Research Projects

This is a list of research projects that may have opportunities for undergraduate students. You can browse all the projects, or view only projects in the following categories:

Bioscience/Biomedical

 

Analysis of Mechanics and Dynamics of Biopolymers in Living Cells

Research categories:  Bioscience/Biomedical, Computational/Mathematical
School/Dept.: Weldon School of Biomedical Engineering
Professor: Taeyoon Kim
Preferred major(s): Biomedical engineering
Desired experience:   - Experience of computer coding using C or MATLAB - Experience of image analysis (preferred, not required) - Independent thinking and problem solving skills
Number of positions: 1

The project is involved with developing software that helps cell biologists and biophysicists to analyze microscope images taken from living cells. The function of the software is to automatically track individual biopolymers in the time-lapse images and calculate their contour length, location, and curvature so that their mechanical and dynamic behaviors can be evaluated without manual measurements. Since the biopolymers are highly dynamic and located in dense networks, these tasks are very challenging problems. To date, there is no software that can efficiently perform these functions, and thus successful development of the software will bring a large impact to relevant fields. Through the project, students will gain research experience of image analysis preferred by numerous laboratories for positions as graduate researchers and will have opportunities to actively collaborate with cell biologists in Department of Biological Sciences at Purdue University.

 

Characterization of Stomatal Development Genes

Research categories:  Agricultural, Bioscience/Biomedical, Environmental Science, Life Science
School/Dept.: Horticulture
Professor: Mike Mickelbart
Preferred major(s): Biology, biochemistry, or related majors
Desired experience:   Biology and genetics
Number of positions: 1

Stomata are small pores on the surface of leaves that regulate gas exchange with the environment. The genetic determinants of stomatal density (SD) changes in response to intrinsic or extrinsic factors are largely unknown. We screened a large population of Arabidopsis thaliana and identified genetic regions correlated with differences in stomatal density. Within these genetic regions, we have selected candidate genes that may be involved in stomatal development. The goal of this summer project is to utilize plants that have mutations in genes of interest to determine if they affect stomatal development. Natural genetic variation will also be used to assess differences in expression of these genes in a diverse set of plant material. The student will gain experience in DNA and RNA isolation, gene expression, DNA sequencing, growth measurements, and leaf anatomical characterization using light microscopy.

 

Constructing Large Scale Representative Social Networks

Research categories:  Bioscience/Biomedical, Computational/Mathematical, Computer Engineering and Computer Science, Educational Research/Social Science, Industrial Engineering, Life Science, Physical Science
School/Dept.: Industrial Engineering
Professor: Mario Ventresca
Desired experience:   At least one student with object-oriented programming, data structures, algorithm analysis, as well as familiarity with at least basic discrete mathematics, statistics and probability (graph theory, distributions, hypothesis testing, regression, etc). Experience using MPI/parallel computation would be highly advantageous, but not necessary. Familiarity with Linux and R would also be useful. A student with a background in epidemiology or applied mathematics would also be very strongly considered.
Number of positions: 1-2

Facebook, Twitter, Orkut and LinkedIn are well known examples of cyber-social networks. However, social networks obviously exist outside of that domain and can represent the connections we make with the people around us. Unlike cyber-world social networks where the connections people make are fully known and observable, real-world networks must be inferred from limited statistical information as well as reasonable assumptions about human behavior. In both instances, a representative social network allows for the study of not only the network topological properties but also diffusive processes acting upon it, such as information spread, influence, disease, etc. There exists a gap in our ability to reconstruct real-world networks from partially observed, noisy and limited data.

This project will aid in developing efficient and scalable algorithms for constructing real-world social network representations at different scales and abstractions (up to global). An extensive literature review of existing capabilities and known social behaviors/mixing patterns will be conducted as part of the project, as will data acquisition and analysis.

 

Developing Brain Computer Interface for Hands-Free Movement Control

Research categories:  Bioscience/Biomedical, Electronics
School/Dept.: Biomedical Engineering
Professor: Zhongming Liu
Preferred major(s): Biomedical Engineering, Electrical Engineering, Computer Science
Desired experience:   Signal and System, Digital Signal Processing, Pattern Analysis, Machine Learning
Number of positions: 2

The student will be involved in developing a real-time brain computer interface system. Through this system, a human subject's brain signal will be acquired and analyzed in realtime to decode the subject's intention to move an object in a 2-D plane without involving his/her hands. The system will serve as a prototype for a new-generation medical device to facilitate disabled patients in motor control by only using their minds.

 

Development of Theranostic Drug Delivery Systems for Cancer Treatment

Research categories:  Bioscience/Biomedical, Chemical, Material Science and Engineering, Nanotechnology
School/Dept.: Industrial & Physical Pharmacy
Professor: Tonglei Li
Preferred major(s): chemistry, chemical engineering, biomedical engineering, biological engineering
Number of positions: 1

Drug delivery for cancer therapy is far from being satisfactory. A significant portion of potential drug compounds fail to enter the clinic because they cannot be formulated and delivered by existing approaches. Many clinically used formulations are poorly designed, bearing significant adverse effects and limiting treatment efficacy. Over the last few years, nanotechnology has been embraced for developing novel drug delivery systems to combat diseases such as cancer and infection. In our laboratory, we have been developing multicomponent nanocrystals to deliver cytotoxic agents along with bioimaging probes to treat and detect tumors. In this project, the delivery system will be fully tested in vitro and in vivo in order to understand the pharmacokinetic and biodistribution properties and to further improve the formulation design. In particular, the student will be learning and conducting cellular uptake experiment and help graduate students in their animal studies. It is expected that the student will gain a basic understanding of drug delivery for cancer and comprehend the current challenges in cancer therapy. The student will also learn the underlying design principles of our delivery system and, hopefully, provide meaningful suggestions for improvement.

 

Enhancing the Resource Potential of Anaerobic Digestion

Research categories:  Bioscience/Biomedical, Chemical, Environmental Science
School/Dept.: Agricultural & Biological Engineering
Professor: Abigail Engelberth
Preferred major(s): Chemical or Biological Engineering
Desired experience:   Statistics, Biology, Chemistry
Number of positions: 1

Anaerobic digestion is an established technology for the treatment of organic waste and the production of energy rich methane, but there is an opportunity to use it for the production of volatile acids as well. Volatile acids are used in the production of plastics, solvents, and pharmaceuticals and are currently being derived from petroleum sources. The anaerobic digestion of organics in wastewater could provide a renewable source of acids for the production of goods in existing markets. The SURF student will conduct experiments to narrow in on the conditions which are optimal for volatile acid production. This work will aid in upcycling a waste source and moving the economy away from dependence on fossil carbon sources.

 

Optimization of antibody penetration for 3D tissue imaging

Research categories:  Bioscience/Biomedical, Innovative Technology/Design, Life Science
School/Dept.: Biomedical Engineering
Professor: Sarah Calve
Preferred major(s): BME/Biology
Number of positions: 1

Recent advances in tissue clearing have increased the depths to which conventional confocal microscopy can image by at least an order of magnitude. Unfortunately, researchers are limited by the ability to only image endogenous fluorescence as passive diffusion of antibodies into intact tissues, to specifically label molecules of interest, can take weeks. Our lab is developing a method to actively promote the diffusion of primary and secondary antibodies into biological tissues to better take advantage of these new clearing techniques.

We are looking for a student to help optimize this method to better label key extracellular matrices expressed during tendon and muscle development in the mouse. The student will be directly involved in harvesting embryos from mice in which the muscle or tendon progenitors endogenously express green fluorescent protein, optimizing the active antibody staining protocol being developed in our lab and imaging the specimens using confocal microscopy. The overall goal of this research is to characterize the 3D composition of the extracellular environment during muscle and tendon assembly inform the design of artificial scaffolds to promote tissue regeneration.

 

The Effects of Angiotensin II Infusion into Apolipoprotein E-Deficient Rodents for the Creation of Abdominal Aortic Aneurysms

Research categories:  Bioscience/Biomedical
School/Dept.: Biomedical Engineering
Professor: Craig Goergen
Preferred major(s): Biomedical Engineering
Desired experience:   - Previous lab experience, lab courses - Previous rodent handling - Experience with Excel and Matlab - Independent problem solving skills
Number of positions: 1-3

The overall purpose of this research is to better understand the effects of angiotensin II (angII) infusion into apolipoprotein E-/- (apoE-/- ) rodents as this often leads to the development of abdominal aortic aneurysms (AAA). AAA rupture in humans is the 13th leading cause of deaths in the United States, causing approximately 15,000 deaths each year. Unfortunately, aortic aneurysms are often asymptomatic and are most often found during routine screenings. Because of this, our lab is dedicated to forming a better understanding of the cause of these aneurysms, which will hopefully lead to preventative treatment and better diagnostic techniques. This specific research project focuses on a apoE-/- mice and rats. These rodents will be infused with angII through an osmotic minipump, which causes vasoconstriction and creates hypertension. Aneurysms often form in the suprarenal abdominal aorta. The development of these AAAs will be tracked through the use of high-frequency ultrasound. The student research assistant will contribute to the study by helping to surgically implant the osmotic pumps, acquire the ultrasound data, and analyze the acquired images.

 

Tumor-Microenvironment-On-Chip To Mimic Tumor Heterogeneity

Research categories:  Bioscience/Biomedical, Mechanical Systems, Nanotechnology
School/Dept.: Mechanical Engineering
Professor: Bumsoo Han
Preferred major(s): Mechanical Engineering, Chemical Engineering, Nuclear Engineering, Biomedical Engineering
Desired experience:   Fluid Mechanics, Heat and Mass Transfer, Biology
Number of positions: 1

This project is to develop and validate a new in vitro tumor model to study tumor heterogeneity. Tumor heterogeneity is one of the most significant and unmet challenges of oncology. Existing tumor models including animal models are not adequate to systematically study and understand its implication on the treatment outcome. In order to address this, my laboratory is developing a new tumor model using tissue engineering and microfluidic technologies which can mimic in vivo tumors of breast cancer. The SURF fellow will participate in this project to characterize the response of various breast cancers to chemotherapeutic drugs and their nanoparticle formulations.