Fred DeMatteis School of Engineering and Applied Science
ASPiRe Advanced Summer Program in Research
Annual Symposium Hofstra University Science & Innovation Center, Room 231 Remote Link
August 20, 2026 9:00 a.m. – 4:15 p.m.
This is the tenth annual Advanced Summer Program in Research (ASPiRe) Symposium to be hosted by the Fred DeMatteis School of Engineering and Applied Science, and I am pleased that twenty-five students have participated. A key component in its success and growth is the most generous financial support it receives from distinguished benefactors of the DeMatteis School. Donor support of these exceptional researchers is of immeasurable value to the students themselves and adds luster to all our educational endeavors.
Sina Y. Rabbany, PhD Dean Fred DeMatteis School of Engineering and Applied Science
2026 ASPiRe Symposium Thursday August 20, 2026 8:50am to 4:15pm Science & Innovation Center (SIC), Rm 231
TIME 8:50AM
STUDENT/ ADVISOR RESEARCH PROJECT TITLE WELCOME - Philip Coniglio, Assistant Dean for Co-op and Experiential Learning Cayden Hollar / Aniket Jangam, Zeev Alias / PI: Dr. Chad Bouton Feinstein Principal Investigator
Fabrication of a Spinal Cord Stimulator PCB as a Therapeutic Device for Individuals Living with Tetraplegia
1
9:00 AM
2
9:14 AM
3
9:28 AM
4
9:42 AM
5
9:56 AM
Gurleen Kaur / PI: Dr. Stephan Bickel and Dr. Sabina Gherman, Christine Chesebrough Feinstein Principal Investigator
Decoding Attention States from Intracranial EEG Signals
6
10:10 AM
Julian Singh-Smith / Dr Zonghua Gu
Availability Attacks and Runtime Defenses for Real-Time AI Perception Systems
7
10:24 AM
Nickolaos Hatzigeorgiou / Dr. Jianchen Shan
Mitigating Excessive vCPU Spinning in Confidential VMs Without Hypervisor Support
Lauryn Jacques / Ahn Vu, MD / PI: Stavros Zanos, MD PhD Feinstein Principal Investigator Deepak Karupen / PI: Dr. Timir Datta-Chaudhuri Feinstein Principal Investigator Gabriella Lucas / PI: Dr. Chunyan Li Feinstein Principal Investigator
Investigating Neuroinflammation and Sensory Signaling in the Thoracic Spinal Cord During Pulmonary Arterial Hypertension A High-Throughput Wireless Sensor Bluetooth Platform for Screening Polymer Encapsulation for Medical Implantable Devices Optimization of a Non-Invasive Electrode to Treat Chronic Conditions with Trigeminal Nerve Stimulation
10:40 AM
BREAK
8
10:50 AM
Subhan Nadeem / Thomas G. Re
A Multimodal Embodied Robot Assistant for Natural Human-Robot Interaction
9
11:04 AM
Daniel Kowal / Thomas Peers / Dr. Roche de Guzman
Tilting Bed Insert with an Auxetic Mattress for Hospital-Acquired Pressure Injuries
10
11:18 AM
Leila Mejia / Dr. Sithara Wijeratne
Real-time tracking of the structural and mechanical properties of endothelial cell migration in wound healing
11
11:32 AM
Makis Landon Prescod / Dr. Sina Rabbany
Computer Controlled Microfluidic Platform for Automated Pump Driven Vascularization
12
11:46 AM
Tara Osumanu / Dr. Nicholas Merna
Preconditioning Plant-Based Vascular Grafts with Flow and Electrical Stimuli
Matthew Kurcz / Dr. Sleiman R. Ghorayeb
Quantitative Ultrasound Assessment of Fetal Lung Heterogeneity in Complete Atrioventricular Canal Defect (AVC)
13
12:00 PM 12:14 PM
LUNCH
12:54 PM
Annalisa Samaroo / Dr. Manuel Miranda
15
1:08 PM
Drew Atkins / Maksim Pivovarskiy / Dr. Edward M. Segal
16
1:24 PM
Nelson Velasquez / Dr. Margaret A. Hunter
Building and Testing a Simple Detection Method for the Quantification of Microplastics Using Absorption with Fluorescent Dyes
17
1:38 PM
Pete Sotirakos / Dr. Minjeong Suh
Exploration of 6-PPDQ Phototransformation using Non-targeted Analysis
18
1:52 PM
Christian Malla / Dr. D E. Williamstyer
Enabling End-Fire Radiation in a 1D- Arbitrary Slot Antenna
19
2:06 PM
Donovan Cios & Micheal Toppin / Dr. Edward H. Currie / Dr. Zhao
Delta Robot
20
2:20 PM
Emily Carroll / Dr. Edward H. Currie
Machine Learning for Wound Edge Detection in Autonomous Surgical Closure
2:36 PM
BREAK
21
2:46 PM
Regina Cantu Chavez / Dr. Salvador Rojas-Murillo
Investigating the Effect of Feedback on Decision-Making During an Augmented RealityBased Axillary Block Procedure
22
3:00 PM
Andrew Braun / Dr. Gozde Ustuner
Nanomaterial-Based Coatings for Corrosion Resistance and Durability
23
3:14 PM
Luke Lander / Maksim Pivovarskiy / Dr. David Rooney / Dr. John Vaccaro
Experimental Study of Vortex Interaction Between Two Cylinders at Different Spacings
24
3:30 PM
Kevin Barry / Dr. Simona Doboli
AI Creativity Agent for Group Brainstorming
3:50 PM
ASPiRe Group Photo
14
25
Remote Access: Meeting ID: 960 7901 8444 Passcode: 368644 +16465588656,,96079018444#,,,,*368644# US (New York)
Utilization of Waste Material from Soil Washing Plant for Low-Carbon Concrete Production Designing and Assembling A Carbon Fiber Drone Cage
1. Fabrication of a Spinal Cord Stimulator PCB as a Therapeutic Device for Individuals Living with Tetraplegia Researcher: Cayden Hollar Advisor: Aniket Jangam, Zeev Alias, Dr. Chad Bouton (Feinstein Principal Investigator) Cervical spinal cord injury is a leading cause of paralysis in the upper extremities, and as a result, recovery of arm and hand function is a top priority for this population. The team at the Neural Bypass and Brain Computer Interface Laboratory at the Feinstein Institutes for Medical Research at Northwell Health is actively working to restore hand function by developing innovative neurotechnologies. This research has led to the development of a therapeutic and assistive hybrid system called the Double Neural Bypass (DNB). This system integrates brain-computer interface technology with external stimulation devices, such as transcutaneous spinal cord stimulation (tSCS) and neuromuscular electrical stimulation. Building on this system, the original tSCS stimulator was redesigned and fabricated as a printed circuit board (PCB)-based platform to improve safety, reproducibility, and scalability for therapeutic use. The tSCS system can deliver focal stimulation to the cervical spinal cord using a custom electrode array. When paired with activity-based training, tSCS has produced significant gains in volitional upper-limb strength, with up to 86% improvement in elbow flexion force that persisted over several months, demonstrating the capacity of targeted spinal cord stimulation to promote lasting functional recovery. To help identify cervical targets that produce the desired muscle responses and their optimal stimulation location and parameters, the system is paired with surface electromyography to evaluate how changes in settings affect recruitment of upper-limb muscles. This mapping process identifies the stimulation parameters and locations that most effectively engage specific motor pathways for each participant. The original stimulator was constructed as a pilot device using breadboards and perfboards with soldered components. Although effective for early clinical use and validation, this prototype design limited reproducibility and standardization, motivating the transition to a printed circuit board-based platform with added safety and protection features. This redesign provides a more robust, reproducible, and scalable hardware foundation for tSCS and future therapeutic applications of targeted spinal cord stimulation in upper-extremity rehabilitation after spinal cord injury.
2. Investigating Neuroinflammation and Sensory Signaling in the Thoracic Spinal Cord During Pulmonary Arterial Hypertension Researcher: Lauryn Jacques Advisor: Ahn Vu, MD PI: Stavros Zanos, MD PhD (Feinstein Principal Investigator) Pulmonary arterial hypertension (PAH) is a progressive cardiopulmonary disease caused by remodeling of the pulmonary arteries, leading to increased pulmonary arterial pressure, right ventricular overload, and eventually heart failure. Although current treatments target pulmonary vascular dysfunction, many patients continue to experience disease progression, suggesting that additional pathological mechanisms contribute to PAH. Growing evidence indicates that autonomic imbalance, altered neural signaling and neuroinflammation may participate in the development and progression of the disease. This study investigates whether PAH is associated with microglial activation and increased sensory afferent signaling in the thoracic spinal cord. PAH will be induced in rats, and thoracic spinal cord segments corresponding to cardiopulmonary innervation levels (T1–T6) will be collected and analyzed using immunohistochemistry. Microglial activation will be evaluated using ionized calcium-binding adaptor molecule 1 (Iba1) and the lysosomal activation marker CD68. Changes in spinal sensory signaling will be assessed by measuring calcitonin gene-related peptide (CGRP) immunoreactivity, particularly within the dorsal horn, where primary sensory afferents terminate. Quantitative image analysis will be used to assess microglial morphology, CD68 expression, and CGRP-positive sensory fiber density in PAH and healthy control animals. We hypothesize that PAH will be associated with increased microglial activation and enhanced CGRP-positive sensory signaling in the thoracic spinal cord. Characterizing these spinal changes may provide insight into how cardiopulmonary sensory input and spinal neuroinflammation contribute to disease progression in PAH. These findings may also identify spinal sensory and neuroimmune pathways as potential therapeutic targets for PAH.
3. A High-Throughput Wireless Sensor Bluetooth Platform for Screening Polymer Encapsulation for Medical Implantable Devices Researcher: Deepak Karupen Advisor: PI: Dr. Timir Datta-Chaudhuri (Feinstein Principal Investigator) Active implantable devices require encapsulation strategies to limit the ingress of moisture. Standard approaches for clinical devices utilize metals and ceramics, but these materials are generally too costly or heavy for small animal studies. Additive manufacturing approaches such as 3D printing can be used to develop lightweight and low-cost polymer-based packages for implantable electronics. However, polymers have significantly higher water penetration rates and require additional processing and design considerations to enable the semi-hermetic performance required for chronic experiments. Selection of appropriate approaches requires screening of these methods by exposing the encapsulation to saline to mimic the environment within the body. Standard data collection approaches using wired sensors do not scale well. Here we discuss the development and evaluation of a novel high throughput wireless screening platform. Each sensing unit, referred to as a “shell unit”, combines a precision temperature and humidity sensor with a Nordic nRF52 system on chip, which broadcasts measurements in custom-structured Bluetooth Low Energy advertising packets from inside the sealed volume. Because the units advertise at long intervals rather than establishing and maintaining connections, the power draw stays low, and one receiver can observe many units at once. Since each shell unit is sealed and powered by a small primary cell that cannot be replaced mid-test, a central design effort was to minimize power draw by optimizing sensor sampling, advertising intervals, and CPU power governors for sleep between transmissions. This allows us to extend unit lifetime to multiple months and cover a full test campaign on a single cell with minimal packet loss. An nRF54 receiver was used to buffer and filter incoming packets and stream data over a digital connection to a Raspberry Pi computer used to store the data in an organized format. The data were then automatically processed using MATLAB and graphed for evaluation of encapsulation performance. Future work targets scaling beyond one hundred units and additional sensor types and test environments.
4. Optimization of a Non-Invasive Electrode to Treat Chronic Conditions with Trigeminal Nerve Stimulation Researcher: Gabriella Lucas PI: Dr. Chunyan Li (Feinstein Principal Investigator) The trigeminal nerve is composed of three main branches: the ophthalmic nerve (V1), the maxillary nerve (V2), and the mandibular nerve (V3). Trigeminal nerve stimulation (TNS) has been seen to modulate cerebral vasodilation, brain metabolism, cerebral autoregulation, cerebral and systemic inflammation, and the autonomic nervous system (Shah, 2022). TNS’s diverse mechanisms have enabled clinical applications in migraine, disorders of consciousness, and depression (Shah, 2022). In preclinical studies, percutaneous TNS has been studied using both direct stimulation as well as needle injection, but given the broad potential of TNS, a non-invasive, transcutaneous approach is desirable. This study aims to design, model, and 3D print, a plastic, cured resin clip to hold the electrode used for stimulation of the V2 branch of the trigeminal nerve to be externally attached to the rat. The model of the electrode clip is evolving, with next steps aiming to include a component to be inserted into the nostril for stimulation of the V1 branch in addition to the V2 branch. So, a secondary objective of this study is to render a 3D model of the rat head, of the nasal canal, and of the nerve bundles neighboring the nasal canal to obtain a better understanding and visualization of the morphology of the nasal canal accessible by the electrode as well as identify nerve bundles to be targeted for stimulation. The morphology of the animal, considering the circuitry of the electrode, and TinkerCAD were crucial in the design and modeling of the clip. ImageJ as well as an EVOS microscope were crucial tools during this neuro-mapping and 3D-modeling process. This project is ongoing, and so the effectiveness of the clip as stimulation for the animal has not yet been ascertained.
5. Decoding Attention States from Intracranial EEG Signals Researcher: Gurleen Kaur Advisor: Dr. Stephan Bickel (Feinstein Principal Investigator) Christine Chesebrough, Sabina Gherman Our attention naturally shifts throughout the day between focusing on the outside world and our internal thoughts. This project explores whether these changes in attention can be identified using brain signals recorded with intracranial electroencephalography (iEEG) and eye movements. Intracranial EEG records electrical activity directly from the brain using electrodes that are surgically implanted for clinical monitoring. Each electrode contains multiple contacts that measure brain activity from different locations. The experiment consisted of patients watching two ambient movies that were designed to be relaxing and under-stimulating. At pseudo-random intervals between 30-60s, they were prompted to answer whether their attention was more externally oriented (towards the movie) or internally oriented (i.e. mind wandering). Their eye movements were simultaneously recorded using an eye-tracker. iEEG data from N = 4 patients was preprocessed, and the 12-second period prior to each thought probe were segmented into one-second windows. Analytic power was extracted across canonical EEG frequency bands for every time window at each electrode contact. EEG frequency bands are the classification of brainwaves into categories such as delta, theta, alpha, beta, and gamma. These band frequencies are measured in Hertz (Hz) which represent the number of signal oscillations that occur per second. Each frequency band is associated with different patterns of brain activity and cognitive states. A data frame was constructed to link key layers of data, and from this a contact-level feature matrix was engineered. This feature matrix treated the power measured at each electrode contact and frequency band as independent features. This was used to train supervised machine learning classifiers, including Linear Support Vector Machines (Linear SVMs), to decode attention states from neural activity. Feature coefficients were extracted from the trained models to identify specific brain regions and electrode contacts that serve as key neural signatures of attention state. This work provides a foundation for advancing our understanding of how different attention states are represented in the brain.
6. Availability Attacks and Runtime Defenses for Real-Time AI Perception Systems Researcher: Julian Singh-Smith Advisor: Dr. Zonghua Gu Modern AI systems increasingly operate under strict real-time constraints in autonomous vehicles, edge computing, and cyber-physical systems. While most adversarial machine learning research focuses on prediction integrity, this research investigates a different security objective: availability, where an attacker amplifies computational workload to violate real-time deadlines without necessarily changing prediction accuracy. This project studies availability attacks and runtime defenses across three representative AI pipelines. First, we develop TrackShield, the first runtime defense against availability attacks on multi-object tracking, which detects abnormal tracker-pool growth using lightweight runtime signals and bounds association workload through graceful degradation. Second, we analyze confidence-gated edge– cloud inference and show that adversarial manipulation of confidence scores can trigger excessive cloud offloading, leading to queue congestion, deadline misses, and increased energy consumption; we propose Bounded Escalation, a runtime admissioncontrol framework that limits malicious escalation while preserving benign service quality. Third, we demonstrate that removing Non-Maximum Suppression (NMS) from modern object detectors does not eliminate latency attacks but instead relocates the attack surface from detector post-processing to downstream tracking, introducing a unified overload attack against NMS-free perception pipelines. Together, these studies reveal a common systems-security principle: adversaries increasingly target resource amplification rather than prediction accuracy and protecting real-time AI systems therefore requires runtime mechanisms that explicitly monitor and bound computational workload. This work provides a unified perspective on availability attacks in AI systems and demonstrates practical runtime defenses that improve the resilience of safetycritical real-time perception and adaptive inference.
7. Mitigating Excessive vCPU Spinning in Confidential VMs Without Hypervisor Support Researcher: Nickolaos Hatzigeorgiou Advisor: Dr. Jianchen Shan To design and implement a lightweight, guest-only solution to eliminate wasteful vCPU spinning in Confidential VMs, where hypervisor cooperation and paravirtualization are not feasible. In modern Confidential VM environments, excessive spinning on locks remains a major inefficiency, especially when the lock holder’s vCPU is preempted. Techniques like adaptive spinning and deferred preemption—effective in host kernels—fail in guest kernels due to the lack of visibility into vCPU states and inability to influence scheduling. This problem is exacerbated in multi-cloud and untrusted host scenarios, where guest VMs cannot rely on hypervisor support. We propose a novel mechanism that enables adaptive spinning and approximates deferred preemption entirely within the guest kernel. Our approach uses a lightweight method to detect if a vCPU is preempted - without paravirtualization or hypervisor involvement. This allows the lock waiter to skip spinning when the lock holder is not actively executing. Additionally, we dynamically migrate lock-holding threads away from vCPUs that are likely to be preempted, approximating deferred preemption.
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8. A Multimodal Embodied Robot Assistant for Natural Human-Robot Interaction Researcher: Subhan Nadeem Advisor: Thomas G Re Natural human-robot interaction requires a robot to perceive a person, understand flexible spoken language, respond verbally, and coordinate physical behavior in real time. This project develops a multimodal embodied robot assistant that integrates voice interaction, computer vision, natural-language command interpretation, and multi-axis motion on a single platform. The goal is to move beyond isolated servo demonstrations toward an attentive assistant whose eyes, head, torso, hand, and forearm act as a coordinated system. The prototype runs locally on an Ubuntu mini-PC. It combines wake-word detection, automatic speech recognition, a local language model with safety-constrained semantic routing, text-to-speech, and YOLO-based person detection. Visual error is translated into smooth eye, head, and torso corrections, while spoken instructions trigger allowlisted gestures even when phrased in different ways. To support simultaneous behaviors safely, a centralized hardware coordinator manages shared servo controllers, channel ownership, known actuator positions, timed trajectories, cancellation, signal release, and sequential shutdown parking. The resulting prototype has demonstrated wake-word interaction, transcription and spoken responses, horizontal and vertical person tracking, paraphrase-tolerant commands, five-finger hand gestures, forearm motion, and torso rotation. Calibration established safe operating envelopes for the eyes, head, hand, forearm, and torso. Engineering investigations also identified and corrected microphone buffering failures, controller resets caused by duplicate hardware initialization, stale position assumptions, and trajectory timing errors that previously produced abrupt movements. Current work is completing shoulder and jaw calibration, refining hierarchical eye-headtorso attention, and evaluating command success, tracking accuracy, response latency, and long-session reliability. This platform provides a reusable foundation for studying how coordinated speech, gaze, body orientation, and gesture can make human-robot interaction safer, more natural, and more understandable.
9. Tilting Bed Insert with an Auxetic Mattress for Hospital-Acquired Pressure Injuries Researchers: Daniel Kowal and Thomas Peers Advisor: Dr. Roche de Guzman Hospital-acquired pressure injuries (HAPIs) are a common and largely preventable form of harm in healthcare, arising when prolonged loading over bony prominences deforms soft tissue and restricts local blood flow, producing ischemia and eventual cell death. They are staged by severity, from stage 1 (non-blanchable erythema of intact skin) to stage 4 (full-thickness tissue loss exposing muscle or bone), and carry a substantial clinical and financial burden for an outcome generally considered avoidable. Conventional prevention depends on manual repositioning and foam bolstering, which are timeconsuming and a leading cause of caregiver musculoskeletal injury, and on alternating-pressure mattresses, which redistribute surface pressure but do not offload the underlying skeletal structure. This Figure 1. Repositioning device prototype actuated to 30 degrees study develops an automated, mechanical insert compatible with standard hospital beds that offloads the patient without manual lifting. It uses two independently controlled plates, each combining a linear actuator with a Scott Russell straight-line linkage. A control system then raises either side of the mattress to tilt the patient to a target offloading angle of approximately 30° (Fig. 1), the angle clinically associated with reduced sacral and trochanteric interface pressure. To improve load distribution at the skin interface, a 3D-printed thermoplastic polyurethane (TPU) mattress with an auxetic (negative Poisson's ratio) lattice was modeled and is being evaluated in combination with the device. Together, the tilting insert and TPU overlay system provide a low-cost, automated strategy that actively offloads at-risk tissue while reducing the physical burden on caregivers.
10. Real-time tracking of the structural and mechanical properties of endothelial cell migration in wound healing Researcher: Leila Mejia Advisor: Dr. Sithara Wijeratne Endothelial cell (EC) migration is the process by which cells move to form new blood vessels in response to oxygen demands and tissue injury. Failure of ECs to migrate properly can have life-threatening consequences, contributing to diseases such as tissue death, coronary artery disease, and stroke. During EC migration, the leading edge of the cell extends forward while the trailing edge retracts behind it. In addition, Piezo1, a mechanosensitive channel in ECs, controls this process. Although many biochemical studies have examined EC migration, there is limited knowledge on how the biophysical properties change during migration and how activating or blocking Piezo1 affects these changes. Here, we use phase-contrast time-lapse microscopy and atomic force microscopy (AFM) to quantitatively measure the dynamic, mechanical, and structural properties of EC migration in real-time. Our time-lapse microscopy studies show that ECs treated with Yoda-2, a Piezo1 activator, migrate significantly less than untreated ECs to close a scratch. In addition, our AFM results show that height and stiffness values differ significantly between Yoda-2 treated and untreated ECs. When we specifically examined the leading and trailing edges of the cells, we found that the leading edge was less stiff than the trailing edge in ECs. Together, these results suggest that Piezo1 redistributes mechanical stiffness across the cell, softening the leading edge in a way to impair the protrusive forces needed for migration. These findings provide insights into vascular biology and also inform us on our understanding of tissue and organ repair and the mechanics of wound healing. This work could also be extended to examine real-time dynamics of cellular processes in other areas of biology.
11. Computer Controlled Microfluidic Platform for Automated Pump Driven Vascularization Researcher: Makis Landon-Prescod Advisor: Dr. Sina Rabbany Vascularization of organoids is essential for modeling tissue development, studying disease progression, and evaluating potential therapeutics. However, existing microfluidic platforms designed to support vascularization often fail to maintain stable vessel networks over extended periods due to fluctuations in the pressure gradient driving flow. This project addresses that challenge by developing an automated system that maintains a constant height difference between the inlet and outlet reservoirs in a microfluidic chamber, thereby providing a more stable flow environment for vascular growth. The computer-controlled platform integrates a Raspberry Pi, Arduino, and pump system to continuously monitor and regulate fluid levels to ensure constant pressure. The Raspberry Pi captures images of the inlet reservoir and analyzes media height in real time. When the fluid level drops below a threshold required for effective vascularization, the Raspberry Pi sends a signal to an Arduino, which controls the pump’s operation and flow rate. Using a reservoir containing fresh media, the pump replenishes the inlet reservoir while media from the outlet is collected and recycled. Through continuous communication among these electronic components, the system aims to significantly extend the viability and longevity of microfluidically generated blood vessels. This enhanced capability will enable longer-term and more comprehensive investigations of vascular biology, including studies of vessel responses to pharmaceutical agents and quantitative analyses of the mechanical stresses experienced by vascular tissues. Ultimately, this product may provide new insights into the biological and biomechanical factors that regulate vascular function and disease.
12. Preconditioning Plant-Based Vascular Grafts with Flow and Electrical Stimuli Researcher: Tara Osumanu Advisor: Dr. Nicholas Merna Cardiovascular disease is the leading cause of death worldwide, creating an urgent need for effective small-diameter vascular grafts. Autologous grafts remain the gold standard but are often unavailable due to prior harvest or disease, while synthetic grafts perform poorly at small diameters because of thrombosis, compliance mismatch, and incomplete endothelialization. Decellularized plant-derived scaffolds have emerged as biocompatible, scalable alternatives capable of withstanding physiological pressures. Although perfusion bioreactor conditioning has been used to improve plantderived grafts, the effects of electrical stimulation remain largely unexplored. In this study, we developed and tested a bioreactor that combines electrical stimulation with luminal perfusion to condition endothelialized plant-derived vascular grafts. Multilayer grafts were fabricated using decellularized leatherleaf viburnum scaffolds and cultured under electrical stimulation, luminal perfusion, or combined electric-perfusion conditioning. Analytical electric-field modeling was used to estimate local graft-region exposure and guide the selection of biologically tolerated stimulation conditions. A 24hour live/dead viability assay identified a local field range of approximately 0 to 18 V/m that maintained greater than 90% endothelial cell viability. Viability fell below this threshold at local fields above 20 V/m and declined to 47% at 26 V/m. Within the tolerated range, electrical stimulation, perfusion, and combined conditioning, each increased endothelial elongation and orientation, as assessed by scanning electron microscopy and CellProfiler analysis. Additionally, endothelialized, flow-conditioned grafts showed reduced penetration of fluorescent microbeads into the underlying scaffold layer, suggesting improved barrier function. Overall, this work introduces an electric-perfusion bioreactor for plant-derived vascular grafts and identifies electrical and perfusion conditions that preserve endothelial cell viability while promoting cell organization.
13. Quantitative Ultrasound Assessment of Fetal Lung Heterogeneity in Complete Atrioventricular Canal Defect (AVC) Researcher: Matthew Kurcz Advisor: Dr. Sleiman R. Ghorayeb Complete Atrioventricular Canal Defect (CAVC) also known as Complete Atrioventricular Septal Defect (AVSD) is a congenital heart anomaly characterized by a common atrioventricular valve and defects of both the atrial and ventricular septa, resulting in interaction between all 4 cardiac chambers. The defect results in abnormal intracardiac blood flow with symptoms similar to heart failure and requires correction during infancy, with mortality without intervention approaching 50% within the first year of life. Abnormalities associated with AVC defect include a single leaky common valve instead of two valves (mitral and tricuspid), an enlarged heart, and left to right shunting after birth. Complete AVC defect also results in an increase of blood flow to the lungs causing advanced pulmonary vascular disease with intimal fibrosis noted between ages 6 months to 1 year, and vascular dilation with plexiform lesions found by 1 year. Reliable prenatal assessment of lung development in fetuses with congenital heart defects remains limited, and existing methods are invasive with limited accuracy. Quantitative ultrasound analysis using the fetal lung heterogeneity index (HI) has been shown as an effective method in distinguishing between preterm and term fetal lungs along with detecting respiratory distress syndrome (RDS) and transient tachypnea of the newborn (TTN). Although echocardiography is the current standard of diagnosing AVC, little is known about whether quantitative measures of fetal lung texture differ in affected fetuses. The purpose of this study was to determine whether there is an association between AVC and fetal lung tissue heterogeneity (HI) prenatally. An initial patient cohort containing 72 patients (36 AVC + 36 control) demonstrated that the fetal lung heterogeneity index is moderately predictive of complete AVC defect, with an AUC of 0.6119 (p=0.06) and average HI values for AVC and control being 1.2553 and 1.3284 respectively. These preliminary findings suggest that fetal lung heterogeneity may differ in fetuses with complete AVC, warranting further investigation into larger cohorts. Future studies will include an increased patient population and examine other heart defects, such as large ventricular septal defects (VSD).
14. Utilization of Waste Material from Soil Washing Plant for Low-Carbon Concrete Production Researcher: Annalisa Samaroo Advisor: Dr. Manuel Miranda The Posillico Wash Plant located in Farmingdale, N.Y., was the world's largest soil washing facility when it opened in 2019. In 2025, the plant processed approximately 375,000 tons of contaminated soil, construction and demolition waste, excavation waste, dredge waste, etc., and was able to recycle approximately 90% of this material into high-quality washed construction sands and aggregates. However, the remaining 10% consists of a clayey silt material with traces of contaminants, known as "filter cake," which poses significant waste management and disposal challenges. In this project, we evaluate the feasibility of using this filter cake as a partial substitute of cement in low-carbon concrete production. The first stage of the project focuses on the mechanical strength of mortar cubes made with a mix of water, type I/II cement, filter cake, and standard-graded Ottawa sand. Several mortar trial mixes were prepared to identify the maximum amount of filter cake that yields a minimum of 75% of the compressive strength of the control mix at an age of 28 days. With the optimal amount thus identified, we also prepared concrete trial mixes with different water-to-cementitious material ratios to identify corresponding compressive strengths (evaluation of these concrete trial mixes is ongoing). In addition, we explored several strategies to increase the effectiveness of the filter cake, including using sedimentation to reduce the amount of clay and organic material present in the filter cake, as well as preconditioning the latter with powdered activated carbon, hydrated lime, and cement.
15. Designing and Assembling a Carbon Fiber Drone Cage Researchers: Drew Atkins and Maksim Pivovarskiy Advisor: Dr. Edward M. Segal Close-range drone operation is a precise process that requires expert, attentive control, with little room for error. However, some procedures have such little allowance for mistakes that a safety net would lead to much better, more successful results. An example of such a safety net could be a cage that surrounds the drone, which takes on whatever impact the drone could face in the event of mismanaged control as opposed to the propellers or main body of the drone. The purpose of this research was to design a cage for an Aurelia X6 drone, so that it could safely carry out operations necessary for future research projects. The main design questions that needed to be addressed were what material the cage should be made of, how should that material be configured around the drone, how should the parts be connected together and to the drone, and how can the cage be configured to not exceed the drone’s payload of eleven pounds. Iterative design and prototyping led to a final drone cage consisting of 0.383-inch diameter carbon fiber tubes and custom 3D printed polylactic acid (PLA) connectors.
16. Extraction of semantic relations from group ideation experiments Building and Testing a Simple Detection Method for the Quantification of Microplastics Using Absorption with Fluorescent Dyes Researcher: Nelson Velasquez Advisor: Dr. Margaret A. Hunter There are millions of tons of plastics in our oceans. While there are efforts to clean up the larger plastics floating in the oceans, the microplastics found in the oceans are much harder to identify. Microplastics are defined as plastic particles ranging from 0.001 – 5mm in length. Some of these microplastics are intentionally created such as glitter and microbeads while others are fragmented from plastics in use or found in litter. Microplastics have the ability to absorb persistent bioaccumulative and toxic compounds (PBTs) from their environment. These compounds remain in these microplastics that are small enough to be ingested and transferred to an organism and eventually work their way up the food chain and into the food we eat. This problem is only being exacerbated as an estimated 4.8 to 12.7 metric tons of plastic litter makes its way into our oceans every year. To understand the problem better, it is important to be able to quantify and identify plastics in environmental samples. Currently methods such as fourier transform infrared (FTIR) spectroscopy and Raman spectroscopy are reliable ways of microplastic identification due to their ability to distinguish between different polymers with very high accuracy. However, these methods require expensive instrumentation and are time consuming for quantification because identification is done a single particle at a time. Methods such as microscopy and camera image analysis are simple to set up to count visible plastic particles making them more suitable for quantification. However, these methods have no way of identifying the specific polymers of plastic and are highly susceptible to false positives or missing hard to see particles. This experiment looks into increasing the accuracy of microscopy and camera image analysis by building an affordable light source that can be used with both methods along with Nile Red dye solution which stains plastics and causes them to fluoresce when excited by certain wavelengths of light. This makes the plastic particles more visible and easier to quantify, decreasing the likelihood of a false positive or missing a hard to see particle. Because this does not identify the specific polymer of a particle, methodologies are currently being looked into to help with this identification. For example, different wavelengths of light can excite stained plastics to fluoresce differently depending on the plastic polymer. This fact can be taken advantage of for narrowing down the specific plastic polymers present in a sample. Another technique being developed is counterstaining which stains organic non plastic materials in the sample that may have taken on the Nile Red. This provides further differentiation that helps reduce false positives. In this project, the feasibility of these methods was tested by comparing their accuracy to that of a fluorescence microscope.
17. Exploration of 6-PPDQ Phototransformation using Non-targeted Analysis Researcher: Pete Sotirakos Advisor: Dr. Minjeong Suh 6-PPD is an antioxidant widely added to tires and other rubber products to extend their functional lifespan. However, once released into the environment, 6-PPD can transform into more toxic byproducts, including 6-PPD-quinone (6-PPDQ), which has been linked to adverse ecological effects. Sunlight-driven (photochemical) reactions represent a major pathway governing the environmental transformation of these compounds. In this project, we will investigate the photochemical transformation of 6-PPDQ, with particular attention to the role of chloride. Chloride is ubiquitous in natural waters and becomes especially concentrated during winter months due to large-scale road salt application. Under sunlight, chloride can generate highly reactive chlorine radicals, which may significantly alter the transformation pathways and persistence of and 6-PPDQ. The products of photochemical transformation are extremely difficult to predict a priori. Modern mass spectrometry–based non-targeted analysis (NTA) is a powerful analytical approach that enables the simultaneous detection and tentative identification of a broad suite of known and unknown transformation products in complex environmental matrices. Because manual interpretation of multi-dimensional mass spectrometry datasets is impractical, we apply Progenesis and UNIFI to detect and identify transformation products from the photochemical degradation of 6-PPDQ.
18. Enabling End-Fire Radiation in a 1D- Arbitrary Slot Antenna Researcher: Christian Malla Advisor: Dr. D.E. Williamstyer Far-field radiation patterns play a key role in the design and analysis of almost every modern antenna application, ranging from satellites and radar to wireless networks and remote sensing, since the pattern is able to show how efficiently and in what direction the antenna structure transmits or receives energy. In light of this, arbitrarily reprogrammable antennas capable of electronically steering their radiation pattern would have a significant impact on wireless systems, enabling adaptive beam control beyond what is achievable by phased arrays. The slot antenna is a rectangular cutout within a metal plane that radiates power almost identical to the dipole antenna. By expanding the length of the slot and placing multiple ports along it, various spatial modes (and therefore radiation patterns) can be excited. However, the boundary conditions at the edge of the slot are critical at wide angles of radiation. Currently, the end-fire mode, or radiation along the slot and metal plane, is not feasible due to the mismatched transition from the PCB to the surrounding air, which reflects energy back to the feed and limits the achievable directivity for true end-fire. This project seeks to address this issue by designing an electromagnetic structure that will allow for efficient end-fire radiation of a slot antenna. To accomplish this goal, a traditional Vivaldi end-fire antenna was first designed, simulated, and fabricated to develop intuition for end-fire PCB antennas. This intuition was then used, along with the theory of end-fire and slot PCB antennas, to begin innovating a new antenna structure. Simulation results from the Vivaldi baseline, including corrugated and variable-taper-length variants, have been used to characterize the tradeoff between end-fire directivity and radiation efficiency on standard FR4 substrate, with design of the novel slot structure expected to be completed by the end of the semester.
19. Delta Robot Researchers: Donovan Cios and Michael Toppin Advisor: Dr. Edward Currie and Dr. Yimin Zhao This project consists of using Artificial Intelligence for hand tracking and creating a 3d mesh for the robot to understand where the hand is, Hardware components such as a stereo camera for triangulation and an enclosure for all the components (such as motor drivers, microcontroller board, power supply, touch screen, and other necessary ports to connect to ethernet and computer), and programming magnetic material using energy beam writing techniques. In order for the robot to track the hand in real time, we need to triangulate the position of each hand keypoint from the stereo camera into real 3D space. To achieve this, a stable 2D keypoint estimate is required, along with calibration in real-world coordinate space of the stereo camera. A blaring issue with this methodology is that the predicted real-world keypoints are heavily distorted, causing inaccurate anatomical poses. To address the distortion error, we take a neural network-based approach where we train a model to learn the kinematic construction that minimizes an anatomy-distance mixed loss function. Classical neural network approaches model the hand structure as an MLP (Multilayer Perceptron), but in this project we introduce a single step Diffusion style Graph Attention Network that is used to account for the lack of data samples needed to train the network along with modelling the joints and implicit structure within the hand. The enclosure is designed using OnShape, a CAD software that produces STL files and more. The components are measured, and variables are accounted for such as mounting holes and methods of access to the enclosure. Something that has to be accounted for is the shrinkage of 3d prints due to thermal expansion. Programming magnetic material for this project is mainly for the magnets that are placed to close the wound after edge detection. The methods can be done in various ways but the method that we use is “Pulsed Field/CoilArray Magnetizing Heads”. Small electrical coils blast quick, powerful bursts of magnetism directly onto specific spots on the magnet. Because these pulses are stronger than the material's resistance, they instantly flip the magnetic direction of those exact spots. This lets you quickly print complex patterns of North and South poles across a single piece of magnet at room temperature.
20. Machine Learning for Wound Edge Detection in Autonomous Surgical Closure Researcher: Emily Carroll Advisor: Dr. Edward Currie Autonomous robotic surgery has the potential to improve surgical precision, reduce procedure time, and increase access to high-quality medical care. One critical challenge in autonomous wound closure is the accurate localization of wound boundaries so that sutures can be placed consistently along the wound edge. This project investigates a deep learning approach for automated wound edge detection as part of a robotic surgical system that utilizes magnetic sutures for autonomous closure. A wound image dataset was developed from clinically relevant wound photographs and preprocessed using region-of-interest (ROI) cropping to isolate the wound from surrounding tissue. A baseline U-Net++ segmentation architecture was trained using a combination of Focal Binary Cross-Entropy and clDice loss functions to improve both regional segmentation accuracy and preservation of thin, continuous wound boundaries. Model performance was evaluated using multiple complementary metrics, including Dice coefficient, Intersection over Union (IoU), Average Symmetric Surface Distance (ASSD), 95th percentile Hausdorff Distance (HD95), Boundary F-score, and Chamfer Distance. In addition, a novel application-specific metric, Average Suture Placement Error (ASPE), is being developed to quantify the average distance between predicted and ground-truth wound edges in terms of expected suture placement accuracy. Preliminary results demonstrate substantial improvements in wound boundary localization compared to baseline approaches, producing smoother and more anatomically continuous edge predictions that are better suited for autonomous surgical planning. The resulting wound edge detection framework is intended to serve as the perception component of an autonomous robotic wound closure system, enabling accurate magnetic suture placement and advancing the development of intelligent surgical robotics.
21. Investigating the Effect of Feedback on Decision-Making During an Augmented Reality-Based Axillary Block Procedure Researcher: Regina Cantu Chavez Advisor: Dr. Salvador Rojas-Murillo Advancements in augmented reality (AR) and eye-tracking technologies are reshaping how procedural skills are taught and evaluated in medical education. This project centers on the design and development of an interactive AR simulation for the axillary brachial plexus block, aimed at understanding how feedback and visual guidance influence learning and decision-making. The system combines anatomical modeling, real-time feedback, and gaze-tracking analytics to examine how learners engage with procedural content and respond to instructional cues. Current work focuses on refining the software environment, defining Areas of Interest for gaze tracking, and synchronizing visual and auditory feedback to align with key anatomical features. The goal is to establish a strong framework capable of capturing attention patterns and feedback responses once experimental trials begin. By integrating AR and eye-tracking data, this study seeks to advance evidence-based strategies for improving learner engagement, optimizing feedback mechanisms, and supporting the development of procedural competence in medical training.
22. Nanomaterial-Based Coatings for Corrosion Resistance and Durability Researcher: Andrew Braun Advisor: Dr. Gozde Ustuner This project investigates the development of advanced nanomaterial-based coatings for improving corrosion resistance in energy systems. Graphene oxide (GO), nitrogendoped carbon (NC) derived from the metal-organic framework ZIF-8, and cerium-doped nitrogen-doped carbon (Ce-NC) were synthesized and evaluated as protective coatings for metallic substrates. The synthesized materials were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDX) to examine their crystal structure, morphology, elemental composition, and to confirm successful material synthesis. The corrosion resistance and durability of the coatings were evaluated through corrosion testing and electrochemical characterization, including cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), to assess coating stability, barrier performance, and long-term protective properties. Electrochemical measurements were performed after 1, 7, and 21 days of immersion in saltwater under both air and argon atmospheres to investigate the effects of exposure time and environmental conditions on the corrosion behavior and durability of the coatings. Comparative analysis of GO, NC, and Ce-NC coatings provided insight into the influence of nitrogen doping and cerium incorporation on coating performance and corrosion resistance. The findings demonstrate the potential of MOF-derived carbon nanomaterials and rare-earth doping as effective strategies for enhancing the longterm durability and corrosion protection of advanced coatings for energy infrastructure operating in harsh environments.
23. Experimental Study of Vortex Interaction Between Two Cylinders at Different Spacings Researchers: Luke Lander and Maksim Pivovarskiy Advisor: Dr. David Rooney and Dr. John Vaccaro The interaction of the vortices shed behind a pair of circular cylinders was studied using flow visualization techniques in the Michael Delaney Water Tunnel. The cylinder pair had diameters of 0.25" and a length of 6 inches under the water surface, giving them an aspect ratio of 24, Dye was injected from the side of both cylinders at midheight into a constant velocity water current, producing a Reynolds number Re = 250. The two injected streams were of different color so that the vortex activity of each cylinder could be easily identified. A camera placed directly overhead of the test section captured images of the development, advection and interaction of the shed vortices over a 30 second timeframe. The two cylinders were placed at distances of one diameter through five diameters apart, and at angles of incidence from 0 to 90 degrees in increments of 10 degrees to create a test matrix of 50 relative orientations. A protocol for counting the shed vortices from each cylinder was developed and data were summarized in terms of Strouhal number St = f D / U versus relative spacing P / D for three groupings of angles of incidence 0 – 20 degrees, 30 – 50 degrees and 60 – 90 degrees. In addition, each 30 second video was examined to identify special cases that emerge, such as single bluff body flow patterns, small incidence angle flow patterns, and large incidence angle flow patterns. Comparison of present results with results obtained by previous investigators with similar geometries but at higher Reynolds number flows (800 < Re < 1950) were made.
24. AI Creativity Agent for Group Brainstorming Researcher: Kevin Barry Advisor: Dr. Simona Doboli The goal of this research is to build a group brainstorming AI agent that analyzes the group conversation in real-time, identifies when to intervene and with what type of message, and it generates a message that will help unlock more creativity from the human members of the group. In this work, we are extending the group conversation analysis with keyphrases and external knowledge and relationships at the idea level and identify the moments the group brainstorming can be enhanced by an AI agent.
H HOFSTRA FRED DEMATTEIS SCHOOL OF ENGINEERING AND APPLIED SCIENCE