Meet Our Team
The Research Computing and Data Services team works across the University to help support the computational, data, and technology needs of our research community through consultation, training, collaborative projects, and a range of resources and services.
We work closely with our colleagues in Cyberinfrastructure, who lead and manage the University Data Center, computing, storage, networking, and data transfer systems and capabilities.
Are you interested in joining our team? Full-time staff open positions include Lead Statistician, Statistician, and Data Management Specialist. Visit Careers in Northwestern IT to learn more, and apply.
Jackie leads the Research Computing and Data Services team in delivering a portfolio of computational and data services supporting and enabling Northwestern's diverse breadth of research. Read more about Jackie.
Christina leads the Data Services teams that support researchers in working with their data throughout the research lifecycle, from collecting and securely storing it, to analyzing and visualizing it. Read more about Christina.
IT Business Operations
Letty leads the business operations of Research Computing and Data Services (RCDS). She focuses on the financials, services management, communications, office administration and implementation of efficient procedures for all RCDS teams. Read more about Letty. Liz has an IT systems development and project management background. She focuses on managing cross-team projects for research computing and research data management services between RCDS and our CI partners. Read more about Liz.
Data Science, Statistics, and Visualization
Colby leads the data science, statistics, and visualization team in providing consultations, training, and collaborative project support to researchers across Northwestern. Read more about Colby.
efrén collaborates on data science projects with researchers from all Northwestern departments and programs. They have expertise in machine learning as well as special interests in agent based modeling, complex systems, interdisciplinary collaboration, and art projects. Read more about efrén.
Ritika works on data science projects, teaches workshops, and oversees the consultation service. She has a breadth of skills, from working with genomic data to building reproducible data pipelines. Read more about Ritika.
Aaron collaborates with researchers to communicate their data and findings through both static and interactive visualizations, and he enjoys teaching workshops on the latest visualization packages and tools. Read more about Aaron.Emilio supports researchers and teaches workshops. He has particular experience with statistical modeling of survey data, predictive modeling, and data visualization and is interested in text analysis with language models. Read more about Emilio.John is a data scientist in the Research Computing and Data Services team. He works with researchers and students across the Northwestern University by providing data science and visualization support. Read more about John.
Research Data ManagementKristin leads the data management team in building services and providing consultation in support of researchers reliably and securely storing, reusing, preserving, and sharing data throughout the research lifecycle. In her role, she brings expertise in information systems, research support, proposal and award review, cybersecurity compliance, as well as technology and organizational change management. Read more about Kristin. Kevin supports research data management services and infrastructure by improving and automating processes, creating documentation and training materials, and supporting the creation of new services. Read more about Kevin.
Tobin leads strategy for services provided by the data management team, supports researchers in implementing best practices throughout the research data lifecycle. Read more about Tobin.
Brian provides consultation to researchers regarding their data management needs throughout the research data life cycle. This includes providing support for data management tools and services that leverage both on-prem and cloud computing and storage environments. Read more about Brian.
Research Computing Services
Alper leads the team facilitating researchers' access to and effective use of computational resources both at Northwestern and through external services. He is a recognized leader in developing student consultants and shares this experience through national research computing and data forums such as CaRCC and PEARC. Read more about Alper.Andrew combines his previous experiences of teaching and information technology to support Northwestern researchers with their computational needs. Read more about Andrew.
Haley supports the computational needs of genomics and other “omics” related research at Northwestern. Her bioinformatic experience comes from her background in plant genomics and evolutionary biology. Read more about Haley.
Scott uses his experience from astrophysics to support researchers across all domains in using Quest and other computational resources, and manages the student computational consultant team. Read more about Scott.
Matthew uses his previous experience as a scientific application developer and systems engineer to assist Northwestern researchers with their computational needs. Read more about Matthew. Sai has a wealth of experience in facilitating computational research and a strong background in porting various scientific applications onto high-performance computing clusters. Read more about Sai.
Matt leverages his research and high-performance computing (HPC) experience to support Northwestern students, faculty, and staff from a variety of backgrounds access computational researchers on Quest. Read more about Matt.Sophie uses her previous education in Computer Science and Informatics, as well as her research experience gained during her master's degree to facilitate computational research at Northwestern. Read more about Sophie. Wenceslao supports Northwestern researchers by ensuring timely resolution or escalation of service requests for Quest high performance computing cluster and related resources. Read more about Wences.
Data Science Student Consultants
Tuba is a PhD candidate in mechanical engineering, and a PhD fellowship recipient from the U.S. Department of State under the Fulbright foreign student program. Her research focuses on uncertainty quantification in machine learning for metamaterial design applications, where she uses machine learning tools and stochastic modeling approaches. Tuba is most familiar with Python but also has experience with MATLAB. She loves learning about the research problems other researchers work on and how they benefit from machine learning in solving these.
Arne is a PhD student in the Department of Political Science studying comparative politics and political methodology. He is also in the master's program in the Department of Statistics and Data Science. His main academic interests lie in political behavior, quantitative methods, and computational social science. He is studying the causes and mechanisms of far-right political success, focusing on processes of normalization of far-right ideology in mainstream politics.
Isabel is a third-year undergraduate majoring in data science and minoring in Spanish. She first learned Python in her data information management class and never looked back. She enjoys working on predictive modeling in Python and loves to meet new people and learn new things through their experiences.
Jenny completed her PhD from Northwestern's Department of Mechanical Engineering in 2021. Jenny is interested in dynamics and time series analysis. As an undergraduate student in the Department of Electrical & Systems Engineering she analyzed electroencephalography (EEG) data. Her PhD research focused on computational modeling of protein motion using molecular dynamics simulations. The project also exposed her to network science and provided hands-on experience analyzing large datasets on Northwestern’s high performance computing cluster Quest. Jenny is currently finishing her last year of medical school from the Feinberg School of Medicine.
Ren LopezRen is a PhD candidate in materials science and engineering. Her research is using cheminformatics and automated network generation to discover new biobased materials, their properties, and how to make them. She is most familiar with Python and C/C++ but has familiarity with Matlab, Bash, and Java. She loves learning new coding languages and how other disciplines apply them.
Julie Anh NguyenJulie Anh is a PhD candidate in the applied math department. Her research focuses on the identification of dynamic systems from data using a combination of techniques from data assimilation and machine learning with applications in synthetic biology. Julie works mostly with Python and command line but is also familiar with Quest, Matlab, R, and other statistical tools used in the social sciences, such as Stata.
Yaelle is a third-year undergraduate majoring in Data Science. She has been a TA in the data science sequence and has gained valuable experience through completing various data-related internship projects. Yaelle has employed machine learning models to predict distinctions between similar tech job titles using survey data. One of her notable accomplishments is the creation of a dynamic R Shiny application that effectively visualizes demographic variations based on job titles and company selections made by the user. She is proficient in R and SQL, and is interested in enhancing her coding skills by also learning Python and tackling complex data science projects.
Anthony is a PhD student in the Interdisciplinary Biological Sciences program. His research in the Amato Laboratory focuses on interactions between human and non-human primate host genomes and their microbiomes. He leverages molecular biology, evolutionary, and anthropological perspectives to explore the genetic underpinnings of our shared primate biology to better understand chronic diseases like diabetes and obesity. Anthony enjoys learning new software tools and has experience with using Python, R, Unix and high-performance computing resources like Quest for data-analysis projects.
Jose Sotelo is a PhD student in the cognitive psychology program and a master’s student in the statistics department. His research revolves around spatial cognition. In particular, how people build cognitive maps in large-scale space as well as how individual and cultural differences impact spatial thinking. Jose is most familiar with R but has some with other languages and statistical tools.
Carrie Stallings Carrie Stallings is a PhD student in sociology and a Native and Indigenous Studies Cluster fellow. In her work, she primarily uses R and Stata for statistical analysis and data visualization. Her current research focuses on income and wealth inequality, particularly on the roles that government and educational institutions play in the life outcomes of Black and Indigenous peoples. She is also a member of the CoronaData U.S. team at Northwestern.
Dan TurnerDan joined Northwestern in 2017 as a linguistics PhD student. Previously, he taught courses in linguistics, writing, and journalism and conducted research in linguistics at the University of Minnesota Duluth. His current research interests include prosody, mental representations of sounds, and adaptation. He is familiar with R and Python, as well as various languages and statistical tools common in the social sciences.
Vishnoi is a Ph.D candidate in Physics. His interests lie at the intersection of various disciplines including social science, physics and machine learning. His current work models U.S. arrest rates from FBI data, utilizing cross-sectional scaling laws in a Bayesian framework coded in Python. Additionally, he works with the Demographic division of Max Planck Institute in Germany, studying evolution of the global scientific workforce. When not on his laptop, Vishnoi likes to play guitar. You can always find him reading physics and calling it leisure.
Pat ZacherPat is a PhD candidate in the Department of Psychology's brain, behavior, and cognition program. His research focuses on spatial attention. In particular, he is interested in how people shift attention around their environments and how this ability applies to complex interfaces. Pat is most familiar with R but has experience in Python and Matlab.
Daniel Encinas ZevallosDaniel is a PhD candidate in political science. His work focuses on political regimes, subnational politics, and civil wars in Latin America. His methodological interest lies in advancing multi-methods research designs and the application of qualitative methods to experimental and statistical analysis. He enjoys helping people with their R projects, providing online resources, and discussing alternative approaches to coding issues.
Computational Support Student Consultants
Saya Rene Dennis
Saya is a PhD candidate in the Department of Preventive Medicine at Feinberg School of Medicine. Her research focuses on the applications of machine learning and deep learning algorithms in patient genomic data, as well as in electronic health records. She most frequently works with Python, Unix commands, R, and SQL and is interested in various tools that facilitate the handling of large-scale data.
Xamantha is a sophomore from Peru majoring in economics and computer science with a minor in data science. She wrote her first line of code during her first quarter of study at Northwestern and has since become passionate about programming and its applications for educational purposes. She enjoys working on projects focused on data visualization and is familiar with R and Python.
Diana C. PerezDiana is a PhD candidate in the Brain, Behavior, and Cognition program in the Department of Psychology. Her research focuses on brain networks in aging and how individual differences in brain networks relate to individual differences in age-related cognitive decline. This work has led to extensive experience using neuroimaging software, such as Workbench, fmriprep, FSL, AFNI, and FreeSurfer, as well as using MATLAB on Quest to work with large datasets. Diana also enjoys learning new skills (currently working on Python and SQL) and debugging code.
Xiaoyu XieXiaoyu is a Ph.D. candidate in the Department of Mechanical Engineering. His research aims to develop scientific machine learning algorithms to accelerate numerical simulations and discover physical laws in the fields of manufacturing, fluid mechanics, and solid mechanics. He is passionate about solving challenging scientific and engineering problems using flexible and robust artificial intelligence methods. Xiaoyu works primarily with Python and the Unix command line, and he is also proficient in using data analysis and visualization tools.
Lucas is an undergraduate student studying computer science, with an interest in cybersecurity. He has worked in projects related with web and game development. Since joining the Research Computing Services team, he enjoys learning about high-performance computing and its applications.