Research Projects

Projects are posted below; new projects will continue to be posted through February. To learn more about the type of research conducted by undergraduates, view the 2018 Research Symposium Abstracts.

2019 projects will continue to be posted through January!

This is a list of research projects that may have opportunities for undergraduate students. Please note that it is not a complete list of every SURF project. Undergraduates will discover other projects when talking directly to Purdue faculty.

You can browse all the projects on the list or view only projects in the following categories:

Electronics

 

Human Body Communication

Research categories:  Bioscience/Biomedical, Computer Engineering and Computer Science, Electronics
School/Dept.: ECE
Professor: Shreyas Sen
Preferred major(s): ECE, BME

The student will work on theory and device design related to using the human body as a communication medium to improve Healthcare and HCI.

 

Low-cost user-friendly biosensors for animal health

Research categories:  Agricultural, Bioscience/Biomedical, Electronics, Innovative Technology/Design, Life Science, Material Science and Engineering, Mechanical Systems
School/Dept.: Agricultural and Biological Engineering
Professor: Mohit Verma
Preferred major(s): Biomedical engineering, biological engineering, electrical engineering, mechanical engineering, or other relevant fields
Desired experience:   To be successful at this position, you should have a GPA>3.5, prior experience working in a wet lab (ideally experience with bacterial culture and DNA amplification), experience building electromechanical devices, and the ability to work in a team.

Infectious diseases are a leading cause of economic burden on food production from animals. For example, bovine respiratory diseases lead to a loss of ~$480/animal. Current methods for tackling these diseases includes the administration of antibiotics by trial-and-error. This approach leads to failure of treatment in up to one-third of the cases. In addition, it also leads to a proliferation of antibiotic resistance in pathogens.

Our research project focuses on developing a low-cost user-friendly biosensor based on paper that can detect which pathogen is causing the disease and whether it exhibits antibiotic resistance. Such a biosensor would provide a readout to the farmer or the veterinary physician and suggest which antibiotics are likely to be successful.

The SURF student will have three objectives: i) design primers for detecting pathogens associated with bovine respiratory diseases, ii) build a device for processing the sample and extracting DNA that can be amplified by the biosensor, and iii) build a device for detecting colorimetric/fluorometric output from the biosensor.

More information: www.vermalab.com

 

Optimization of Quantum Circuits for Noisy Environments

Research categories:  Electronics, Nanotechnology, Physical Science
School/Dept.: ECE
Professor: Andrew Weiner
Preferred major(s): Electrical Engineering, Physics or any closely related major
Desired experience:   (a) Experience using Matlab or Python for instrument control is strongly preferred. (b) Electricity and Magnetism coursework preferred

Our research group works on encoding and processing quantum information in the frequency domain. The platform we work with – biphoton frequency combs (BFCs) – are photon pairs that are entangled in time and energy (frequency). We use commercial hardware like phase modulators and pulse shapers for quantum state preparation and manipulation. Some recent demonstrations include measurement of high dimensional frequency-bin entanglement and tunable quantum gates, among others. Our current efforts are focused on developing quantum circuits to simulate the dynamics of molecules.

The SURF student’s contribution would be as follows:
(1) Develop an instrument control interface to automate the process of quantum state preparation. In particular, we often use commercial pulse shapers to “carve” BFCs from a continuous down conversion spectrum. However, carving a BFCs requires precise positioning of frequency bins in order to ensure that one passes energy-matched (anti-correlated in frequency) comb line pairs. The student would automate this process by interfacing with the pump laser, pulse shaper, and single photon detectors and implementing appropriate instrument control.

(2) What we often measure in our quantum experiments is coincident single photon detection events or, simply, coincidences. However, the number of coincidences depends on factors like loss in the experimental system, the timing jitter of single photon detectors, and the resolution of the timing electronics. The student will carry out a systematic study to evaluate the effect of these factors on the coincidence rate out of a quantum circuit and make recommendations on how to optimize the detection system for high coincidence rates or high coincidence-to-accidental ratios (analogous to signal to noise ratio).

 

Photonic Component Design for Quantum and Classical Information Processing

Research categories:  Electronics, Nanotechnology, Physical Science
School/Dept.: ECE
Professor: Andrew Weiner
Preferred major(s): Electrical Engineering, Physics or any closely related major
Desired experience:   (a) U.S. citizenship, (b) Electricity and Magnetism coursework preferred

Photons are ideal carriers of quantum information because they are robust against decoherence and are compatible with fiber optic networks. Our research group works on encoding and processing quantum information in the frequency domain. One limitation of conventional or bulk optical equipment is that these devices have high optical losses, which is a major issue for applications in the quantum regime. We recently designed photonic integrated circuits to implement elementary quantum gates and carry out operations like parallel single qubit rotations.

The SURF student’s contribution would be as follows:
(1) Design and simulate photonic elements (microresonators for generation of Kerr and quantum frequency combs, pulse shapers, etc.) for our next round of chip fabrication. The student will be given performance specifications and be expected to use analytical expressions, as well as FDTD and/or FEM simulation tool, and come up with recommendation for appropriate device geometries.

(2) Characterize on-chip optical devices/systems and relate actual performance in our first batch of chips to the original design specifications. Depending on the student’s level of experience, he/she will collect data from our testbed, compare it to the design specifications, and draw appropriate inferences from the data.

 

Processing of innovative satellite remote sensing data for ocean and snow remote sensing

Research categories:  Aerospace Engineering, Computer Engineering and Computer Science, Electronics, Environmental Science, Physical Science
School/Dept.: AAE
Professor: James Garrison
Preferred major(s): ECE, AAE, Physics, EAPS
Desired experience:   Good programming skills, signal processing (ECE 301 or AAE301). Experience with software defined radio (USRP) will be a plus.

Reflectometry is a new approach to Earth remote sensing in microwave frequencies, using reflections of Global Navigation Satellite System (GNSS, e.g. GPS, Galileo, etc ...) signals from land and ocean surfaces as illumination source in a bistatic radar configuration. Through observing measurable changes in the properties of these signals, various features of the reflecting surfaces can be inferred.

Ocean surface winds is the most developed application for GNSS-Reflectometry (GNSS-R), with the launch of the CYGNSS constellation by NASA in 2016. CYGNSS data has been collected during the 2017 and 2018 Hurricane seasons, showing some capability for wind field measurements at a high spatial resolution. New models and algorithms are required, however, to optimally process these data and extract wind vectors with high sensitivity, especially at the higher wind speeds present in hurricanes. Development of these new models and algorithms requires the collection of high-quality data under carefully controlled conditions along with in situ training data provided by independent sources. With this goal in mind, Purdue has developed a wideband GNSS-R signal recorder which will be flown on the P-3 “Hurricane Hunter” aircraft operated by NOAA. This aircraft is capable of operating in extremely high winds and penetrating the Hurricane eye wall, in order to collect data inside developing tropical cyclones. GNSS-R data collected in this experiment will be compared with wind speed observations from other instruments on the P-3 aircraft, other satellite data, and model results. These comparisons will be used to develop and improved model for the extraction of ocean winds from CYGNSS and future satellite missions.

Snow Water Equivalent (SWE) is a representation of the total water stored in the snow pack. This is an important climate variable for the prediction of fresh water supplies as well as applications such as hydroelectric power. A new application of GNSS-R is measuring SWE as a change in phase of the reflected signal, a result of the slower propagation of the signal through the snow layer. Spaceborne measurements of SWE using GNSS-R have never been conducted. Special collections of CYGNSS data were conducted this year, in which raw signals (no on-board processing or compression) were collected in arcs spanning snow-covered regions in the Himalayan mountains.

SURF projects are proposed to support these two research goals for CYGNSS data. Both will involve extensive programming and data processing, using a “software defined radio” method that essentially implements all signal processing in software to operate on the full-spectrum of the recorded signal.

Applicants should have very strong programming skills, some knowledge of basic signal processing.

 

Remote sensing of soil moisture and forest biomass using P-band Signals of Opportunity: Model development and experimental validation

Research categories:  Agricultural, Aerospace Engineering, Electronics, Environmental Science, Physical Science
School/Dept.: AAE
Professor: James Garrison
Preferred major(s): ECE, AAE, Physics, ABE
Desired experience:   Basic signal processing (AAE 301 or ECE 301 or equivalent) desired. Students should know how to use basic hand tools, and be willing to work outdoors in agricultural or forest environments. A drivers license and reliable access to a car is required for field work.

Root Zone Soil Moisture (RZSM), defined as the water profile in the top meter of soil where most plant absorption occurs, is an important environmental variable for understanding the global water cycle, forecasting droughts and floods, and agricultural management. No existing satellite remote sensing instrument can measure RZSM. Sensing below the top few centimeters of soil, often through dense vegetation, requires the use of microwave frequencies below 500 MHz, a frequency range known as “P-band”. A P-band microwave radiometer would require an aperture diameter larger than 10 meters. Launching such a satellite into orbit will present big and expensive technical challenge, certainly not feasible for a low-cost small satellite mission. This range for frequencies is also heavily utilized for UHF/VHF communications, presenting an enormous amount of radio frequency interference (RFI). Competition for access to this spectrum also makes it difficult to obtain the required license to use active radar for scientific use.

Signals of opportunity (SoOp) are being studied as alternatives to active radars or passive radiometry. SoOp re-utilizes existing powerful communication satellite transmissions as “free” sources of illumination, measuring the change in the signal after reflecting from soil surface. In this manner, SoOp methods actually make use of the very same transmissions that would cause interference in traditional microwave remote sensing. Communication signal processing methods are used in SoOp, enabling high quality measurements to be obtained with smaller, lower gain, antennas.

Under NASA funding, Purdue and the Goddard Space Flight Center have developed an airborne prototype P-band remote sensing instrument to demonstrate the feasibility of a future satellite version. Complementing this technology development, a field campaign will be conducted for its third year the Purdue Agricultural research fields. This campaign will make reflected signal measurements from towers installed over instrumented fields. Measurements will be obtained over bare soil first, and then throughout the corn or soybean growth cycle. Complementing these remote sensing measurements, a comprehensive set of ground-truth data will also be collected for use in developing models and verifying their performance.

In Spring 2019 an additional experiment, using a small Unpiloted Aerial Vehicle (UAV), will be conducted in a forested area in collaboration with the School of Forestry and Natural Resources (FRN).

Work under this project will involve installing microwave electronic equipment in the field, writing software for signal and data processing, and making field measurements of soil moisture and vegetation properties.

Students interested in this project should have good programming skills and some experience with C, python and MATLAB. They should also have a strong background in basic signal processing. Experience with building computers or other electronic equipment will also be an advantage. Students should be willing to work outdoors and have an interest in applying their skills to solving problems in the Earth sciences, environment, or agriculture.

The project will involve regular travel to and from the local research field, so students should have a driving license and access to a car.