By: Eli Freund, Editorial Communications Manager, UConn School of Engineering
Four UConn Engineering professors received Faculty Early Career Development Awards from the National Science Foundation this year, one of the highest honors a junior science or engineering faculty member can receive.
The NSF Faculty Early Career Development (CAREER) Program supports early-career faculty who have the potential to serve as academic role models in research and education, and to lead advances in the mission of their department or organization. Activities pursued by early-career faculty build a firm foundation for a lifetime of leadership in integrating education and research.
The recipients for 2019 are as follows:
Yupeng Chen, associate professor of biomedical engineering, received $480,625 over four years for his project, “Assembly of Nanopieces for Controlled Penetration and Binding of Difficult-to-Reach Cartilage Matrix for siRNA Therapy against Osteoarthritis.”
Chen will center his research on Osteoarthritis (OA), which affects approximately 13.9 percent of Americans aged 25 years and older. This equates to an estimated 30 million people in the United States, making it one of the leading causes of disability. OA is a degenerative joint disease involving in the degeneration of joint cartilage. This leads to pain, stiffness, movement problems, and activity limitations. Currently, there is no clinically successful therapeutic to against OA. As a Nobel-prize winning discovery, siRNA can effectively and specifically inhibit disease gene expression, which provides a great therapeutic potential to treat OA. However, it is extremely challenging to deliver negatively-charged siRNAs to infiltrate avascular, dense, negatively-charged tissue matrix, such as cartilage. This research will develop a novel delivery vehicle, which can self-assemble with therapeutic siRNAs and deliver them into matrix-rich tissues in an effective and safe manner.
Bin Feng, assistant professor of biomedical engineering, received $549,656 over five years, for his project, “Understanding Peripheral Neuromodulation to Enhance Non-drug Management of Chronic Pain.”
For his research, Feng will look at chronic pain, its treatment with prescribed opioids, and curbing the current epidemic of prescription opioid abuse, which costs $500 billion annually in medical, economic, social and criminal ramifications.
According to Feng’s research description, the most serious side effects of opioids, including physical dependence and addiction, arise from unintended effects on the central nervous system (CNS). Pain is generally evoked from the periphery and thus targeting the peripheral nervous system (PNS) could alleviate pain without unintended CNS effects. However, drug-based treatments to selectively target the PNS remain largely unsuccessful. Peripheral neuromodulation treats chronic pain by focused delivery of physical energy (usually electrical current) to PNS tissues. However, current peripheral neuromodulation methods are unpredictable and only benefit a fraction of chronic pain patients. This project aims to develop novel experimental and computational tools to advance our mechanistic understanding of peripheral neuromodulation, and thus will provide new experimental and theoretical data to improve neuromodulation for benefiting a broader patient population with chronic pain.
Sabato Santaniello, assistant professor of biomedical engineering, received $500,000 over five years for his project, “Robust Identification and Multi-Objective Control Methods for Neuronal Networks Under Uncertainty.”
According to Santaniello, the control of biological neural networks underpins the development of minimally-invasive brain therapies as well as adaptive learning for cyber-physical systems, but it remains challenging because of the irregular dynamics involved. These systems also have sparse and weak connections and a range of dynamics that cannot be fully probed. There is an urgent need to determine the impact of unmodeled dynamics on the controllability of these networks and develop robust controls accordingly, otherwise controllers will remain underperforming, fragile, and hard to calibrate. This is the case for deep brain stimulation (DBS), which follows a conservative “one-size-fits-all” paradigm and remains underutilized despite having the potential to treat millions of people worldwide. The objective of this CAREER program is to develop identification methods that estimate the impact of unmodeled dynamics on neuronal circuits and a robust control framework for these circuits. Brain circuits targeted by Parkinson’s disease and DBS will be considered to maximize the impact of the research.
Julia Valla, assistant professor of chemical and biomolecular engineering, received $500,000 over five years for her project, “Revolutionizing sulfur removal in transportation fuels via adsorption in ion exchanged zeolites.”
Valla’s research will look to aid the fuel processing industry, which faces mandatory government- and industry-issued standards that require the reduction of sulfur in transportation fuels (e.g., gasoline, diesel, and jet fuels) to near-zero levels. Hydrodesulfurization (HDS) is the widely-accepted commercial refinery technology used for the removal of sulfur in fuels. Although HDS is effective for this purpose, it is also energy intensive, particularly as refineries attempt to meet tighter regulatory standards of sulfur. This project will establish a new technological platform and associated fundamental science enabling the development of environment-friendly “filters” for the efficient and cost-effective adsorptive desulfurization (ADS) of liquid hydrocarbon fuels at ambient conditions. Such “filters” will be portable, compact, and regenerable and may eventually be integrated into vehicle engines or gas stations. Successful design of these desulfurization “filters” will transform the fuel processing industry by reducing combustion-based sulfur emissions, the energy requirements, and the cost of fuel desulfurization.