students doing research in lab

Promoting Undergraduate Research Experiences


Undergraduate summer research is an opportunity for CEMS students to experience working in a research environment and to develop a personal relationship with a faculty member. The CEMS Summer Research Experience for Undergraduates (REU) provides a stipend of $4000 to the student to support full-time research effort over a summer period. This amount is paid $2000 from a faculty grant or contract and $2000 from the College Dean’s Office. Any undergraduate CEMS student is eligible to apply, although preference will be given to students in their sophomore or junior years. Senior students graduating in May are only eligible to apply if they are admitted to a CEMS Accelerated Master’s Program (AMP) and will be continuing as an M.S. student in the fall.

The proposed project must fit within the general research area of the faculty advisor. In this way, undergraduates have the opportunity and resources to pursue independent research as well as work closely with active faculty members who are leading scholars in their fields. Project ideas can be independently generated by the student or selected from research topics that have been described by faculty members. It is expected that faculty mentors will be on campus for the majority of the summer and available to mentor the student.

The program is structured to reflect the application process and the execution of a program that would typically be funded by an external granting agency:

  • Students are required to submit an application describing a specific research project to be completed under the direction of a faculty mentor;
  • Applications are evaluated by a panel of UVM College of Engineering and Mathematical Sciences faculty, and the top ranked proposals are elected for funding; and
  • Awardees carry out the research during a single summer, create and present a poster describing their work and their results, and submit a final report detailing the outcomes.
  • In many instances, results may be suitable for presentation at regional or national conferences and/or publication.

How to Apply

CEMS Summer REU Application Dates:

Applications Open: Wednesday, January 6, 2021
Applications Due: Friday, March 5, 2021

To Apply: Please read the Program Guidelines (linked below) for detailed instructions and then apply on Handshake at https://uvm.joinhandshake.com/jobs/4160021 for job #4160021.

CEMS Summer REU Program Guidelines 2021 (PDF)

Application Cover Guide (PDF)

Academic Year 2018-2019 REU Participants

DeptLast NameFirst NameFacultyProject
EETranKhangEva CosoroabaBattery Management using a Buck-Boost Converter for Microgrid Applications
EESychykovValeriyJimModular Analog Computer Design with Control System Applications
EEBerneSophieEva CosoroabaAnalysis of and Strategies for Vermont's Energy Transition
EEPetersonKarlTian XiaAutomobile collision detection using radar
BMEWarrenRoseRyan McGinnisDeveloping a Musculoskeletal Kinetics- and Kinematics-Based Algorithm for Fall Prediction in Patients with Multiple Sclerosis
BMEMcGillMadeleineDrs. Menon and BatesVentalect, a communication tool for patients on mechanical ventilation
BMECareyAllisonDrs. Menon and BatesVentalect, a communication tool for patients on mechanical ventilation
BMEBarakyGraceDrs. Menon and BatesVentalect, a communication tool for patients on mechanical ventilation
BMEFisherIsabelleDrs. Menon and BatesVentalect, a communication tool for patients on mechanical ventilation
M&SMyhaverVanessaDoraisFormalizing theorems of linear algebra: The project consists of building computer verifiable proofs of theorems in linear algebra using the Lean Theorem Prover, a new proof assistant developed by Microsoft Research and Jeremy Avigad (Carnegie Mellon) https://leanprover.github.io/. This is intended as part of a long-term REU program for mathematics and computer science students. The goal is to have students contribute to the growing library of computer-verified proofs. The three students team will contribute by formalizing theorems of linear algebra and building on earlier work done by Vanessa over the Summer. This work is especially important since linear algebra was identified as an area of need at a recent meeting in Orsay.
M&SStupinskiAnne MarieDoraisFormalizing theorems of linear algebra: The project consists of building computer verifiable proofs of theorems in linear algebra using the Lean Theorem Prover, a new proof assistant developed by Microsoft Research and Jeremy Avigad (Carnegie Mellon) https://leanprover.github.io/. This is intended as part of a long-term REU program for mathematics and computer science students. The goal is to have students contribute to the growing library of computer-verified proofs. The three students team will contribute by formalizing theorems of linear algebra and building on earlier work done by Vanessa over the Summer. This work is especially important since linear algebra was identified as an area of need at a recent meeting in Orsay.
M&SThomasHeleneDoraisFormalizing theorems of linear algebra: The project consists of building computer verifiable proofs of theorems in linear algebra using the Lean Theorem Prover, a new proof assistant developed by Microsoft Research and Jeremy Avigad (Carnegie Mellon) https://leanprover.github.io/. This is intended as part of a long-term REU program for mathematics and computer science students. The goal is to have students contribute to the growing library of computer-verified proofs. The three students team will contribute by formalizing theorems of linear algebra and building on earlier work done by Vanessa over the Summer. This work is especially important since linear algebra was identified as an area of need at a recent meeting in Orsay.
M&SKotzenBenTaras LakobaA stability analysis of a numerical scheme that simulates so-called coupled-mode equations by a Method of Characteristics: Recent numerical experiments by a colleague of mine revealed an unstable behavior of this scheme when noise is being added during the calculations to simulate the physically occurring noisy field. We are trying to come up with an analysis that would explain these observations, and at the end hope to propose a modification of the numerical scheme that will not have such a numerical instability.
M&SHirschLauraMaggie Eppstein (CS),  Donna Rizzo (CEE),  collaboration with Dr. Robert Gramling, (Medicine)Assessing the quality of medical caregiver communication is a time-sensitive endeavor and may infringe on patient privacy.  To address these issues, the Vermont Conversation Laboratory is conducting research into automated assessment of quality of conversations using machine learning. Over last summer, Laura helped us to quality-control on transcripts of audio recordings of real palliative care consultations and conducted some preliminary data analysis. During this academic year, Laura will be conducting exploratory research using natural language processing and machine learning from these transcripts, to help us try to identify signatures of effective conversations. For example, among other things she is exploring whether patterns in duration of clinician/patient speaker turns are associated with the degree to which the patient later reported feeling heard and understood.  This work involves significant creating thinking, programming in Python, and principled application of various statistical and machine learning approaches.
CS/CSYSWilliamsBlakeLaurent Hebert-DufresneThis project will evaluate the resilience of real-world influenza A (H3N2) hemagglutinin genotype networks to host immunity and compare resilence with a space of simulated networks.  Real-world networks will be generated from NCBI database protein sequences.  Features of the real-world networks will be analyzed, and features of resilient networks will be identified through multi-strain compartmental modeling. Utilizing networks will offer a complementary view to the phylogenetic trees commonly used in analyzing the evolutionary dynamics of influenza subtypes.
CSStuntzLindseyChristian SkalkaThe student will explore new technologies for improving security in modern networks, including networks that underly the Internet. In particular, the student will explore techniques for automatically guaranteeing that network routing configurations adhere to stated policy, and that any changes to configurations are properly authorized. A secondary goal of this project is to synergize UVM research with the student's internship work at Amazon Web Services.
CSDuvalBenRobert EricksonThe responsibilities for an undergraduate student will be to conduct fact-finding meetings with the client to document their needs.  The current side is working but needs several additions that will require more coding. This is a great opportunity for one of our students to apply existing knowledge as well as branch out into areas of Development they have not explored yet. Languages needed: HTML, CSS, PHP, MySQL
CSDoEdmundByung S. LeeThis project aims to build a software program that converts 12-lead ECG data to multi-dimensional VCG data and visualizes the VCG data.  Public data available from PhysioNet will be used as the ECG data, and Python libaries will be used for VCG visualization over a selected set of dimensions.
CEEHancockKevinPriyanthan WijesingheKevin will study new bio-inspired structural forms that can be utilized at the organism level as freestanding structural forms. He will also research the demanding material properties and analysis techniques and tools required to make these structures a reality.
CEEGilliesMerrickMandar DewoolkarAbout thirty percent of world's housing is made of adobe, air-cured large bricks made out of soil often mixed with some straw. These structures are heavy and unreinforced making them vulnerable in seismic regions. This project will assess strengths of adobe and grouts individually and as a unit.
CEEThorneHeidiMandar DewoolkarWe are conducting research developing and applying machine learning algorithms to help us understand what factors contribute to the effectiveness of clinical conversations with seriously ill patients.  Using audio recordings of 363 palliative care conversations, we are currently focusing on two sub-projects, as follows. (1) Connectional Silences: Human connection is an essential component of palliative care conversations. Some moments of silence amid such conversations indicate such human connection. Our preliminary work demonstrates capacity to use machine-learning to identify pauses in conversation and human coding to reliably classify pauses as “connectional” or not. (2) Temporal Attribution & Affect:  Palliative care conversations involve reflection on the past, understanding the present and contemplation of the future in a highly emotional context of medical decision-making. These two elements—time and affect—are conceptually “findable” using text processing methods and are likely to mark different clinical “types” of conversations that are likely to lead to different outcomes (eg. treatment choices, quality of life).  The three undergraduate research assistants will assist in both of these projects through various tasks including data pre-processing of conversation transcripts, audio screening of pause clips identified by our machine learning algorithms, helping to compile a corpora of temporal reference words and phrases, and exploratory data analysis.
CEERomeroEricScott HamshawResearch will involve GIS and Matlab analysis of sediment data several watersheds throughout Vermont. These watersheds include but are not limited to: Lewis Creek, Shepard Brook and Mill Brook watersheds. The goal of this research is to analyse turbidity-TSS relationships in the various watersheds, characterize the land cover, geomorphology, geology, road network and hydrology upstream of sensor monitoring locations and to process and analyze time series of river discharge and turbidity/TSS (Total Suspended Solids) collected at other monitoring sites throughout Vermont.
CEEJobin-DavisElizaDewoolkar, Rizzo, GarciaEducational modules using augmented reality sandbox

 

Interested? There are many opportunities for undergraduate research in CEMS!