CTSGC Spring 2025 Awardees Announced!

Faculty Project Grant

Nicolas Zoghb
University of Bridgeport
Realizing Mathematical Potential for Incoming Freshmen

This is a mathematics enrichment program designed to engage incoming freshmen students in immersive mathematical experiences to prepare them for university math courses as well as math-based science and engineering courses.

Faculty Travel Grant

Rasmani Hazra
University of New Haven
Advancing glioblastoma research through international collaboration: a professional development opportunity at the 2025 WFNOS-SNO meeting.

Attending the 2025 WFNOS-SNO Annual Meeting in Honolulu is a vital opportunity to advance my research on glioblastoma, particularly in areas of radiation-induced mutations and RNA-based immunotherapies. The meeting’s theme, “30 Years of Progress,” aligns with my focus on emerging hallmarks of brain cancer and fosters interdisciplinary collaboration. Presenting my work will enhance my professional development, expand my global network, and support translational insights relevant to both oncology and space radiation biology. This experience will strengthen my scientific foundation and contribute meaningfully to NASA’s mission by bridging cancer research with space health priorities.

Faculty/Student Research

Haoyu Wang
Central Connecticut State University
Automated Robotic Inspection System for Aerospace Airfoils Based on 3D/2D Vision and AI

This project aims to develop an automated robotic inspection system for aerospace airfoils, enhancing propulsion system reliability for NASA. The system integrates an ABB IRB-1200 robot with a FocalSpec LCI 1600 line sensor to perform high-resolution 3D scans of airfoils, addressing the limitations of traditional manual inspection methods. The centralized control interface ensures accurate and repeatable results, while future iterations aim to automate scan merging using RealityCapture’s command-line interface. This project provides practical experience for student researchers and contributes to the advancement of aerospace technologies.

Brian Wells
University of Hartford
The University of Hartford Multiscale Metamaterial Undergraduate Student-Faculty Research Summer 2025

The proposed project will be led by Professor Brian Wells at the University of Hartford’s Multiscale Metamaterial Research Laboratory. This effort consists of two integrated projects aligned with NASA’s Science (SMD), Space Technology (STMD), and Space Operations (SOMD) Mission Directorates. The first project involves the development of an X-band software-defined radio (SDR)-based vector network analyzer, which will be incorporated into our state-of-the-art, custom-built automated microwave optics table. This system will characterize reconfigurable metasurfaces and metalenses for beam steering and frequency modulation, with direct applications in satellite communications and wireless energy transfer in the X-band (8–12 GHz). The second project focuses on the additive manufacturing of compact, flat metamaterial lenses. A Lulzbot TAZ6 FDM printer will be adapted to incorporate novel high-conductivity photoactivated paste extrusion additives into dielectric filament manufacturing. Simultaneously, a Phrozen Sonic Mighty 14K SLA printer will be modified to cycle photopolymer resins for fabricating high-resolution dielectric and conductive structures. Two undergraduate students—one from a community college—will participate fully in design, fabrication, and testing throughout the 8-week Summer 2025 program.

STEM Education Programming Grant

Viktoria Savatorova
Central Connecticut State University
Undergraduate-Led Learning: Mathematical Modeling in Aerospace

We propose two STEM workshops for local high school students, designed and led by undergraduate students with faculty advisement. Each session will focus on an aerospace-themed experiment – rocket launches and parachute design – and guide participants through data collection and the development of mathematical models based on physical laws of motion. CCSU alumni working in aerospace will be invited to share their career journeys as guest speakers. Connecticut hosts globally leading companies in aerospace and other STEM fields, creating strong demand for a skilled local workforce.  Our project aligns with NASA’s mission to build the STEM pipeline.

Robert Sheftel
CT State Community College – Naugatuck Valley
STEM Maker Lab: A Summer Hands-On Tech Experience for Underserved students at CT State Naugatuck Valley

Aligned with NASA’s Office of STEM Engagement, the STEM Maker Lab at CT State Naugatuck Valley empowers CT State Colleges students from underserved communities to explore STEM through immersive, project-based learning. Inspired by the energy and creativity of maker spaces, the program will offer experiences in coding, AI, soldering, 3D design, 3D printing, and electronic circuitry, while also integrating Digital Graphic Arts. Participants will not only build and assemble tech projects—they will document and showcase their work through multimedia content creation, cultivating both technical and creative skill sets.

STEM Education Research Grant

Tomoyasu Mani
University of Connecticut
Molecular Quantum Days for High School Teachers and Students

This project proposes to develop a new outreach program, weekend workshops (Molecular Quantum Days), targeted at high school students and teachers focusing on molecular quantum science and technologies.  The new program will allow high school students and teachers to explore the quantum world through molecular science, connecting quantum concepts with phenomena/technologies students find in daily life. Students will explore fundamental concepts in quantum mechanics through hands-on activities and discussions facilitated by PIs and undergraduate/graduate assistants. The project aligns with NASA’s mission to develop cutting-edge quantum technologies for space exploration and scientific discovery under the Space Operation and Space Technology Mission Directorates.

Faculty Research Grant

Junnan Cao
Central Connecticut State University
Hybrid biopolymer-sulfur stabilization for Lunar and Martian surface infrastructure

Sustainable surface infrastructure is essential to achieving NASA’s Artemis and Mars exploration goals. This research proposes a novel biopolymer-sulfur hybrid method to stabilize lunar and Martian regolith, combining biologically derived polymers for initial soil cohesion with sulfur infusion to enhance structural strength and environmental durability. The mechanical properties, erosion resistance, and long-term resilience of the hybrid material will be systematically evaluated. This approach advances In-Situ Resource Utilization (ISRU) technologies, reduces construction energy demands, and supports the objectives of NASA’s Space Technology, Human Exploration, and Science Mission Directorates by enabling robust, low-mass surface infrastructure for future missions.

Natalia Gonzalez Pech
Wesleyan University
Synthesis of clusters of Fe3O4 and NiO nanoparticles for water reclamation

Water reclamation is process that allows the use of treated water in conditions where clean water is not readily available. Our goal is to synthesize clusters of magnetite nanoparticles that incorporate NiO. Magnetite nanoparticles are well-known for the high capabilities to remove ions such as arsenate and phosphates from water. We propose adding NiO to enhance the water treatment to also remove organic molecules such as urea. Urea and phosphates are some of the main components of urine, which could be used to reclaim water in space exploration missions.

Shivanjali Khare
University of New Haven
SPARC: Spectrally-Guided Pseudolabeling for RGB-Only Semantic Segmentation of Urban Land Cover

This project addresses the need for improved land cover analysis in RGB imagery by introducing a novel spectrally-guided pseudo-labeling pipeline that generates land, water, soil, and tree canopy masks from NDVI. Pixel-level labels derived from NDVI are spatially mapped to RGB images to create a training dataset for a deep learning segmentation model to detect pervious and impervious surfaces from RGB-only imagery. This approach enhances ecosystem monitoring and decision-making where access to spectral imagery is unavailable, directly supporting NASA’s Earth Science objectives by improving access to advanced Earth observation and fostering a sustainable environment.

Gengyun Le-Chan
University of Hartford
Exploiting exercise to combat type 1 diabetes: Enhancing glucose control, immune function, and muscle health for space and earth-based human well-being

This project explores the preventive and therapeutic effects of exercise on metabolic, immune, and musculoskeletal health in type 1 diabetes, with implications for both Earth-based and spaceflight environments. Utilizing the Non-Obese Diabetic mouse model and human participants, we aim to investigate how exercise influences blood glucose regulation, muscle function, and myokine signaling in diabetic conditions. Aligned with NASA’s Space Operations Mission Directorate (SOMD), this research intends to identify exercise-based countermeasures to combat muscle atrophy and metabolic dysregulation during long-duration space missions, promoting astronaut health and offering broader benefits for individuals with type 1 diabetes on Earth.

Yingcui Li
University of Hartford
AI-Based Spatial and Functional Modeling of Osteoclast and Osteoblast Interactions in Bone Remodeling and Degeneration

This project studies osteoblast–osteoclast dynamics in bone remodeling using high-resolution imaging and machine learning. Building on our AI model of endochondral ossification, we aim to create a spatially indexed, single-cell framework to analyze these cells in normal and degenerative conditions. By modeling bone formation and resorption in altered cellular environments, the research offers insights into musculoskeletal health for astronauts and age-related bone loss on Earth. It aligns with NASA’s Human Research Program, addressing skeletal deterioration during long-duration spaceflight and terrestrial aging.

Akshay Mathur
Fairfield University
Adversarially-Stable Cyber Defense for Anomaly Detection in Satellite Communications

This study explores the vulnerability of AI-driven anomaly detection models for space communication to adversarial attacks and investigates defense mechanisms to enhance their resilience. We will train machine learning models on a labeled satellite telemetry dataset and retrain them with adversarial examples to mitigate exploitable weaknesses. The dataset reflects real-life space communication scenarios, enabling robust anomaly detection. The proposed two-branch, end-to-end network architecture aims to provide layered defense against both evasion and poisoning attacks. This research not only addresses national security interests but also promotes student engagement in developing secure and resilient AI systems.

Fazel Mohammadi
University of New Haven
Integrated Space Systems Security and Data Assurance via Zero Trust Architecture

The integrity, confidentiality, and availability of space-derived data are increasingly vulnerable to sophisticated cyber threats targeting satellite communications, ground control infrastructure, and data relay networks. As space systems grow in complexity, autonomy, and interconnectivity, traditional perimeter-based security models are no longer sufficient. This proposal presents the design, analysis, and implementation of a domain-specific Zero Trust Architecture (ZTA) designed for application across the space domain, addressing the unique operational and cybersecurity challenges of orbital and deep-space environments. The framework integrates core ZTA principles—such as continuous identity validation, least-privilege access control, and real-time behavioral monitoring—across the end-to-end satellite-to-ground architecture. Key technical components include cryptographically enforced trust boundaries, policy-driven access control engines, and Artificial Intelligence (AI)-powered anomaly detection mechanisms. The resulting architecture is designed to be modular, scalable, and adaptable for a wide range of NASA mission profiles, including Low Earth Orbit (LEO) satellites, deep-space exploration assets, and distributed satellite constellations.

David Shekhtman
Fairfield University
Shear Stress and Angle-of-Attack Flow Stability Measurements on Flight Geometries in Hypersonic Flow

Thin graphite resistor arrays are proposed to be used as shear sensors in hypersonic speed flow. Graphite resistors are sensitive to temperature, erosion, and flexing. These properties can be used to measure streamwise and wall-normal shear stress and heat flux profiles on test articles during ground testing. The slopes of these profiles can be used to determine the transition point and other flow features, such as separation bubbles. The wall-normal shear stress profile can contribute to the development of a general Law of the Wall turbulence model at different angles of attack. The proposal suggests exploring the use of graphite resistor arrays in cold Mach 6 flows, generated by the upcoming Fairfield Ludwieg Tube. Using a rotating model mount, the shear stress sensor arrays will be used on flight geometries (flat plates, actuated control surfaces, cones, and hollow cylinder flares) to ultimately measure the sensitivity of hypersonic flow fields to oscillations in angle of attack. Schlieren and possibly, acetone velocimetery will accompany results to verify flow conditions and transition point. From flow data, simplified turbulence models will be proposed to aid in hypersonic vehicle development. Multiple 2026 AIAA SciTech submissions will be made and presented. Students will participate in all project stages.

Elizabeth Stone
Fairfield University
Environmentally-Sustainable Synthesis of Xenobiotic Peptide Therapeutics

Natural biological processes rely on 20 canonical amino acids. Xenobiology seeks to expand the genetic code to utilize amino acids beyond those of terrestrial biology. The goal of this research is to develop a safe and sustainable method to synthesize and modify drugs that contain a xenobiotic amino acid. Working with undergraduate students, this work will advance key NASA directorates: 1) expanding traditional chemical synthesis to include xenobiotic materials that may be found in extra-terrestrial environments, and 2) developing safe and sustainable strategies to produce therapeutics that could be accomplished in remote locations or on exploration missions.

Carter Takacs
Quinnipiac University
Elucidation of ADNP function in neurodevelopment and maintenance using a zebrafish model

Exposure to radiation in space can result in increased risk of neurodegeneration and cognitive impairment. Activity-dependent neuroprotective protein (ADNP) is a transcription factor that plays protective roles in neurodegeneration, and reduced ADNP function is associated with neurodevelopmental disorders such as Alzheimer’s, schizophrenia, and autism. Our lab has generated zebrafish harboring adnp gene mutations in order to better understand its neurodevelopmental roles. Here, we aim to 1)map brain activity in adnp mutant zebrafish and 2) identify downstream genes regulated by ADNP. Together, we seek to understand how ADNP impacts brain function, and highlight pathways that may provide neuroprotection in space.

Sanaz Vajedian
Wesleyan University
Monitoring Vegetation Dynamics in Borderland Ecosystems Using Integrated Satellite Imagery and Cloud-Based Analysis Platforms

This project aims to monitor vegetation change in the ecologically sensitive U.S.–Mexico borderlands using a multi-sensor, cloud-based remote sensing framework. By combining imagery from Sentinel-2, Landsat 8/9, HLS, and PlanetScope, we will generate seamless NDVI time series to detect vegetation stress linked to climate variability and human disturbance. Additional datasets, including precipitation, land surface temperature, and soil moisture, will support interpretation of observed patterns. Data processing will be conducted in Google Earth Engine and Google Colab. The project also includes undergraduate research training, offering hands-on experience with geospatial analysis, time series interpretation, and satellite-based environmental monitoring.

Song Wang
University of Hartford
Impact of Concrete Surface Roughness on the Short-Term and Long-Term Interfacial Bond Performance of FRP-Strengthened Concrete Members

This study will examine how concrete surface roughness affects the bond performance of FRP-strengthened concrete members. Concrete surfaces will be sandblasted to target roughness levels, then measured with two surface profiling machines to quantify roughness parameters before FRP application. Specimens will then undergo nine months of simulated harsh environmental conditioning. Mechanical tests will be conducted to assess short-term performance and long-term durability. Statistical and AI-driven image analyses will correlate roughness metrics with bond strength. Results will establish objective concrete surface preparation guidelines and support NASA’s Exploration Systems Development Mission Directorate by enabling rapid, on-site evaluation and construction of extraterrestrial infrastructures.