical trials.

Segal, Mark

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Mark Segal, PhD

Development and application of statistical methods to address problems in computational biology and genomics

Dr. Segal has devised methods for addressing several aspects of analyzing data deriving from high-throughput biotechnologies, straddling low-level (e.g., pre-processing) to high-level (e.g., linked survival phenotypes, regulatory module elicitation) approaches. He is currently engaged in developing and comparing methods for inferring 3D genome architecture utilizing data from chromatin conformation capture assays.

Seeley, William

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William Seeley, MD

Selective vulnerability in neurodegenerative disease

The Seeley Lab uses advanced neuroimaging techniques to map the specific neural networks and regions targeted early in each neurodegenerative disease. The patterns of network- and region-level vulnerability serve as maps for exploring cellular and molecular pathogenesis with quantitative neuropathological approaches. The lab’s research relies on the visualization and analysis of very large datasets using increasingly sophisticated modeling approaches. Overall, the lab seeks to clarify mechanisms of selective vulnerability and disease progression in order to develop novel therapeutic strategies and tools for monitoring change in patients during life.

Pollard, Katherine

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Katherine Pollard, PhD

Developing statistical and computational methods for the analysis of massive genomic datasets

Dr. Pollard’s group aims to identify specific DNA alterations that are responsible for novel functionality, such as variation in gene expression.

Shoichet, Brian

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Brian Shoichet, PhD

Discovering reagents to modulate G-Protein Coupled Receptors (GPCRs)

The Shoichet lab seeks to bring chemical reagents to biology, combining computation and experiment. In a protein-centric approach, molecular docking, they discover new ligands that complement protein structures. Using a ligand-centric approach, they discover new targets for known drugs and reagents.

Douglas, Shawn

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Shawn Douglas, PhD

Novel Tools and Devices at Nanoscale and Finer

Recognizing that the elements of life are at angstrom-scale, the Douglas lab aims to create the computational building blocks for a new generation of therapies and devices.

Sirota, Marina

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Marina Sirota, PhD

Data Science in Disease Diagnosis and Treatment

The Sirota lab develops incremental computational methods in the context of disease diagnostics and therapeutics – especially leveraging ‘omics and clinical data to better understand the role of the immune system.

Ye, Jimmie

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Jimmie Ye, PhD

Building new experimental and computational approaches to generate and interpret human biological data

This collaborative team of data scientists, computational biologists and genome detectives, have a shared vision —a fundamental understanding of human biology with an eye to improving human health. See website

Keiser, Michael

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Michael Keiser, PhD

Small molecule therapeutics with protein network perturbations

In classical pharmacology, drugs struck single notes, where one drug would hit one target to treat one disease. But drugs frequently modulate entire target “chords” at once, and this can be essential to their action. The Keiser lab is decoding this molecular music, both in terms of new and useful chords for the treatment of complex diseases, and also to identify the jarring notes that existing drugs unintentionally hit when they induce side effects. Michael is also uncovering the biological roots of Alzheimer’s disease.

Altschuler, Steven and Wu, Lani

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Steven Altschuler, PhD and Lani Wu, PhD

Fundamentals in Cellular Heterogeneity Using Quantitative Techniques

The Altschuler-Wu lab investigates fundamental questions about the origins and impact of cellular heterogeneity in collective cellular decision making, tissue development and homeostasis. Results from our studies are applied to investigate mechanisms of drug resistance, cancer evolution and new therapeutic strategies. A common theme is the combined use of single-cell perturbation assays, quantitative imaging, data-driven modeling and theory.

Butte, Atul

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Atul Butte, MD, PhD

A New Frontier of Problems Relevant to Genomic Medicine

The Butte lab builds tools in translational bioinformatics to make sense of big ‘omics and clinical data and solve new classes of problems in Oncology.

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