Past Research Trainees

 

2023 Research Trainees

 
 

nischal khatri, colby college

During this internship, I had the incredible opportunity to work alongside Dr. Kei Ouchi and his lab team to enhance conversations about end-of-life care and advance care planning between patients with serious illnesses and their physicians. Using Clinical Regex, a natural language processing software, I filtered and annotated medical records to assess whether an ED intervention called EDGoal led to increased conversations about end-of-life care and advance care planning engagement with their physicians. In addition to data analysis, I assisted the team by performing weekly enrollment calls to recruit patients for the research study. This fall, I am starting my senior year on the pre-med track as a double major in music and biology, neuroscience!

 
 
 
 

Sindhuja uppuluri, university of pennsylvania

This summer, I had the pleasure of working under PI Dr. Emily Ruiz on two different projects in the Mohs and Dermatologic Surgery department. My first project entailed looking at the incidence of cutaneous skin cancer in immunosuppressed patients in order to quantify risk and provide disease-specific recommendations. My second project focused on the impact of Tranexamic Acid (TXA) on bleeding complications in Mohs Micrographic Surgery. Manuscripts will be submitted for both projects following completion. This fall, I will also begin my final year at the University of Pennsylvania studying Neuroscience and Health Care Management.

 
 
 
 

emma yu, northwestern university

This summer, I was paired with Dr. Alexander Turchin in the Endocrinology department. With Dr. Turchin, I am working on the Canary project, an NLP tool designed to help clinicians and medical researchers extract information from unstructured EHR data. Specifically, I am testing whether implementing topic segmentation improves the performance of the Canary NLP tool. Also, I am interpreting Python code for a BERT neural network model project. I received my BA in Neuroscience and Data Science from Northwestern University this year.

 
 
 
 

sandhini agarwal, University of chicago

This summer, I worked under Dr. Erik Alexander in the Department of Endocrinology to investigate the correlations between thyroid nodule mutations, surgical pathology, and patient outcomes with thyroid cancer. My project involved analyzing the genomic data of patients from EPIC to understand the genotype-phenotype relationships of thyroid nodules. I recently graduated from the University of Chicago with a Bachelor of Science in Biological Sciences and a minor in Health and Society.

 
 
 
 

Lulu bi, brown

I am a senior at Brown University studying Biology, and I will attend Warren Alpert Medical School next year. As a member of the Golby Lab for Image-Guided Neurosurgery, I am working under Dr. Alexandra Golby and Dr. Sarah Frisken on NousNav, a neuronavigation system designed to be affordable, portable, and open-source to make it accessible to low and middle-income countries. This summer, my project focuses on the skin segmentation step of NousNav; it involves manually segmenting brain scans of healthy patients and training a deep learning segmentation model (U-net) using this data set.

 
 
 
 

Caroline conway, dartmouth

This summer, I have the privilege of working with Dr. Alexandra Golby and Dr. Yanmei Tie in the Image-Guided Neurosurgery Lab. We are working to develop a naturalistic paradigm to map patient brains before neurosurgery using functional magnetic resonance imaging (fMRI) and movie clips. We are particularly interested in identifying language and emotion areas of the brain in order to maximally preserve function in these regions and avoid damage during surgery. I am recruiting subjects for the study and evaluating the emotional content of various movie clips in order to select the videos best suited for the fMRI portion of the project. This includes working with data from the VADER sentiment analysis Python program. This fall, I will begin my senior year at Dartmouth College, where I major in Cognitive Science and minor in Hispanic Studies.

 
 
 
 

Gabby rickards, Colby

This summer I have the pleasure of working with Dr. Marie McDonnell, the director of the Diabetes Program at BWH. So far, I have utilized Epic records and entered patient data into an electronic data capture (EDC) system. This data is being use dto examine the effectiveness and safety of continuous glucose monitoring (CGM) systems in non-critically ill patients in the inpatient setting. I also am writing a white paper to investigate how GCM use in the hospital can impact care outside of the hospital and help promote medical technology equity for patients with diabetes. In the fall, I will be entering my senior year at Colby College where I am majoring in Biology with a concentration in Neuroscience and a minor in Math.

 
 
 
 

shreya vailaya, stanford

I am a senior at Stanford University studying Bioengineering and Music. This summer, I worked under Dr. Irene Ghobrial at the Dana Farber Cancer Institute to characterize genomic biomarkers that predict patient’s risk of progression from asymptomatic precursor stages of Multiple Myeloma - mGUS and Smoldering Multiple Myeloma - to advanced Multiple Myeloma. My project had two components. The first component involved performing EPIC chart reviews to capture clinical and biological variables, such as monoclonal immunoglobulin biomarkers, demographic data, and laboratory results, and recording patient data in the REDCap database. In the second part of the project, I focused on developing longitudinal linear regression and correlation models using Python to track clonal dynamics and predict risk of progression based on enumerated circulating tumor cell (CTC) biomarkers from liquid biopsy.

 
 
 
 

Larry shue, princeton

This summer, I am working with Dr. Rosh Sethi on a correlational study to determine how different treatments for head and neck cancer patients may impact their quality of life. This project involves compiling a large dataset of patient information for head and neck cancer patients and using statistical software for correlational analysis. I have recently graduated from Princeton University with a concentration in Molecular Biology and a minor in Bioengineering. I will soon be starting a PhD in the Biological and Biomedical Sciences program at Harvard Medical School. 

 
 
 
 

valeria zuluaga-sanchez, princeton

This summer, I am working under Dr. Gregory Piazza in the Thrombosis Research Group of the Department of Cardiology. My project focuses on identifying trends between the incidence of venous thrombosis, embolism, and other cardiovascular events such as heart failure and COVID-19 illness in different patient populations, such as the elderly, vaccinated and unvaccinated groups, and those who have been administered medications such as corticosteroids or antiviral agents. I perform EPIC chart review to obtain information about diagnosis date, treatment, risk factors for developing adverse cardiovascular events, and incidence of cardiovascular problems 30-days and 90-days after diagnosis. I then enter this data into a REDCap database. This fall, I will be entering my senior year at Princeton University, where I am concentrating in Neuroscience with a minor in Creative Writing.

 
 
 
 

SUNDEEP CHAkladar, MIT

This summer, I have worked under Dr. Chris Baugh on a project investigating the emergency department visits of cancer patients presenting with non-neutropenic fever. We want to understand how this group can be triaged more effectively to combat emergency department overcrowding. I performed hundreds of chart abstractions, inputting EPIC data into a REDCap database. I am a rising senior at MIT where I am majoring in Biology and minoring in Science, Technology, & Society.

 
 

2022 Research Trainees

 

anna chen, Colby

I have been working with Dr. Emily Ruiz this summer on her dermatologic oncology research. I have been going through REDCap and  Epic records to identify metastasis and recurrence in basal cell carcinoma patients, and logging the treatments for each recurrence. I have also been working with Dr. Ann Silk and Dr. Manisha Thakuria on merkel cell carcinoma patients, and evaluating cell free DNA as a prognostic indicator. I have been going through 130+ oncologic records and Epic records, while making a REDCap database. I am starting in my senior year at Colby College as a computational biology major and chemistry minor, on the pre-med track!

 
 
 

libby czarniak, dartmouth

In the fall, I will be entering my last term at Dartmouth College where I am working towards my Master’s in Health Data Science. For my summer internship, I am matched with PI Dr. Alexandra Golby and Dr. Étienne Léger, who both work in the Golby Lab for Image-Guided Neurosurgery. My project is focused on NousNav, which is a neuronavigation system designed to be low-cost and less resource intensive. I am using virtual data to develop a pipeline that utilizes various methods to register point clouds. Within this pipeline, I am recording different metrics reflecting registration accuracy in order to determine which method is most useful for registration.

 
 
 

vem nazarian, middlebury

During this internship, I work under PI Dr. Irene Ghobrial on a project that focuses on designing a model to predict the risk of Multiple Myeloma progression for patients with precursor conditions, MGUS and Smoldering Multiple Myeloma. I perform EPIC chart review to identify serial timepoints of clinical and biological variables, such as demographic data, dates of diagnosis, and laboratory results, for patients with high-risk of progression. I then record patient data in a REDCap database. Currently, I am completing my final semester at Middlebury College, studying Molecular Biology and Biochemistry.

 
 
 

soobin choi, cornell

This summer, I worked under PI Rosh Sethi on a prospective study researching the role of personal social networks in care seeking and treatment outcomes in head and neck cancer patients. I performed EPIC chart reviews and consolidated pertinent diagnostic and treatment information into REDCap. I also learned interview techniques and how to conduct semi-structured interviews with patients, as well as transcribed interviews in order to be used for thematic analysis. I also learned about network science methods and how personal network data can be analyzed. I explored the data collected via PERSNET, a validated survey instrument, to begin characterizing the social network landscape of head and neck cancer patients. I am now a senior at Cornell University, where I am majoring in Biomedical Engineering and minoring in Information Science and Psychology.

 
 
 

sarah chacko, dartmouth (bs and md)

This summer, I am working under Dr. Alexandra Golby and Dr. Nazim Haouchine to investigate the use of depth maps in reducing the financial barriers to image-guided neurosurgery. My project involves training a convolutional neural network on computer-generated images to predict camera positions. I also developed a base of training and testing data by writing code to store camera positions with their depth maps. I am a senior at Dartmouth College studying Computer Science and Biology, and I will be attending the Geisel School of Medicine after graduation.

 
 
 

paula remon baranda, dartmouth

I am a current Master in Engineering Management student at Dartmouth College. During the internship I worked under Dr. Chris Baugh on a project for End of Life Transitions to Hospice for Patients with Cancer visiting the Emergency Department. My tasks included literature review, help with the development of the data entry tool in REDCap and used EPIC-records to perform chart abstraction.

 
 
 

Francesca Abulencia, brown and emory

This summer, I worked with Dr. Ghobrial and her data annotation team. I contributed to the PANGEA project which is a longitudinal clinical study of patients with early precursor conditions (MGUS and SMM) for Multiple Myeloma. The goal of the project is to improve current models of risk progression by creating a large database of precursor patients and tracking the changes in their clinical variables over time. I conducted Epic chart review and reviewed lab results and bone marrow biopsies to record their clinical variables every 6 months and to also determine relevant dates that mark a patient’s diagnosis and the progression to active disease on REDCap. I graduated from Emory University with a BS in Engineering Science, and I am currently pursuing an MS in Biomedical Engineering at Brown University.

 
 
 

kyra howard, brown

This summer, I am working under Dr. Marie McDonnell, the director of the Diabetes Program at BWH, to investigate how various characteristics such as A1c affect outcomes for diabetes patients who are hospitalized with COVID-19. For this study, I perform data analysis in REDCap and Excel on a multi-institutional patient database to identify trends and help determine future research directions. Additionally, I enter patient data into an electronic data capture (EDC) system for a separate clinical study on the accuracy of continuous glucose monitoring in hospitals. I am entering my senior year at Brown University, where I am concentrating in applied math and biology.

 
 
 

joy xie, princeton

I work under PI Alexander Turchin on the Canary Project in the Endocrinology Department. My project involved testing new functionalities of Canary, a natural language processing platform and using them to develop natural language processing tools. This is an important component of the overall project that will help develop more accurate natural language processing tools that will ultimately be used in clinical research. I recently completed a Bachelor’s in Biology with minors in Finance and Global Health at Princeton University.

 
 
 

ARmaan rathi, upenn

I’m currently a Master’s student at the University of Pennsylvania and am pursuing a dual degree in Biotechnology along with Computer and Information Technology. This summer, I was paired with Dr. Kei Ouchi and worked alongside his team on a project centered around advanced care planning. I screened over 500 patients from the Emergency Department’s recent discharge list every week on EPIC and logged the ones who qualified for the study. I also made calls to some of the patients who met the criteria for the study in order to schedule them for enrollment if they were interested in participating. Finally, I used Python to clean up and organize the log data and used R to generate a consort diagram from it that would track the flow of patients through the various stages of enrollment and analysis.

 

2021 Research Trainees

 

Catie Riley, colby

I recently graduated from Colby College with degrees in Biology and Government while following the Pre-Med Track. This summer, I worked under PI Kei Ouchi to assist with three research studies focusing on Palliative Care and Advanced Care Planning (ACP) in the Emergency Department (ED) setting. For these projects, I utilized EPIC-records to screen the patient discharge list and ED trackboard from the Brigham and Women's Hospital ED to determine which patients were eligible to participate in our study. Using inclusion/exclusion criteria I screened approximately 40-100 patients per day (varied depending on number of patients discharged). I organized EPIC-patient data using REDCap and LabArchives tools to create comprehensive data records. Additionally, I helped lead enrollment Zoom calls with study participants, caregivers, and an enrolling clinician. During these enrollments I ensured all study procedures were completed and provided feedback to the enrolling clinician.

 
 
 

Alexa Conomikes, columbia

This summer, I had the opportunity to work with Dr. Emily Ruiz on her dermatologic oncology research. My project specifically focused on studying eccrine carcinoma diagnosis, which are rare skin cancers of eccrine sweat glands. Using REDCap for database building, I performed 180+ EPIC chart reviews, coding for patient history, pathology and imaging results, treatment strategies, and final disease outcomes. This fall, I will work to finish the last semester of my bachelor’s degree in biology at Columbia University, while also competing in my final NCAA field hockey season.

 
 
 

YuhJong Liu, upenn

I worked under PI Alexandra Golby and Dr. Nazim Haouchine to investigate registration methods between depth camera data and MRI/CT scans. My project involved registering different source faces to transfer labels between the two. I developed a pipeline in Python to preprocess head meshes, register faces, and label various regions of a face. I also assessed registration results through analyzing fitness measurements and examining rotational and translational robustness. I am currently finishing my Master’s in Scientific Computing at the University of Pennsylvania.

 
 
 

Katie Downey, mit and bu

During this internship, I worked under Dr. Ghobrial on a project using serial data points to establish a new model that aims to identify earlier clinical biomarkers of Multiple Myeloma progression. I used Epic chart review to add additional lab values, identify outliers, and perform quality-control on previously entered values in a REDCap database. I recently graduated from MIT with a BS in Biology and I am now starting a MS in Medical Science at Boston University and I will continue to work with the Ghobrial lab as a research assistant in the fall.

 
 
 

Abby Recko, colby

I was matched with PI Alexandra Golby, director of the Golby Lab for Image-Guided Neurosurgery. Within the lab, I worked with Yanmei Tie and Einat Liebenthal to develop a database of film stimuli to be used in presurgical language and emotion mapping with fMRI, as well as emotional reactivity assessment in patients with mood disorders. To evaluate the effectiveness of these stimuli, I collected multiple hours of pilot data and presented the preliminary findings to members of the Golby lab. I am now a senior at Colby College, studying neuroscience and religion, and continuing to work for Drs. Tie and Liebenthal remotely.

 
 
 

Sally Hwang, columbia

I worked under PI Erik Alexander to process, label, and recall a preliminary dataset of over 17000 thyroid nodules into groupings for a larger statistical analysis to determine a correlation between nodule shape and indications of malignancy. I performed hands on descriptive data analysis using the JMP software program to run univariate logistic regression, chi squared tests, and the basics on multiple logistic regression. This project is currently in the concluding stages of being put together for a manuscript. I am now in my senior year at Columbia University majoring in Biology with a Computer Science concentration and I hope to attend medical school in the future.

 
 
 

David Argyelan, texas a&M

This summer, I worked under Dr. Irene Ghobrial at Dana Farber Cancer Institute on PANGEA, a project seeking to develop more advanced prediction methods for progression of MGUS to smoldering myeloma and multiple myeloma. I consolidated patient charts and worked with the annotation team on identifying and correcting anomalous data used for submission to the American Society of Hematology. Additionally, I also annotated full patient data sets, verifying addition of more data points for a more accurate predictive model. I am currently finishing a Master of Science in Medical Sciences at Texas A&M University Health Science Center College of Medicine.

 
 
 

Claire Jordan, stanford

I worked under Dr. Chris Baugh on a project investigating emergency department visits of patients with chest pain before and after the implementation of a high-sensitivity troponin assay. I contributed to developing the data entry tool, performed chart abstraction for hundreds of visits, and trained onboarding research assistants. I am currently a senior at Stanford University, where I am majoring in neurobiology and minoring in psychology.

 
 

2020 Research Trainees

 
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ELLIE XIONG, columbia

MSc in Bioengineering, Columbia University

I worked under PI Alexandra Golby and Dr. Nazim in the Surgical Planning Lab. My project involved using digital subtraction angiography image analysis to enhance function guided neurosurgery. I mostly built deep learning algorithms based on Unet architecture, achieving 98% accuracy and further help the intraoperative imaging guiding during surgery. These algorithms were used to support an article submitted to Neurology Today (Winter 2020). I recently completed a Master’s of Science in Bioengineering at Columbia University.

 
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George Tolkachev, nyu

BA in Computer Science and Math, New York University

I am a recent graduate of NYU where I majored in computer science and math. During this internship, I worked under PI Dr. Erik Alexander to analyze data on chromatin accessibility in 23 human cancer types to identify DNA regions where thyroid cancer is most likely to develop. I devised a novel computational approach to prioritize transcription factors according to their level of enrichment in DNA regions with high chromatin accessibility using Python. Since the end of the internship, I have been continuing my Master's in Computer and Information Science at UPenn and am set to graduate this semester. In the fall, I participated in a hackathon hosted by the Wharton School, which focused on how COVID-19 has impacted global economic performance, and my team ended up winning second place! I recently received a full-time job offer from a top financial institution for their Quantitative Analytics program, which is set to begin in July.

 
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Lynn Bi, columbia

BSc in Bioengineering, Columbia University

I graduated from Columbia University in 2020 where I completed a BSc in Bioengineering. As an intern with TechFoundation, I worked under PI Roland C. Merchant to perform a systematic literature review for HIV screening programs in pediatric emergency departments using Pubmed, Scopus, Embase, Cochrane, Web of Science, CINAHL, PsycInfo and Google Scholar electronic databases. I performed qualitative analysis on the publications selected based on inclusion and exclusion criteria. I am currently completing a Postbac through the NIH.

 
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Michael Nercessian, cornell

Major in Neurobiology and Behavior, Cornell University

I worked under PI Alexandra Golby to optimize a neural style transfer algorithm using deep learning to expand the dataset of cortical images from hundreds to thousands of images. These were used to train a deep learning segmentation algorithm using U-Net architecture. I also performed automated segmentation of vessels from the cortical images, which will facilitate registration of preoperative MRI to intraoperative images during neurosurgery, a key component to augmented reality-assisted surgery. I am now in my senior year at Cornell University majoring in Neurobiology and behavior.

 
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Matthew Johnson, colby

BA in Math, Colby College

I worked under PI Marie McDonnell to identify patterns in outcomes among COVID patients with diabetes using EPIC chart review, REDCap database building, and RPDR data querying. I reviewed the charts for 76 patients coding for length of hospital stay, hospital location, intubation, and selected lab measures. I also constructed a REDCap instrument to capture over 200 relevant variables from health records as part of a multicenter consortium on diabetes and COVID. I am currently the head of student research at the Maine Concussion Management Initiative.

 
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Rachel Chacko, dartmouth

Computer Science and Biology Major, Dartmouth College

I am a senior at Dartmouth College majoring in Computer Science and Biology. Over the last year, I have been working on a Computer Science thesis, in which I analyze Medicare administrative claims data to visualize end-of-life care. This summer, I will begin medical school at the Geisel School of Medicine at Dartmouth. As a TechFoundation intern during the summer of 2020, I worked on two projects in the Mohs and Dermatological Surgery department (PI: Dr. Emily Ruiz) that entailed 1) a retrospective analysis of outcomes for squamous cell carcinoma and 2) a cohort study of the effects of COVID-19 on patients seeking treatment for non-melanoma skin cancers. A manuscript for the latter project has been submitted for publication.

 
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Robert Larmore, uva

BSc in Finance, University of Virginia

I worked under PI Kei Ouchi. My project involved studying the effect of two different styles of palliative care delivery in patients with advanced illnesses. I Drafted, edited, and finalized IRB protocol summaries, and performed EPIC chart review for 50 patients coding advanced illnesses, demographic information, baseline survey results, and subsequent outcomes. I also revised and edited a viewpoint paper written by the PI and submitted to JAMA and JAMA-IM (August 2020). I graduated from UVA in 2020 with a Bachelor of Science in finance and information technology. I am now an incoming analyst at Jefferies.

 
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William West, columbia

BSc in Biomedical Engineering, Columbia University

I graduated from Columbia University in 2020 with a BSc in biomedical engineering. During this internship, I worked under PI Michael O’Leary. My project involved screening patients for a clinical research study to develop a patient reported outcome measure for underactive bladder. I attended virtual urology conferences to observe physicians discussing their current patients. I Performed EPIC chart review for 143 patients coding for features including pre-existing conditions, current medications, surgical history. I am now working on my Master of Bioengineering degree at Rice University while playing for the Rice baseball team. As part of my degree, I am working in the Grande-Allen Integrative Matrix Mechanics Lab on the mechanism of radiation-induced cardiovascular disease. I have been accepted to medical school at the University of South Florida Morsani College of Medicine and the University of Central Florida College of Medicine. I continued my working with my PI from Brigham and Women’s Hospital through my fall semester.