Potential research projects!
This is where we post ideas for research projects that are outside the main work of the lab. These could be suitable for undergraduate students to do as independent studies, or MS projects, or just for fun! Some of them may be a little off the wall. If you see something that strikes you as interesting and you would like to find out more, get in touch!
Suitable for students from CS or a related discipline. You bring the skills, we provide the cool applied problems!
Dynamic fish tracking and identification
Given a video of fish swimming in an aquarium, develop a system to both track and identify the individual fish in real time, so as to create a dynamic, live overlay of labels on the video. This would involve putting together a number of existing technologies, as separate good (mainly neural-network-based) systems exist now for tracking and image identification. Suitable for a student with experience in machine learning, especially CNNs.
Physical platforms for field imaging
One of our research areas is automated ‘technical’ ID systems: systems for identifying species from images of specific parts, such as bees from their wings or trees from their leaves. As good as modern deep learning networks are at being robust to noise, disambiguating species often depends on very subtle differences, and so it is still important to get good consistent images, both for training, testing, and ultimately deployable systems. This can be a challenge. We suspect that there might be relatively simple hardware accessories that would improve the process dramatically. Here are two cases:
Bees are identified from preserved specimens under a microscope. Obtaining a clear image of a bee’s wing is a challenge: generally the wing is detached from the body and sandwiched under a cover slip, which is fiddly and time-consuming. The resulting images often have glare spots, which are noise for the ID algorithm. So the design challenge is this: is there a specially shaped platform (in microscope terms, a ‘stage’) that would allow a high-quality image of a bee wing (or really any kind of insect wing) to be taken quickly without detachment?
The leaves of some species have distinct outlines, but most are ‘simple,’ and the key to distinguishing the leaves of different species is the pattern of venation. It is therefore necessary to acquire an image of a leaf that emphasizes this, which can be achieved by oblique lighting (usually of the underside of the leaf). This is easy to achieve in a lab, but we want to be able to do it in the field. So we are thinking about a sort of light box onto which one might place an iPhone or similar in a specially designed slot, plus a leaf. The box would apply consistent oblique lighting (plus a plain background) for getting a good leaf image, allowing field researchers to obtain many images in a short amount of time without having to bring the leaves back to the lab.
Environmental data science and communication
Suitable for students from STS, design and/or computing backgrounds, probably working in teams.
‘State of NJ’ dashboard
Create a live display of key environmental indicators for the state of NJ, from public records. Forest coverage, soil loss, recycling efficiency, energy consumption balance, etc. Requires some ‘investigative journalism’ skills.
Augmented reality for environmental information
Take existing environmental datasets and figure out how to represent normally invisible environmental variables and processes using location-based AR. Example 1: show sea surface temperature anomalies as an overlay on the actual ocean. Example 2: show gas exchange around a tree, for example as in the particle-based simulation shown here (from hiilipuu.fi). Requires someone with skills in (or interested in learning) Apple’s ARKit or Google’s ARCore.