Engineering Health

We aim to establish mathematical models, quantitative criteria, and algorithmic/computational foundations toward their implementations in robotics (for design and control), biomechanical systems (for prediction and analysis), and their intersections such as lower-body wearable robots.

Taking advantage of state-of-art nanotechnologies and fabricating fascinating functional biomaterials and integrated biosystems, the Professor Weiqiang Chen’s laboratory addresses numerous important problems in fundamental biology as well as clinical applications in disease diagnosis and treatment.

Levicky Group — The Bio-interfacial Engineering and Diagnostics Group’s research focuses on quantitative characterization of biomolecular interactions, with technological connections to diagnostics for medical and fundamental biology applications. The group seeks to dissect the fundamental equilibrium and kinetic aspects of biomolecular reactions at surfaces and in solution, elucidate the role played by the molecular organization, and apply this understanding to advance bioanalytical technologies.

The overarching goal of our research is to develop the principles needed to incorporate unstructured, Internet and mobile data into a better understanding of population-level health. We primarily develop computational methods across data mining, natural language processing, and machine learning to generate features for spatio-temporal population-level public health models.

Professor Andreas Hielscher’s team focuses on developing clinically relevant optical tomographic imaging systems. They apply these devices and wearable electronics to the diagnosis and treatment of various diseases, such as breast cancer, arthritis, peripheral artery disease, diabetic foot syndrome, and real-time monitoring of brain activities.

Professor Rose Faghih group develops biomedical signal processing and control algorithms for human-technology interactions and monitoring. These state-of-the-art tools are employed for prognosis, diagnosis, and treatment of pathological conditions related to neuro-endocrine and neuro-psychiatric disorders.

The Digital Health Work initiative is an interdisciplinary research program at NYU that brings together technological, organizational and medical innovations toward a healthy and resilient society, and an inclusive healthcare workforce.

Professor Maurizio Porfiri’s group conducts multidisciplinary research in the theory and application of dynamical systems, motivated by the objectives of advancing engineering science and improving society. Their theoretical expertise is in controls, networks, nonlinear dynamics, and time-series, while our application domain is in modeling and analysis of physical, social, and technical systems.

Todd Hudson is a computational neuroscientist whose research focuses on modeling sensory and motor systems, particularly eye and arm movements in healthy and disease states. He received his training at the Clarence Graham Memorial Laboratory of Visual Science at Columbia University, and co-founded Tactile Navigation Tools, LLC, a company that develops navigation aids for the visually impaired.

Professor Khalil Ramadi and his team develop innovative approaches for the modulation of neural activity throughout the body. The goal is to come up with novel therapies for neurologic, metabolic, and immune disorders. They combine mechanical, electrical, materials, and bio-engineering toolkits in the design of minimally invasive technologies.

Personalized immunotherapies involving CAR T cells, TCRs and BiTEs, have revolutionized the treatment of cancer. They provide in cures in subsets of cancer patients, yet remain ineffective for the majority of patients. Prof. Mark Yarmarkovich aims to expand the use of curative immunotherapies. To this end, his group develops and employ technologies at the intersection of genomics, proteomics, immunology, antibody engineering and computational biology.

Professor Ruggles’ laboratory focuses on understanding human health and biology using data science, data visualization, and predictive modeling. A primary goal of this research is to analyze and integrate diverse data modalities, including bulk and single-cell sequencing, phospho- and global- proteomics, metagenomics, flow cytometry, imaging, and clinical data. These multi-omic methods are used to better understand cancer, heart diseases, and other disorders.

We focus on engineering macromolecules. We aim to predictably design or engineer artificial therapeutics, biocatalysts, scaffolds and cells.

Our lab designs, develops, and applies nanoscale and bioengineering tools to understand and manipulate cell fate and function. Our ultimate goal is to help the body regenerate better.

The NanoBioX initiative at NYU stimulates fundamental research and technological innovation at the intersection of nanotechnology, biomedical research, and data science.

The aim of Dr. Chklovskii’s research is to understand how the brain analyzes large and complex datasets streamed by sensory organs. Informed by anatomical and physiological neuroscience data, his group develops algorithms that model brain computation and solve machine learning tasks. The overarching goal it to build artificial neural systems and treating mental illness.

The team of Professor Shy Shoham works at the interface of neuroscience and engineering, developing and applying modern bidirectional neural interfaces for observing and controlling neural population activity patterns. Their goal is to better understand sensory-motor information coding and to advance medical neurotechnology.

Kevin Chan and his group are developing and applying new methods for noninvasive imaging of neurodegeneration, neurodevelopment, neuroplasticity, and neuroregeneration in people with vision-related diseases and injuries. They study the structural, metabolic, physiological, and functional relationships between the eyes, brain, and behavior with the mission to improve vision.

Research activities in Professor Yao Wang’s group deal with encoding and distributing videos among a large number of users. Of special interest are diverse network access links and applications to biomedical imaging. The lab collaborates extensively with other research groups in wireless communication and networking at the School of Engineering and NYU’s medical school and hospitals.

The human experience of pain is incredibly complex. Understanding how pain affects patients, and how best to manage it, is Prof. Jing Wang’s goal. His research interest is centered on the role of brain circuits in the regulation of acute and chronic pain. Of particular interest are the cortical mechanisms of pain processing and regulation.

Every day, our brains cycle through different states of awareness: from the rich conscious experiences during wakefulness to dreamless sleep to the bizarre experiences during dreaming sleep. Understanding the neural basis of conscious awareness is the basic goal of Prof. Biyu He’s team. She is using a combination functional magnetic resonance imaging (fMRI), magneto- encephalography (MEG) and invasive electrophysiology to explore relevant neural mechanisms and characterize various neuropsychiatric illnesses.

The primary objective of Professor Kenichiro Kamei’s lab is to revolutionize the field of biomedical engineering by reconstructing complete human and animal bodies using cutting-edge engineering techniques. A prime example of their work is the development of the “Body on a Chip” (BoC) system, which simulates physiological and pathological conditions of living organisms in vitro. This work has far-reaching implications for drug discovery and regenerative medicine.

Advances in miniaturized sensors and actuators, as well as artificial intelligence (AI), have broadened horizons for assistive and rehabilitative technologies. The team of Professor JohnRoss Rizzo, MD, is leveraging these innovations to help patients with conditions such as blindness and stroke, enhancing their ability to interact physically with their environment.

In the laboratory of Professor Ivan Selesnick, PhD, researchers are interested in digital signal processing, sparsity in signal processing, and multi-dimensional wavelet-based signal/image/video processing. They develop new methods for signal filtering, separation, and deconvolution, especially in the area of biomedical imaging.

How is language produced and perceived in the human brain? What are the network dynamics that allow us to fluently communicate? These questions are still poorly understood and collaborations between scientists, clinicians, and engineers are crucial for making progress in this fascinating field. Adeen Flinker and his team are using unique human neurosurgical recordings and advanced data processing algorithms to elucidate these questions.

Tissue maintenance and regeneration are crucial for preserving tissue functionality and organismal health. With age and disease, both of these processes can become inefficient. Professor Wosczyna’s laboratory seeks to identify cellular mechanisms that are responsible for pathological phenotypes. They look for molecular targets that can be modified to extend tissue functionality further into age.