Advanced Research Core

Apply Yourself In Applied Research

In our Advanced Research Core program, you can participate in applications-oriented, graduate-level research projects with the NYIT College of Osteopathic Medicine (NYITCOM). Work under the mentorship of a NYITCOM faculty member as you provide technical assistance and intellectual input.

Create Knowledge, Make A Difference

If you’re ready to demonstrate high levels of commitment and dedication, the Advanced Research Core (ARC) program is a pathway to a unique educational experience. Work with faculty at the NYIT College of Osteopathic Medicine (NYITCOM) to support their medical research projects. Be part of the discovery process and actually create knowledge as you help unlock new findings. Work as part of a team while performing basic or applied research. Many ARC projects are published in peer-reviewed journals and presented at national conferences.

Expectations & Opportunities

You will be expected to contribute at least eight hours per week toward your ARC project. In addition, NYITCOM faculty may have specific requirements for their research. You will also have the opportunity to participate in New York Institute of Technology’s Symposium of University Research and Creative Expression (SOURCE), and present findings to member of the New York Tech community.

Eligibility Requirements

  • Grade of B or higher in General Biology I & II and General Chemistry I & II
  • Demonstrated interest and dedication to research
  • Preferred majors include life sciences, biotechnology, physical therapy, physician assistant studies, occupational therapy, and nursing

Faculty Research

Research must be performed in a manner consistent with university COVID-19 guidelines.

Qiangrong Liang

We study the role of mitochondrial quality control mechanisms in diabetes-induced heart failure.

Michael Granatosky

Using bio-inspired robotics to explore the evolutionary origins of gait. Mechanically, there is an almost infinite combination of ways a quadrupedal animal can coordinate its limb movements and timing to achieve an effective gait. However, a survey of living quadrupedal animals reveals only a limited number of limb coordination patterns. My lab seeks to understand why animals are limited in the way they use their limbs by using a bio-inspired robot that accurately matches the movements of a blue-tongued skink (Tiliqua scincoides). Blue-tongued skinks are remarkable model systems to explore the evolutionary origins of quadrupedal gaits because they are often utilized as an anatomical representative of early tetrapods and use a combination of “belly-dragging” and “high-stepping” steps while walking. However, the use of a bio-inspired robot allows us to alter aspects of the anatomy and motor control and directly assess how these changes alter overall system energetics and stability. Such manipulation is not possible with living animals. Students should have some experience with coding in C, C++, MATLAB, or Python.

Akinobu Watanabe

Reptile Skull Shape Evolution: From lizards to snakes, how did reptiles evolve diverse skull shapes? This project will involve processing 3D skull models of reptiles reconstructed from CT and surface scan data and mathematically quantifying the shape of skulls through the use of high-density morphometric techniques. These shape data will then be combined to a larger collaborative work investigating skull evolution across all reptiles and birds. Prerequisites: none but ability to quickly learn new programs and basic familiarity with local and cloud storage (e.g., Google Drive, Dropbox) are preferred.

Chicken Skull and Brain Shape Development: How do brains and skulls interact during development? This project involves reconstructing high-resolution 3D models of skulls and brains from micro-CT scans of chickens, a model system used for studying craniofacial development. Subsequently, high-density shape analysis will be used to mathematically quantify and model shape changes that occur from late embryonic to adult stages in chickens. Prerequisites: none but ability to quickly learn new programs and basic familiarity with local and cloud storage (e.g., Google Drive, Dropbox) are preferred.

Isaac Kurtzer

The projects will examine how human subjects quickly select about different movement options. We have previous shown that subjects automatically prefer the nearest of two options. Here will explore the relative importance of of stimulus information which is important for directing the eyes during visual search (e.g.color) but may not impact arm selection. The project will require collecting data from human subjects as they interact with a programmable robot device. I would accept one student and would much prefer someone with a background in programming.

Weikang Cai

Astrocytes respond to external signals to modulate brain metabolism, neuronal activity, and behavior. The main research interest of our laboratory is to understand how these astrocyte-originated responses may affect the progression of several neurological disorders, including depression, neurodegenerative diseases, and painful diabetic neuropathy. The students are expected to assist on data acquisition and analysis from both cell and animal studies.

Randy Stout

We will use high resolution microscopy to study the gap junctions between astrocytes. Gap junction connections serve as connections between astrocytes and they are critical for normal brain function. Most of the work will be computer-based to analyze microscopy data and use imaging results to build computational simulations.

Haotian Zhao

The outcomes of many childhood brain cancers remain dismal, leaving patients vulnerable to devastating consequences. Our research is aimed at a better understanding of the biology of these cancers in order to develop safer and more effective therapies.

ARC Application Spring 2020

Contact Us

Navin Pokala, Ph.D.
Assistant Professor
Department of Biological and Chemical Sciences
516.686.7771
navin.pokala@nyit.edu

Kurt Amsler, Ph.D.
Professor and Associate Dean for Research
Department of Biomedical Sciences
kamsler@nyit.edu