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), computer vision, and predictive and statistical modeling. 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 Northwestern’s research community through consultations and workshops, as well as strategic service improvements and expansions. Her background in plant genomics and evolutionary biology honed her computational and problem-solving skills. Read more about Haley.
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
Ubeydullah Ademi
Ubeydullah is a PhD candidate in Political Science with a background in applied statistics. His research focuses on developing new methods for causal inference and impact modeling, particularly in settings involving social networks. His broader interests lie at the intersection of data science and social science, with an emphasis on applying quantitative methods to evaluate public policies and support evidence-based decision-making across the public and private sectors.
Artur Baranov
Artur is a PhD candidate in the Department of Political Science at Northwestern University. His research focuses on non-democratic politics and legislative institutions, examining how legislatures contribute to regime stability and how their roles change as political regimes evolve. He uses quantitative and computational methods, particularly text-as-data approaches, to study political behavior and institutions in authoritarian settings.
José Miguel Córdova
José is a PhD student in the Technology and Social Behavior program. His work lies at the intersection of collective intelligence, complex systems, and computational social science, drawing on methods from network science, experimental design, and human-computer interaction. He is particularly interested in understanding how AI can influence, support, or hinder collective intelligence. He is also interested in how early interaction dynamics can be leveraged to predict outcomes in complex social systems.
Aniket Dehadrai
Aniket is a 4th 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, and he's excited to continue learning more about deep learning and image/language processing through his second year with DSSV! When not working, Aniket loves to sing in his band, rock climb, and go for runs along the lake.
Aryan Dwivedi
Aryan is a Master's student in Artificial Intelligence at Northwestern's McCormick School of Engineering. His research focuses on building adaptive, highly efficient AI systems by bridging curriculum learning, state-space models, and vision-language architectures like CLIP. He works at the intersection of multimodal representation learning and resource-aware inference, with the goal of scaling machine learning models to be both computationally efficient and inherently reliable in real-world deployments.
Annie Gomez
Annie is a fifth-year PhD candidate in Material Science and Engineering. Annie’s research focuses on the design and self-assembly of protein complexes. She combines in vitro assays, molecular dynamics simulation, and interpretable machine learning to explain why some engineered shell proteins assemble and others don’t. She uses SHAP and permutation attribution to find which sequence features drive a deep learning model’s predictions, then tests them against experiments and simulation to see whether the model has learned real biophysics. She is especially passionate about turning complex results into clear insights for collaborators across disciplines. Annie primarily works in Python and is also familiar with R, SQL, C/C++, MATLAB, GROMACS, and PyRosetta. She enjoys working between the bench and the computer, and troubleshooting both assays and code.
Tyrone Li
Tyrone is a Master's student in Northwestern's Machine Learning and Data Science program, graduating December 2026. He is interested in AI and how it can be applied to real-world data problems. His background combines data analytics and machine learning with UI/UX design from his informatics degree at the University of Washington.
Yangyang Li
Yangyang is a PhD candidate in the Driskill Graduate Program at Northwestern University Feinberg School of Medicine. His research develops deep learning models and high-performance algorithms for genomic data, including genomic language models and graph-based methods for long-read sequencing analysis. He builds open-source research software. As a data science and visualization consultant, he helps researchers with deep learning, LLMs, large-scale data analysis, and building interactive visualization tools.
Shuhan Liu
Shuhan is a PhD 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.
Assylbek Oteubayev
Assylbek is a Master's student in Artificial Intelligence at Northwestern's McCormick School of Engineering, graduating in December 2026. Originally from Kazakhstan, he spent about a year and a half as a data scientist at SLB before coming to Northwestern, working on applied machine learning problems. His research focuses on diffusion models for bio-image processing, and he is also interested in transformers, Bayesian inference, and NLP. Assylbek is most familiar with Python and PyTorch and has experience with MLOps and running distributed training on HPC clusters using SLURM. He enjoys helping researchers get their models and pipelines running at scale.
Haikal Rozaidi
Haikal is a Master’s student in Computer Science at Northwestern University. He has an extensive background in applying AI and Machine Learning techniques to real world applications. He also has experience in Full Stack Software Development in a wide variety of fields.
Cat Dang Ton
Cat is a PhD student in Sociology, studying consumption, culture, and community life. She enjoys traversing between qualitative inquiry and computational text analysis. Her current research examines the practices of families, professionals, and consumers as they sort through objects left behind by a deceased person. In her previous projects, she's enjoyed analyzing text, demographic and geospatial data she scraped from the web, as well as setting up LLM workflows on Quest.Computational Support Student Consultants
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.
Tanu Priya
Tanu is a PhD candidate at the Feinberg School of Medicine. Her research focuses on understanding sequence-function relationships in enzymes using high-throughput approaches for protein characterization. She integrates experimental data with machine learning models to quantitatively capture enzyme stability and activity to design highly stable and efficient enzymes. Tanu works extensively with Python and command-line tools, and has experience analyzing large-scale sequencing datasets and protein design pipelines.