There are two related projects, both focused on making air safe, including from bioaersols like COVID.

1) Photocatalysis for Air Purification: Photocatalysis is one method for helping degrade harmful airborne particles, like COVID-19, which our lab is investigating in a partnership with a start-up company. Undergraduates interested in designing experimental setups and microbiological experiments are well-suited for this project. Candidates with experience in culturing microorganism/relevant wet lab experience is preferred.

2) Acoustic removal of aerosols: Sound waves can interact with small particles like aerosols, and be used to manipulate their motion. In this project, we aim to invent the first system that can make air safe with sound waves.

Biological Characterization and Imaging, Biological Simulation and Technology, Energy and Environment, Engineering the Built Environment, Fluid Modelling and Simulation, Material Modeling and Simulation, Material Processing and Characterization, Nanotechnology

• No Major Restriction

All applicants should have an interest in photochemistry, microbiology, aerosol sciences, and experimental research. In addition to the required skills mentioned in the points above, applicants with additional experience with some of the following programs are preferred: Python and Adobe Illustrator. What experience will you gain? • Hands on research experience and potential co-authorship in high impact journals • Application of engineering fundamentals to important societal problems • Research credit hours (and potential opportunities for financial compensation in the summer) • Networking opportunities with academic and industry leaders

Mechanical Engineering

David Warsinger

We seek to modify the deformation characteristics of bone through a pharmacological treatment. This project would demonstrate such a concept using animal bone. Treated and untreated bone will be made available for the interrogation of bone by x-rays. Students will be engaged in the data interpretation of x-ray scattering experiments on bone, not subjected to mechanical loads or subjected to mechanical loads.

Biological Characterization and Imaging, Biological Simulation and Technology, Material Modeling and Simulation, Material Processing and Characterization, Other

Materials Characterization, X-ray techniques; Experience in lab work

School of Mechanical Engineering

Thomas Siegmund

Cell division is essential for life, underlying the development of mammals from embryo to full-grown adult, regenerative processes, such as wound healing, and diseases such as cancer. The intracellular aspects of mammalian cell division have been revealed through two-dimensional culture studies, where cells simply grow and then release from the substrate to divide in an unrestricted manner. However, physiologically, many cells divide in mechanically confining microenvironments, including dense extracellular matrices (ECMs) with distinct viscoelastic, viscoplastic, and nonlinear elastic characteristics, often surrounded by other cells, as in tumors. In this project, we will illuminate how cells modulate extracellular forces to facilitate and sustain cell division in confining microenvironments, using a computational model.

Biological Simulation and Technology, Cellular Biology

• Biomedical Engineering
• Mechanical Engineering

Intermediate/Proficient C coding skills Sufficient experiences in MATLAB coding Basic knowledge of cell biology (optional)

Weldon School of Biomedical Engineering

Taeyoon Kim

This project will involve developing models for coupling computational E-field dosimetry tools to neuron solvers. As part of this project students will learn to develop Finite Element Method (FEM) and neuron modeling tools. The student will implement cable model solvers for predicting response of neurons to E-fields.

Biological Simulation and Technology, Medical Science and Technology

• Electrical Engineering
• Biomedical Engineering
• Computer Engineering

Knowledge of Electromagnetics, Matlab, and ODEs is desired.

Electrical and Computer Engineering

Luis Gomez

Single cell pathway analysis refers to the study of biological pathways and processes in individual cells, rather than in bulk tissue samples or cell populations. This approach allows for a deeper understanding of cellular heterogeneity and enables the identification of rare cell types and subpopulations.

Single cell pathway analysis typically involves the use of single cell omics technologies such as single cell transcriptomics (scRNA-seq), single cell proteomics, or single cell epigenetics. These techniques provide a high-throughput and comprehensive view of the molecular changes taking place within individual cells.

Applications of single cell pathway analysis include the study of development, disease, and cellular signaling. For example, it can be used to uncover the complex molecular changes that occur during cell differentiation and the progression of diseases such as cancer. It can also be used to study the effects of drugs and other treatments on individual cells.

there has been multiple methods developed to perform single cell analysis, however, how well these methods perform remains unclear. The aim of this project is developing a benchmark to evaluate various single cell pathway analysis methods.

Big Data/Machine Learning, Biological Simulation and Technology

• No Major Restriction

Computational genomics/bioinformatics. Knowledge of pathway analysis tools and single cell technologies.

BCHM

Majid Kazemian

Project 1: This summer research project will use high resolution imaging test the hypothesis that decoding of Ca2+-flux frequency by CaM and CaMKII plays a major role in dynamic actin polymerization and dendritic spine morphology. Student will learn basic laboratory skills, primary cell culture, immunohistochemistry, confocal imaging and image analysis.

Project 2: This summer research project will use computational modeling of Ca2+/Calmodulin and CaMKII interactions in dendritic spines to test the hypothesis that decoding of Ca2+-flux frequency by CaM and CaMKII plays a major role in dynamic actin polymerization and dendritic spine morphology. Computational tools that will be used include ordinary and partial differential equations and machine learning techniques to rapid explore model parameter space.

Research Question Overview:
Neuronal synapses are tightly regulated intercellular junctions that rapidly convey information from an upstream pre-synaptic neuron to a downstream post-synaptic neuron. Dynamic strengthening or weakening of synaptic connective strength, known as synaptic plasticity, is a critical feature of neuronal function. The direction of synaptic plasticity (increased connective strength (LTP) versus decreased connective strength (LTD)) depends on the timing of action potentials (AP), which is translated into frequency signals of Ca2+ ion flux through NMDA
receptors (NMDAR) located on dendritic spines (100-500nm mushroom-like protrusions that form the post-synapse).

The timing and direction of synaptic plasticity is also exquisitely regulated by dynamic organization and spatial localization of synaptic adhesion molecules, signaling receptors, ion channels, and the intracellular cytoskeleton within spines. However, it not clear to how these electrical, biochemical, and mechanical cues are integrated to produce robust, repeatable, and highly dynamic synaptic plasticity that lasts over the lifetime of a neuron (decades). Our recent work has shown that competition for CaM-binding can influence the Ca2+ frequency-dependence of protein activation and downstream signaling. In particular, the highly expressed Ca2+/calmodulin-dependent kinase II (CaMKII) plays a key role in synaptic plasticity via two
important aspects of its function: (1) CaMKII is highly involved in Ca2+-dependent signal transduction via phosphorylation of a number of downstream proteins including ion channels, guanine nucleotide exchange factors (GEFs), GTPase activating proteins (GAPs), and transcription factors, and (2) CaMKII acts as a multivalent scaffold that binds multiple proteins simultaneously and localizes them to post-synaptic spines, including both filamentous and monomeric actin and may regulate actin polymerization in the spine.

Big Data/Machine Learning, Biological Characterization and Imaging, Biological Simulation and Technology, Biotechnology Data Insights, Cellular Biology

• No Major Restriction

Weldon School of Biomedical Engineering

Tamara Kinzer-Ursem

The student will work on existing computational models (agent-based models or partial differential equation models), making updates toward adapting existing models to new biological systems. Student will be co-mentored by Elsje Pienaar, BME Dept.

Big Data/Machine Learning, Biological Characterization and Imaging, Biological Simulation and Technology

• No Major Restriction

Mechanical Engineering

Adrian Buganza Tepole

Infectious diseases are a leading cause of economic burden on food production from animals. For example, African Swine Fever is the deadliest animal pandemic and led to loss of half the swine herds in China in 2019. Detection of such diseases can be challenging because the clinical signs can be similar to other diseases.
Our research project focuses on developing a low-cost user-friendly biosensor based on paper that can detect which pathogen is causing the disease quickly and provide recommendations on appropriate next steps. Such a biosensor would provide a rapid readout to the farmer or the veterinary physician and guide surveillance efforts.
Lab members working in the team have three objectives: i) design, test, and optimize primers for detecting pathogens and genes associated with African Swine Fever, ii) build and field-test a paper-based device for conducting loop-mediated isothermal amplification, and iii) build and field-test a heating/imaging device for conducting the paper-based assay in the field.
The SURF student will work on one of the objectives depending on their background and experience.

Biological Simulation and Technology, IoT for Precision Agriculture

• Biological Engineering - multiple concentrations
• Biochemistry
• Agricultural Engineering
• Biomedical Engineering
• Mechanical Engineering
• Electrical Engineering

Relevant skills for the project: • Wet lab skills and experience with molecular biology • Autodesk Fusion 360 for 3D Modeling/Printing and Laser Cutting • Python Programming Language for image processing and graphical user-interface using Raspberry Pi (or any other single board computer) To be successful at this position, you should have a GPA>3.5, prior experience working in a lab, and the ability to work in a team.

Agricultural and Biological Engineering

Mohit Verma

Continuous random walks (CRW) – i.e. processes with diffusion and drift – are ubiquitous
in chemistry, appearing in a wide range of fields such as heat and mass transfer, Brownian dynamics (BD) simulations, polymer physics, nucleation theory, and chemical
reaction pathways. Oftentimes in the aforementioned applications, one is concerned with simulating specific types of rare events such as random paths that stay within a particular region of phase space, those which end in a particular region, or those which reach one region before another. Illustrative examples include (a) generating polymer conformations with a specific topology (e.g., rings); (b) examining random pathways in a reaction coordinate space that produce one product compared to others (e.g., polymorphs in crystallization); (c) examining diffusion trajectories of proteins that stay in a region for a sufficiently long time before reaction occurs.

In this project, we are thinking of ways to generate such rare pathways efficiently. The SURF student will work with a graduate student to develop efficient approximations for random walks with a constraint, by examining the partial differential equations that describe different random walks. The student will also look at some example problems in polymer physics where this application could be used.

Biological Simulation and Technology, Fluid Modelling and Simulation

• Chemical Engineering
• Physics
• Mathematics
• Mechanical Engineering
• Materials Engineering
• Mechanical Engineering
• Chemistry

The student should have a background in differential equations, probability, and a basic knowledge of coding. Knowledge in partial differential equations is desired (if possible).

Chemical Engineering

Vivek Narsimhan

Neurite outgrowth is a physiological process where neurons generate farther projections, which is essential for wiring nervous systems during development and regeneration after trauma or disease. The neurite outgrowth is known to be driven mainly by interactions between cytoskeletal components, such as microtubules, cross-linkers, and dynein motors. Previous studies suggested that dynein motors interact with and walk on a pair of neighboring microtubules which are transiently linked by cross-linkers. However, it still remains elusive how these molecular interactions result in neurite elongation at larger scale. To investigate the mechanisms of neurite elongation, we developed an agent-based model that consists of essential cytoskeletal elements with consideration of their mechanical properties and physical interactions. In this project, using the agent-based model, a student will explore extensive parametric spaces to find intrinsic mechanisms of the neurite outgrowth.

Biological Simulation and Technology, Cellular Biology

• Bioengineering
• Mechanical engineering
• Biochemistry

MATLAB, C language

Weldon School of Biomedical Engineering

Taeyoon Kim

Two projects are available. One involves the investigation of enhancing optical imaging resolution using single photon counting techniques. Conventional optical imaging has a hard limit on its spatial resolution, to about one half of the wavelength, and many situations can benefit from higher resolution. In addition, it is challenging to image through scattering media. By way of example, being able to sense with light deeper in the brain would be of enormous benefit in neuroscience. The statistics of photons emitted by or transmitted through an object contain valuable information about the object which could be used to enhance image resolution and possibly see through substantial background scatter. Experiments will be conducted using laser light and with a set of single photon avalanche detectors (SPADs) to measure photon correlations in time, over wavevector (direction), and between detectors in various imaging configurations. Results from these experiments will be used to assess the effectiveness of various techniques for enhancing spatial resolution in imaging applications. This work has a diverse set of potential applications including biological imaging, sensing defects in semiconductors, and imaging through fog. The other project relates to experimental work and the modeling of optical forces on structured membranes induced by a laser. The mechanical motion of a thin membrane deflected by laser light will be used to determine the membrane properties from experimental and simulated data. This will allow extraction of the mechanical material properties and more generally the validation of a theory for optomechanics that can then be used in design. The nascent field of optomechanics offers enormous impact scope, including remote actuation and propulsion, of importance in fields as diverse and molecular biology, communication, and transport. This project relates to attaining the underpinnings to move along such paths in engineering, as well as the basic physics of optical forces in material at small length scales.

Big Data/Machine Learning, Biological Characterization and Imaging, Biological Simulation and Technology, Composite Materials and Alloys, Deep Learning, Material Processing and Characterization, Medical Science and Technology, Nanotechnology

• Electrical Engineering
• Mechanical Engineering
• Physics
• Biomedical Engineering

Students with an interest in experimental or modeling work and some background in electromagnetics would be a good fit for this project. The undergraduate student will work with graduate students to perform experiments in an optics laboratory, modeling, data analysis using MATLAB or python, and review relevant literature.

Electrical Engineering

Kevin Webb