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First Year Research in Engineering Experience
The First Year Research in Engineering Experience (FYREE) program provides first-year undergraduate students and prospective engineering majors with early hands-on experience and mentoring within engineering.
The 2022–2023 application cycle is now closed. Submissions after the deadline are not accepted.
- Up to 12 two-term research projects available over Winter and Spring
- Participation in the form of a part-time internship paying $12 per hour; 8–10 hours per week
- FYREE interns present a poster at the Wetterhan Symposium held annually in May with other Dartmouth undergraduates involved in scientific research
- Get hands-on research experience
- Learn important life and work skills
- Explore possible career paths
- Network with scientists and engineers
- Experience the Dartmouth Engineering community
Evaluation of energy infrastructure permitting processes
Contact: Erin Mayfield
This project will evaluate the driving factors that influence the infrastructure permitting timing. This project will include coding stakeholder interviews and interpretation of pending and passed permitting legislation.
- Introductory understanding of public policy
- Introductory knowledge of interview methods
Deep routing in the real world
Faculty: Peter Chin
Routing is a fundamental part of our lives. We tread physical routes on road networks when trying to navigate to a new restaurant and, without thinking about it, the data we get when interacting with online services needs to be routed to us through the internet.
There are a few versatile routing approaches that have proven to work well on both kinds of networks, including the A*-algorithm, its bidirectional counterpart, or greedy routing. All of them rely on the ability to find good approximations for the distance between a node in the network and the target node. A promising direction to obtaining such distance approximations is to embed the networks into some metric space.
Road networks have a natural embedding onto the surface of the earth (the actual positions of the roads) but it is unclear whether this embedding is optimal for routing purposes. On the other hand, there is not really a natural embedding for artificially constructed networks like the internet. However, it was observed that routing on internet topologies works well, when embedding them into the hyperbolic plane.
In this project, we want to explore how deep learning can help in generating or adjusting embeddings, in order to improve the performances of the above mentioned algorithms. As a start, we want to evaluate existing deep learned embeddings in the context of routing on a variety of real-world networks. The resulting insights shall then be used to adapt the embedding method (trying different embedding spaces or neural network architectures) in order improve this approach in terms of different criteria like routing quality and embedding size.
Fabrication of silk scaffold for an alternative to surgical mesh
Mentor: Rebecca Thomson
Urinary incontinence occurs in 1 out of 3 women weekly and is an extremely common but not talked about problem. Polypropylene mesh used as a mid-urethral sling is currently the gold-standard surgical procedure for the treatment of urinary incontinence. This mesh provides permanent support to the mid-urethra to prevent the continuation of urinary incontinence. Polypropylene mesh has been recalled by the FDA and reclassified as a more dangerous device because of the common occurrence of tissue erosion and mesh exposure. The overall objective of our program is to create a bioresorbable scaffold made of silk to create a safer, more biocompatible alternative to polypropylene. A critical problem to be solved is bridging the gap between obtaining silk from silkworms and concentrating it for effective scaffold creation through electrospinning. The FYREE student involved would participate in the fabrication and characterization of silk and other biomaterials while learning the techniques of processing silk for electrospinning and mechanical analyses.
Balancing nature-based benefits and equitable outcomes in flood adaptation
Faculty: Klaus Keller
Mentor: Adam Pollack
Location: Irving Institute, Office 385
The Federal Emergency Management Agency (FEMA) funds the majority of flood risk adaptation in the US. Critics have argued that two societal values have been overlooked in historic investments due to flawed benefit-cost analyses (BCA) FEMA uses to inform their decision-making: nature-based solutions and social equity. In response, FEMA has recently introduced updates to their BCA methodology to incorporate benefits from nature-based solutions and to promote equitable outcomes from adaptation investments. We hypothesize that the way FEMA values nature-based solutions comes at a tradeoff with their equity goals because the environmental amenities with the highest values are predominantly near wealthy households. In the case of buyouts, this will lead to wealthy communities obtaining higher benefit-cost ratios, and adaptation in their communities being favored more highly, than is possible in the disadvantaged communities FEMA is trying to prioritize in their new equity initiatives.
- How is the value assigned to different land-uses distributed as a function of the socio-economic variables FEMA uses to define disadvantaged communities?
- Do disadvantaged communities have access to benefits from nature?
- Do the benefits from nature-based solutions come at a tradeoff with equitable outcomes under FEMA’s new rules for buyouts?
- Are there nature-based solutions that are synergistic with equity? (Example: vegetation and mitigating urban heat islands, possible additional effects for CSO)
In this context, we might be thinking about the environmental risk reduction benefit as a function of social factors as equity and the environmental risk reduction as the efficiency.
- Conduct a literature review of nature-based solutions in flood risk adaptation with a focus on FEMA funded buyouts
- Geographic assessment of land-use, socio-economic variables, and flood risk for case studies on the New Jersey shore and in New Jersey off the Delaware river
Preferred in Applicants
- Excited by problem overview and research questions
- Passion for learning to overcome any challenge at hand
- Comfortable in a collaborative environment where constructure feedback is provided
Nice to Have Experience/Skills
- Previous literature review conducted
- Coding experience (python would be best for this project)
- Familiarity with flood and/or climate adaptation academic literature, current events, and/or policy
Test rig for can carriers in the circular economy
Contact: Emily Monroe
Focus: Mechanical, environmental and economic engineering
Iterant is a startup on a mission to eliminate single-use packaging waste using a marketplace platform to capture the inherent value of reusable goods and create reuse business models that are both sustainable and profitable. The HDPE 4-pack can carrier used by many craft breweries is an ideal use case to pilot this concept, but manually inspecting the carriers for damage before reuse is too slow and expensive - a fast and reliable quality control method is needed. This project will require students passionate about waste reduction, mechanical design and engineering economics to develop a test process, design a quality control test device, and analyze the potential economic impact of process improvements on the reuse of can carriers at large scale.
Lake Sim: VR for lake health
Contact: Emily Monroe
Focus: Software and environmental engineering
Temperate lakes are an important yet fragile resource in New Hampshire, and engaging elementary and middle school students through an educational VR lake simulation could be a key to preserving lake health for future generations. This project will use virtual reality to design mini-games, loosely based on cause and effect for changes upstream of the lake, that examine effects of watershed land use and/or invasive species on in-lake conditions. Students will need a passion for design (environments, interfaces, user experience), programming (C# in Unity), 3D modeling (Maya or Blender) of both mechanical and organic elements, HCI, and Environmental Science. This FYREE project will involve designing a test for students of middle school age to try out the VR product and provide feedback on the experience.
Environmental Health and Safety app development
Primary contact: Emily Monroe
Focus: Software and human centered design
To keep people safe, Dartmouth's office of Environmental Health and Safety (EHS) and Hanover Fire Department track confined spaces on campus, describing the space and who can access the space as well as provide a log of the use of the space. In this project a database platform would be developed to be used by many types of users, including Dartmouth FO&M personnel, firefighter/EMTs, professors, and EHS engineers. Software and environmental engineers would work together to build this platform.
Human-centered engineering projects and activities
Thayer is working on creating a new human-centered engineering pathway as an alternative to the standard prerequisite-focused pathway. This new pathway will include five new courses that are project-based, human-centered, and that integrate math, engineering, and science. On this pathway, students will learn necessary foundational mathematical concepts in the context of engaging, hands-on project-based learning activities, centered around topics that are human-centered and resonate with students’ interests and backgrounds. We are looking for first-year students who are interested in working with us to research, design, prototype, and test different hands-on, project-based activities that can be used in this series of courses. FYREE students will start by reviewing projects and activities associated with a similar curriculum that is offered at Princeton and then work to adapt activities and projects for use at Thayer.
Data visualization and mapping of energy systems
Faculty: Erin Mayfield
This project will include geospatial analysis and mapping of energy infrastructure, land use, air quality impacts, and labor impacts associated with future decarbonization pathways in the US.
Recommended background: Familiarity with geospatial software.
Autonomous observations of Arctic sea ice
Faculty: Don Perovich
Mentor: Ian Raphael
The Arctic sea ice cover is a key indicator and amplifier of global climate change. Autonomous instrument platforms are an important means of observing this remote, but critical, region. This research position will have two main components:
- working with data from sea ice mass balance buoys
- building a network of sensor to measure snow depth and snow ice interface temperature.
The sensor network will be deployed in the Arctic Ocean in September 2023. This research will encompass data analysis and instrument development.
AdhE complementation in E. coli to enable protein engineering for biofuel applications
Faculty: Daniel Olson
Mentor: Angel Pech (postdoc)
Clostridium thermocellum is an anaerobic bacterium that is a promising candidate for producing biofuels, such as ethanol, from cellulose. However, it does not produce ethanol at high enough concentrations for commercial application. AdhE is a bifunctional enzyme that plays a key role in ethanol production in C. thermocellum. We are interested in performing protein engineering on the AdhE protein to enable increased ethanol produciton by C. thermocellum. The protein engineering technique we are using is called deep sequencing mutagenesis. One problem with this technique is that it produces a large number of inactive variant proteins. We plan to identify these inactive variants by screening a library of mutants in E. coli. The first step is to demonstrate that the adhE gene from C. thermocellum can functionally complement an adhE deletion in E. coli. In the course of this work, students will learn basic molecular biology and microbiology techniques.
Flexible decision making in medicine
Faculty: Wesley Marrero
Translating medical decision-making models into practice is difficult. Despite the many models developed to improve sequential decision making in medicine, those models typically cannot be implemented in their current form. A single recommendation may not be enough, as physicians have their decision processes. Moreover, medical practitioners may interpret guidelines as cumbersome, confusing, and lacking in credibility. It is, therefore, essential to consider practical implications in the design of decision rules. One way such implications can be considered is by providing physicians with flexibility in implementing guidelines. My team and I design sequential decision-making models that provide physicians with multiple suggestions instead of rules, while continuing to improve patients’ outcomes. Medical practitioners and their patients can choose between potential courses of action with similar outcomes based on their opinions, preferences, or other factors. The focus of the FYREE project will depend on the student’s interests. It could range from the application of decision-making models to the design of a decision-support tool. We seek a student interested in operations engineering and statistics. The ideal student should have some coding experience. Although medical knowledge is not required, we expect the researcher to be open to learning about medical domains. The FYREE student will work closely with graduate students, engineering and statistics professors, and medical researchers within and beyond Dartmouth.
Continuum robotic manipulator design
Faculty: Ryan Halter
Traditional robotic manipulators move end effectors (tools, instruments, etc.) by reconfiguring a series of rigid links via revolute (rotating) or prismatic (sliding) joints. In applications with tightly-constrained workspaces like sinus and skull base surgery, it can be advantageous to instead produce motion by changing the shape of a continuously-deformable material. A variety of continuum robots are being proposed and developed for this type of surgical application.
Our lab is interested in developing a similar flexible robotic system for manipulating custom surgical imaging probes used in minimally-invasive surgical procedures. We are at the very early stages of this exploration. In addition to supporting senior honors thesis work on developing an overall robotic system for evaluation, we are seeking undergraduate researchers to work with us on designing, prototyping, and modeling the motion of new continuum architectures that are compatible with intraoperative imaging.
This project may require some work in our lab at Dartmouth-Hitchcock Medical Center which is accessible by bus (either AT Blue or Dartmouth Campus Connector).
- 3D printing
- Familiarity with materials science
Small form-factor electrode tracking for space-deployable US-EIT system
Faculty: Ryan Halter
We are developing a space-deployable ultrasound and electrical impedance tomography (US-EIT) system for imaging deep internal bleeding/injury. In order to achieve sensitivity to deep internal structures, we need electrodes on the ultrasound probe as well as opposite the anatomy of interest (e.g. for abdominal imaging, electrodes may be placed in a ring around the torso in order to acquire impedance measurements throughout the abdomen). Knowing the precise locations of these electrodes is critical to reconstructing the US-EIT image, so electrode tracking is required. On Earth, tracking solutions exist (e.g. optical, electro-magnetic (EM), mechanical, etc.), but a space-deployable system will require a small form-factor (low mass/volume) and low emission (low EMI) solution. We are looking for a student to research (and eventually test) potential real-time tracking solutions that fit within narrow mass/volume constraints.
Mechanical probe housing validation for minimally invasive EIT probe
Faculty: Ryan Halter
We are developing an electrical impedance tomography probe for use in minimally invasive surgical procedures to determine the presence of cancer along the surgical margins. There is currently a concept of all of the components and 3D housing, we are seeking help to validate this design. This project would include 3D printing, post processing materials, and validating that mechanical probe housing works as expected with incorporated components and with the da Vinci surgical robotic system. Opportunities to adjust the housing using Solidworks based on testing results is available but not a requirement. Other opportunities to engage in data collection/experiments exist based on interest and availability.
How to Apply
FYREE projects are two consecutive terms occurring over Winter and Spring.
2022–2023 application deadline: October 24
- Apply to either the FYREE program or the Women in Science Project (WISP), but not both.
- Review list of available projects above and make a selection.
- Submit an online application form for each project before the deadline listed above.
- Not all applicants will be contacted for an interview, nor admitted. (We always have more applicants than we do projects. If you are not selected, we encourage you to reach out to faculty directly if interested in their research.)
- Faculty mentors will interview applicants and select a student for each project.
- Decisions will be made prior to the start of term.