Wearable electrochemical biosensors enable real-time detection and monitoring of biomarkers related to health and wellness anywhere and anytime. While many current wearable devices (e.g., smartwatches) rely primarily on physical sensors that track signals such as heart rate or temperature without sampling biofluids, this limits their ability to measure true biochemical indicators of health. This project focuses on developing an advanced wearable biosensing platform capable of sampling and analyzing skin biofluids, particularly interstitial fluid (ISF), a rich source of biomarkers that closely reflect blood composition.

The project integrates three main research themes:

1. Microneedle Development: Designing and fabricating microneedle arrays for ISF extraction, involving polymer network and hydrogel design, as well as characterization of swelling, mechanical, and biocompatibility properties.
2. Biosensor Development: Creating electrochemical biosensors using 2D nanomaterials to enhance analytical performance. Students will gain hands-on experience in surface modification and bioreceptor immobilization, characterized using techniques such as XPS, AFM, SEM, and EDX.
3. Device Integration: Assembling the microneedle and biosensing components into a compact, wearable device for continuous, non-invasive monitoring.

We are interested in studying the cortical circuits involved in sensory processing with a focus on the role of inhibitory interneurons in these circuits.

Sensory perception is shaped by an animal’s internal state. A large portion of neural activity in the cortex is spontaneously active even in the absence of external stimuli. This spontaneous activity is modulated by the animal’s behavior and internal state.

Many behavior patterns such as locomotion, whisking and blinking correlate with spontaneous activity across the sensory areas. We are interested in developing a processing pipeline that will integrate these fine orofacial movements acquired via an infrared camera with the neural activity recording in sensory cortical areas via 2-photon microscopy.

This project will involve using the facemap module (Pachitariu, M. & Stringer, C. (2024)) to build a pipeline that will preprocess, annotate, extract keypoints from facial camera recording of mice undergoing in-vivo calcium recording. Compute and derived metrics such as principal components of the recorded orofacial movements and, using facemap, apply Hidden Markov models to identify the activity sequences of the spontaneous behaviors and also output them into time series data and then correlate and predict neural activity.

Additionally, the student will learn how to perform patch clamp recordings in acute brain slices to assess the strength of specific inputs to neuronal populations in the visual cortex. 

The internship project aim is to derive and classify geomorphic features from high-resolution seafloor data and to explore how these features vary with depth in the shallow and mesophotic zones along the Saudi Arabian coast of the Red Sea. The student will preprocess the multibeam bathymetry datasets collected across coral-dominated reef environments, generate digital elevation models (DEMs), and extract terrain attributes such as slope, curvature, Bathymetric Position Index (BPI) and rugosity. Building on these metrics, the project will identify and classify geomorphic features (e.g., terraces, slopes, ridges, depressions) and assess their distribution across depth zones. The study will contribute to understanding how geomorphological variability reflects seafloor organization in coral reef-associated settings, providing a baseline for future ROV explorations, long-term monitoring, and the identification of priority areas to be considered within marine spatial planning and protection strategies.

This project aims to design, synthesize, and characterize novel porous organic polymers (POPs) functionalized with specific chemical groups for the selective capture of high-value metal ions (lithium, uranium, rare-earth elements, precious metals) from aqueous solutions. The intern will explore various polymerization techniques to create materials with high surface area and porosity. The synthesized polymers will be rigorously characterized using techniques such as BET surface area analysis, FT-IR, SEM, and TGA. Their performance will be evaluated through batch adsorption experiments to determine key parameters like adsorption capacity, selectivity in multi-metal solutions, kinetics, and reusability. The ultimate goal is to develop an efficient, sustainable, and reusable platform for applications in wastewater treatment and strategic metal recovery.