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.
IT Service Status
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.
Christina Maimone(she/her)
Associate Director, Research Data Services
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.
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 oversees the data science efforts of our team, helping to drive innovation and excellence in research across Northwestern through our service areas. Aaron also brings extensive expertise in data visualization, with years of experience collaborating with Northwestern researchers to share their data and discoveries through impactful visual storytelling. Read more about Aaron.
Emilio is a data scientist who supports research projects and teaches workshops on data science and programming. His expertise spans web scraping, natural language processing (including large language models), supervised machine learning, and statistical modeling of survey data. Read more about Emilio.
Research Data Management
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.
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.
During her PhD in theoretical soft condensed matter physics, Julia developed a strong background in computational methods and tools. She now supports researchers at Northwestern across various disciplines in effectively leveraging computing resources. Read more about Julia.
Data Science, Statistics, and Visualization Student Consultants
Aniket Dehadrai
Aniket is a 3rd year medical student at the Feinberg School of Medicine, with a passion for applying machine learning methods to clinical research. Specifically, he works in the Department of Radiology to develop predictive imaging-based risk models for cardiac outcomes. For this work, he primarily conducts statistical analysis and model training in Python, but he's excited to build his proficiency in R and SQL moving forward. When not working, Aniket loves to sing in his band, rock climb, and go for runs along the lake!
Jonathan Doriscar
Jonathan Doriscar is a Ph.D. candidate in the Social Psychology program and a master’s student in Statistics and Data Science at Northwestern University. He is most familiar with R, but also uses Python in his research. Jonathan utilizes both experimental and computational approaches (i.e., NLP, Machine Learning) to understand cultural change at varying societal levels (e.g., micro, meso, and macro). He is particularly interested in understanding the antecedents (i.e., barriers & facilitators) and outcomes of change cultures (e.g., Police reform).
Arne Holverscheid
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.
Alice Kang
Alice is a PhD candidate in Sociology. Her research examines how legal statuses and the rights they confer are shaped by private interests and market logics. She is especially passionate about leveraging data visualization to translate complex ideas into clear and accessible insights. Alice primarily works in R and is also familiar with Stata, SQL, Python, and Tableau. She enjoys exploring new software tools and troubleshooting code.
Yangyang Li
Yangyang Li is a fifth-year Ph.D. candidate specializing in deep learning, high-performance algorithms, and research software development for complex biological applications. His expertise lies in deep learning approaches for data-driven scientific discovery, with a particular passion for bridging computational innovation and biological research to address challenging problems.
Shuhan Liu
Shuhan is a third-year Ph.D. student in Statistics and Data Science. She is proficient in R and Python, and has developed extensive statistical skills such as experimental design, causal inference, meta-analysis, and survival analysis. She hopes to contribute to scientific discovery as a statistician.
Nick Markov
Nick Markov is a PhD candidate in Driskill Graduate Program (DGP) researching immune response in severe pneumonia and other lung diseases from the computational biology perspective. Prior to that he obtained his MS in bioinformatics and spent a number of years as a full stack web developer in industry. He is proficient with Python, R, Unix and Quest, and has a particular passion for interactive visualizations to allow researchers to engage with their data. In the meantime he is learning more about deep learning, causal inference and Julia.
Anthony Pulvino
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.
Samvardhan Vishnoi
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.
Daniel Encinas Zevallos
Daniel 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
