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.
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.
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.
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.
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.
Wenceslao Hernandez Velasquez (he/him)
User Support Specialist Associate
wenceslao.hernandezvelasquez@northwestern.edu
Data Science, Statistics, and Visualization Student Consultants
Trudy Adjei
Trudy is a Biomedical Engineering PhD Candidate who focuses on how movement-specific brain areas communicate to facilitate movement. Her research aims to determine whether the type of communication depends on the movement to be performed. By understanding these processes in a neurologically intact brain, she hopes to provide foundational knowledge for interventions for neurologically injured brains. Her work involves extensive signal processing and analysis in MATLAB, as well as statistical analysis in R.
Saki Amagai
Saki is a PhD Candidate in Health and Biomedical Informatics at the Feinberg School of Medicine, specializing in big data analysis using Electronic Health Records. She is proficient in Python, R, and SQL, and has worked with machine learning and basic statistical modeling. She is actively expanding her expertise in large language models and natural language processing.
Tuba Dolar
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.
Jonathan Doriscar
Jonathan Doriscar is a third-year 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.
Isabel Knight
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.
Yangyang Li
Yangyang Li is a third-year Ph.D. candidate with a focus on deep learning, highly efficient algorithms, and research software development to tackle complex biological problems. My area of expertise is machine learning-based data-driven domains. Armed with a passion for applying this knowledge to scientific issues.
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.
Julie Anh Nguyen
Julie 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 Pierre
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.
Maalvika Pillai
Maalavika is a PhD student in the Interdisciplinary Biological Sciences (IBiS) program. She is currently working on understanding the dynamics of gene network structures in cells. More specifically, she is working on integrating multiple modes of sequencing data (RNA-seq, ChIP-seq, ATAC-seq) to develop robust models for gene expression in cells. She is familiar with Python, R, shell scripting, Quest and several commonly used bioinformatics softwares.
Edwin Pokisa
Edwin is a senior at Northwestern University majoring in Data Science, with a certificate in Design and Integrated Marketing Communications. He has gained extensive experience in data processing, analysis, and visualization through various academic projects and internships. One of his key achievements includes developing an interactive dashboard that centralizes organizational data, allowing real-time insights for decision-making. Edwin is highly proficient in Python, R, and SQL, and has applied machine learning models to predict outcomes in a range of contexts. His passion lies in using data to solve complex problems, and he looks forward to contributing his skills as a Data Science student consultant for Research Computing and Data Services.
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.
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.
Elizabeth Teng
Elizabeth is a PhD student in Astronomy developing methods for machine learning emulation in binary star evolution research. Her work primarily involves Python development in collaborative open-source software. Elizabeth also works with the command line and the Quest computing cluster.
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.
Eileen Zheng Wu
Eileen Zheng Wu is a PhD candidate in social psychology and also earned a Master of Science in Applied Statistics from Northwestern. She has 8+ years of experience providing insights about human processes through exploratory and confirmatory statistical modeling. She is most familiar with R and SPSS, and becoming more fluent in Python. Currently, she is studying up on machine learning methods. Her research focuses on modeling motivations and behaviors in social relationships such as romantic ones.
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
Nana Haruna
Nana is a Ph.D. candidate at Feinberg School of Medicine in the Division of Allergy and Immunology. She is currently investigating granulocyte functions during inflammation and homeostasis. Her work utilizes a systems biology approach, combining techniques from genomics, bioinformatics, proteomics, and metabolomics to answer research questions. She is proficient in R, Python, and SQL as well as working with high throughput ‘-omics’ datasets. She also enjoys troubleshooting and learning new computational tools.
Iris Liu
Iris is a PhD candidate in the Division of Pulmonary and Critical Care at Feinberg School of Medicine. Her research in the Singer lab focuses on developing novel methylation sequencing methods for ultra-low input clinical samples and understanding epigenetic basis of lung regulatory T cell phenotype in response to inflammation and injury. Iris works mostly with R and command line but is also familiar with Python, Matlab, and SPSS.