Computational Imaging Science Laboratory
Contact information:
maa@illinois.edu
Research summary:
My research program is related to computational imaging science. Specifically, we develop and investigate new mathematical and computational methods for forming biomedical images and extracting information from them. Much of our recent work also incorporates machine learning.
Ideal applicant should have:
Computer coding experience beyond Matlab. For example, Python or C++ are used in our work. Students should also have proficiency in linear systems theory and linear algebra, at a minimum. Familiarity with machine learning is also required for many of our projects.
When to apply:
On a rolling basis.
Biophotonics Imaging Laboratory
Contact information:
(217) 244-7479
boppart@illinois.edu
4351 Beckman Institute
Research summary:
The Biophotonics Imaging Laboratory is a highly interdisciplinary research group focused on developing novel optical imaging and sensing technologies, and then applying them toward clinical applications and biological discovery. We develop new optical imaging hardware systems, including new laser and light sources, as well as novel computational imaging approaches including AI and machine- and deep-learning algorithms to extract more diagnostically-relevant optical signatures and biomarkers from cells and tissues. Our new optical technologies are demonstrated in applications with tissue phantoms, cells and tissues in culture, and pre-clinical and clinical studies.
Ideal applicant should have:
Students with interests and backgrounds in optical imaging and microscopy who are curious, like to tinker and explore new ideas, and who like to work hands-on building optical imaging systems are likely to do well in BIL. Having experience in programming in LabView, MATLAB, and GPUs would be useful too.
When to apply:
It is always helpful to check with Prof. Boppart about 1-2 months before the start of each semester or summer to see if there are openings on projects in the lab.
Research Assistant testimonial:
Elisabeth Martin, Class of 2022“BIL is an amazing community of scientists and engineers. We’re a large group, and this gives amazing opportunities for collaboration as well as a diverse set of projects which use optical imaging to address complex challenges in fields such as cancer, infectious disease, and neuroscience. My research mentor has primarily been a graduate student; I have also received support from other graduate students and post-doctoral scientists. Prof. Boppart and others in BIL have given me a lot of support to apply for grants and fellowships, present my research on campus and at national conferences, and apply for medical school. My work in lab has been varied over the past 3 years; I have done cell culture work and experimental design of cell-based experiments, assistance with optical imaging of samples, image processing and data analysis with MATLAB, and assistance with building a new optical system. I was encouraged to take ownership in my project and develop skills as an independent researcher such as planning experiments, discussing my conclusions from data and future directions during biweekly updates, and finding new materials to assist with my project. Overall, I highly recommend BIL. If you demonstrate commitment to your research and the lab, they are willing to invest a lot in you and help you reach your professional goals as well as your research goals.”
Experimental Molecular Imaging Laboratory (EMIL)
Contact information:
(217) 244-3938
dobrucki@illinois.edu
4261 Beckman Institute
Insana Lab: Ultrasonic Imaging
Contact information:
(217) 244-0739
mfi@illinois.edu
4247 Beckman Institute
Research summary:
My research is in medical imaging. Specifically, I use ultrasound to image blood perfusion in the extremities of diabetic patients to allow physicians to intervene before patients develop peripheral vascular disease. This is a joint effort between my lab and two others in Bioengineering, faculty in Vet Med, and collaborators at the Mayo Clinic and the Univ of California Santa Barbara. I also develop machine learning methods for cancer imaging based on ultrasonic imaging technologies.
Ideal applicant should have:
I look for students with skills in computer modeling. I teach these topics so I see that this is not a skill set among many undergrads. I have worked with a few, who did a great job on projects.
When to apply:
I will consider students any time of the year. I realize that students have strong demands on their time at different times of the year. I can deal with those constraints.
Research Assistant testimonial:
I do not have current students. It has been a couple years since I have had UGs in my lab.
JI Labs
Contact information:
(217) 300-0525
jirudaya@illinois.edu
3102 Micro and Nanotechnology Lab
Research summary:
Ideal applicant should have:
When to apply:
Research Assistant testimonial:
Sid Srikumar, Class of 2023“I have really enjoyed my experience at the Irudayaraj Lab. Getting to work in the Mills Breast Center has been a surreal experience and I have learned so much, even though I have been there for such a short time. My work is mostly independent, as in, I am assigned objectives for the week and it is my prerogative on how/when to complete them. My work mostly revolves around passaging, treating, and imaging HepG2 liver carcinoma cells. Additionally, I also have performed RT-qPCR analysis on plasmids that have been modified with restrictions enzymes and replicated in bacteria. I usually work 12-14 hours a week since my schedule allowed it, but my grad student is very flexible around my schedule and it has been great to not have to worry about something coming up suddenly since I know that my grad student can help me out.”
Lam Laboratory
Contact information:
(217) 300-3713
fanlam1@illinois.edu
4061 Beckman Institute
Research summary:
My research focuses on developing and applying neuroimaging technologies to advance the understanding of complex brain functions, diseases, and to enable better diagnosis, treatment and management of central nervous system disorders. Specifically, our interests include MRI (magnetic resonance imaging), MRI-based molecular imaging of the brain, multimodal brain mapping and computational imaging techniques.
Ideal applicant should have:
We are looking for students who are interested in biomedical imaging technologies, and have experience and strong interest in signal processing, computational modeling and the applications of imaging technologies to neuroscience and/or neurological diseases. Students who are self-motivated, like to solve technical programs and/or like to hone their imaging experimental skills (in MRI particularly) are preferred.
When to apply:
No specific time. We are always looking for motivated undergraduate students who would like to have more research experiences in neuroimaging, computing and performing imaging experiments, to join our group.
Nie Lab
Contact information:
(217) 300-1266
nies@illinois.edu
2116 Everitt Lab
Smith Lab
Contact information:
(217) 300-5638
smi@illinois.edu
2136 Everitt Lab
Research summary:
The Smith Lab develops molecular probes to analyze and image biological molecules such as proteins and nucleic acids. We use these probes to image dynamic microscopic processes in living cells, to quantify disease biomarkers in blood, and to analyze disease processes in tissues from animal and clinical patients. We further develop drug delivery technologies for the immune system in order to modulate how macrophages and monocytes impact diseases including obesity, diabetes, cancer, and Alzheimer’s.
Ideal applicant should have:
The most important personal qualities are curiosity, motivation, and interest in the scientific fields in which we work, particularly chemistry, molecular biology, and imaging. We require no hands-on skills, but students must have a minimum cumulative GPA of 3.45. We usually only consider sophomores and juniors, and require a 1-year commitment, with 8-10 hours of committed time per week during the fall and spring terms.
When to apply:
The best time to apply is at the end of summer. At other times, usually all researchers are consumed with projects and/or working with other undergraduate students.
Research Assistant testimonial:
We do not currently have undergraduates working in our lab due to the pandemic. We hope to open the lab to undergraduates again in fall of 2021.
Magnetic Resonance Functional Imaging Lab
Contact information:
(217) 244-5154
bsutton@illinois.edu
1215C Beckman Institute
Research summary:
In MRFIL we develop new ways to image and quantify changes to the brain using the non-invasive method of magnetic resonance imaging (MRI). We develop new ways to measure pathology in the brain, but also age-related tissue changes, through a variety of image contrasts, including brain structure, function, blood flow, and mechanical properties of the brain. We also work on computational methods to reconstruct more accurate images and to extract information from the images about the physiology being examined.
Ideal applicant should have:
We are looking for signal processing, statistics, computer skills – including analyzing data with MATLAB and python, along with experience on Linux systems.
When to apply:
Beginning and near the end of the semester are the best times to reach out. CV with listed skills would be most helpful.
Research Assistant testimonial:
Nishant Bhamidipati, Class of 2024“Before getting this position, I had no idea about who to ask or where to find research positions, so I reached out to the undergraduate research advisor of the Undergraduate Neuroscience Society RSO after sending a couple of emails to professors at different labs. After informing him of my skill set and my career goals, he told me that Dr. Sutton had a project available that fit perfectly – in other words, I began reaching out to anyone I could until I stumbled upon an available position. This position had a heavy focus on computational bioengineering and computer science while also relating back to neuroscience. Throughout my time working at this lab, my responsibilities have revolved around data visualization and analysis, which has included making a website with graphs generated from an excel sheet and performing descriptive statistics on the data. Due to the nature of the project, I work mostly remotely and during times that are most convenient for me, with extremely supportive weekly meetings to discuss progress and next steps. Aside from building skills directly related to data analytics, being a part of my current project has honed my interpersonal skills, my ability to work independently as a part of a bigger team/project, and, most importantly, my capacity for distinguishing when and how to ask for help.”