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Welcome to the CCSS HelpDesk

Find answers to common issues and access the resources below. Can't find what you are looking for? Email or call 607-255-1986.

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HelpDesk Consultants

The CCSS HelpDesk consultants assist students and faculty by offering support and guidance with statistical applications. Our student consultants represent a diverse array of social science backgrounds who are hired based on their demonstrated quantitative and analytical performance.

The list below may help you find which consultants best match your needs. Please note, however, that the software listed for each is just their expertise. All our consultants have extensive experience in statistical computing and can help get you started in any software supported by CCSS.

Lead Statistical Consultant

Headshot of Jacob Grippin

Jacob Grippin


Software: Stata, SAS, R, RStudio, SPSS, Python, Minitab, Matlab, JMP, MPlus, MikTex, Qualitative(Atlas.ti, NVivo)

Topics: Data Cleaning, Data Manipulation, Output Analysis, Summarizing Data, Qualitative Software, Longitudinal Data Analysis, Web Scraping, Geospatial(R)

Consultant Bios

  • Headshot of Florio Arguillas

    Florio Arguillas
    Research Associate
    741 Rhodes Hall

    Contact me for assistance with:

    • verifying and certifying the reproducibility of your study before submission for publication;
    • packaging your replication files so that the package is portable, independently understandable, easy to re-use, and ready for deposit in any journal-designated repository;
    • best practices in managing and reviewing data and code and in making transparent and reproducible research;
    • training customized for you, your project team, or your class on tools for qualitative and quantitative data analysis, as well as on qualitative and quantitative data management, processing, and analysis;
    • writing, understanding, and debugging codes/scripts;
    • getting your data ready for analysis;
    • crafting or reviewing data management plans for your proposals;
    • assessing and mitigating disclosure risks and anonymizing data before use or sharing.

    Bio: I am passionate about helping Cornell researchers make their research well-managed, transparent, reproducible, and easy to find, access, and re-use. I enjoy conducting customized training for classes, individuals, and project teams on qualitative and quantitative data management and processing and on tools for qualitative and quantitative data analysis. I find joy in imparting my skills and knowledge during individual and project team consultations and learning new things from these interactions. I apply the new knowledge I have gained to improve our services further.

    I hold a Ph.D. and M.S. in development sociology (Cornell University), an M.A. in demography (University of the Philippines-Diliman), and an A.B. in economics (Ateneo de Davao University, Philippines).

  • Headshot of Jonathan Bohan

    Jonathan Bohan
    Data Archive Specialist and Assistant Data Custodian
    391 Pine Tree Road

    Contact me for: Data reference questions, questions about our Data and Reproduction Archive, depositing data in a trusted repository, persistent identifiers, and converting data formats.

    Bio: I am passionate about helping researchers find and use data, making older and historical data usable with modern statistical programs, and making our Data and Reproduction Archive more FAIR (Findable, Accessible, Interoperable, and Reusable). I'm excited to be part of the Cornell Center for Social Sciences.

    I was born and raised in northern New Jersey and lived in the Boston area for 16 years before moving to Ithaca with my family in 2015. I have been working for Cornell since late 2016. I hold Master's degrees in History and Library and Information Science and a Bachelor's in Business Administration.



    Headshot of Jonathan Chang

    Jonathan Chang 
    Ph.D. Student, Senior Data Science Fellow
    Computer Science

    Research Interests: Social media, Content moderation, Computational Social Science, Natural Language Processing

    Bio: Jonathan is a fifth-year Ph.D. candidate in Computer Science at Cornell, advised by Cristian Danescu-Niculescu-Mizil (Information Science). He earned his undergraduate degree in Computer Science at Harvey Mudd College. Jonathan’s current focus is on studying the problem of content moderation on online platforms and social media. He applies NLP and computational social science techniques both to characterize and model the patterns of misbehavior online and to develop computational tools that can help improve the effectiveness of content moderation.

    Tools/Software: Python (+ Numpy/Scipy, Pandas, Scikit-learn, Pytorch), Git, Linux.

  • Headshot of Xiaomeng

    Xiaomeng Chen
    Ph.D. Candidate, Senior Data Science Fellow
    Charles H. Dyson School of Applied Economics and Management

    Research Interests: digital platforms, knowledge spillover, and open innovation

    Bio: Xiaomeng Chen is a fifth-year Ph.D. candidate at Cornell University. She is from Lanzhou, China, and she received her undergraduate degree at Shanghai University of Finance and Economics. She is currently working on platform choices in the context of open innovation platforms, exploring the effect of platform-level strategy on platform outcome, and examining the change in knowledge creation. She is experienced with economic and statistical modeling, causal inference, data analysis, text mining, web scraping, and relational database.

    Tools/Software: Python, STATA, SQL, R, GitHub, Matlab, google big query.


  • Headshot of Elena Goloborodko

    Elena Goloborodko
    Secure Data Services Manager, Data Custodian
    391 Pine Tree Road

    Contact me for: Research with restricted data, data security requirements, data security plans, and the Cornell Restricted Access Data Center (CRADC) operations.

    Bio: I am passionate about everything related to data: data collection business rules, data accuracy and integrity, data analysis, data availability and accessibility, data security, database architecture, and information systems. I believe in data-driven change and consider myself lucky to support research for social sciences and economics.

    I was born in USSR – a country that no longer exists. I completed my Master’s degree in Computer Science and Applied Mathematics at Kiev State University, Ukraine.  After immigrating to the United States in 1998, my family settled in Ithaca. A few months after our arrival, I started a job at Cornell's College of Human Ecology.

    I have been challenging myself to learn new skills and try new jobs in data management and software design project management. I am excited to bring my 30+ years of experience to the Cornell Center for Social Sciences.


  • Headshot of Hwang

    Angel Hwang
    Ph.D. Student, Senior Data Science Fellow
    Department of Communication

    Research Interests: human-agent teamwork, human-machine communication, human-AI interaction

    Bio: Angel Hwang is a Ph.D. student in the Department of Communication at Cornell University, working with Dr. Andrea Stevenson Won at the Virtual Embodiment Lab. Her research explores the potential of human-agent collaboration to facilitate team synergy and innovation, including how users work directly with autonomous agents and how agents can mediate human-human teams. She pays particular attention to how agents can support marginalized members and address common challenges in group settings. More of her work can be found at

    Tools/Software: R, Python, Jupyter Notebook, Qualtrics, Amazon Mechanical Turk (MTurk), SPSS, OS

  • Headshot of Sabrina Porcelli

    Sabrina Porcelli
    Ph.D. Candidate, CCSS Data Science Fellow

    Research Interests: Emotion regulation, impulsivity, risky behavior, and psychopathology

    Bio: Sabrina Porcelli is a PhD Candidate in Developmental Psychology at Cornell University. Prior to entering the PhD program, she completed her Bachelor of Arts in Psychology with a minor in Statistics at The George Washington University and earned her Master of Arts in Human Development and Family Studies from Cornell University. Her research focuses on people’s tendency to act impulsively in response to strong emotions. Sabrina has experience with both quantitative and qualitative methods and has worked with both cross-sectional and longitudinal data.

    Tools/Software: R, SAS, Mplus, Qualtrics, Amazon Mechanical Turk (MTurk), SPSS, OSF


  • Headshot of Aspen Russell

    Aspen Russell
    Ph.D. Student, CCSS Data Science Fellow
    Information Science, Cornell Bowers College of Computing and Information Science

    Research Interests: online communities, norms, social media conflict, computational social science

    Bio: Aspen Russell is an Information Science PhD student at Cornell University. There she studies the emergence and maintenance of norms in online spaces. Currently, she is studying how online groups create and maintain prosocial spaces while dealing with conflict, with the intention to use results to inform platform moderation and public policy. She typically uses computational and qualitative methods. Aspen is also lead researcher on a multi-platform social media study investigating user strategies to deter toxic behavior. At Cornell, Aspen is a member of the Social Media Lab (SML) and Data Science Fellow for the Cornell Center for Social Sciences (CCSS), where she develops workshops on computational social science. Aspen is supported by the National Science Foundation's Graduate Research Fellowship and is a Sloan Foundation Fellow.

    Tools/Software: R, Python, JavaScript (D3.js), GitHub, Qualtrics, NVivo, Dedoose, OpenRefine


  • Headshot of Aishat Sadiq

    Aishat Sadiq
    Psychology Ph.D. student, CCSS Data Science Fellow
    Human Ecology

    Research Interests: Early life social context and health

    Bio: Aishat Sadiq is from Houston, Texas, completing her Ph.D. in Psychology at Cornell. She graduated from Earlham College ('19) with a major in Neuroscience and a minor in African/African American Studies. She is passionate about early life environments and how they impact both physical and mental health. Aishat sees herself as an activist first, scholar second. Due to this, she hopes to tailor her research toward marginalized and hidden communities.

    Tools/Software: R, Python, Github, SPSS, Qualtrics


  • Headshot of Sam Sautu

    Sam Sautu
    Human Development Ph.D. Student
    Research Assistant in the Life History Lab
    Data Consultant at CCSS
    Editor Assistant for Cientifico Latino

    Department: College of Human Ecology, Psychology Department, Neuroscience Institute.

    Research Interests: I look at the role of physiological state as a mediator of the effect of chronic stress on health outcomes, behavior and performance.

    Bio: Samantha is an argentinian-born, panamanian-raised medical doctor who sees social relationships as critical molders of the individual’s neurophysiology and the collective wellbeing. During her time outside of the lab you'll find her binging on music and cat cuddles.

    Tools/Software: R, SPSS, Python, Qualtrics



    Headshot of Christian Sprague

    Christian Sprague
    Ph.D. Candidate, Senior Data Science Fellow

    College of Engineering

    Research Interests: Educational Opportunity, Market Design, Market and Policy Analysis

    Bio: Christian is a 4th-year Systems Ph.D. candidate at Cornell University. He uses frameworks developed in Systems Engineering to analyze market inefficiencies that affect accessibility in K-12 education. His work is interdisciplinary and policy-relevant, with recent work particularly examining the influence of school choice policy on segregated access to educational opportunities and the role of public-school transportation infrastructure. His approaches wed together a wide range of computational and analytical skills to address pressing issues of structural inequalities that come from market design failures and policy oversights. Christian’s work shows a clear commitment to improving markets and infrastructure for the public good.

    Tools/Software: R, Python, QGIS, GitHub, Jupyter Notebook, RedHat, API Integration

  • Headshot of Remy Stewart

    Remy Stewart 
    Ph.D. Candidate, CCSS Data Science Fellow

    Research Interests: Natural language processing in social science research, public policy, inequality in urban contexts, ethics within data science

    Bio: Remy is a PhD Candidate in the Sociology Department originally from the San Francisco Bay Area. Her research focuses on two primary topics. The first is the application of natural language processing methods to understand housing policy dynamics related to gentrification, homelessness, rent control, and beyond within American metropolitan regions. Second is engaging with ethical dilemmas inherent within emerging data science backed research such as user privacy, participant consent, and algorithmic harm. She is a National Science Foundation Graduate Research Fellow and a Cornell Office of Inclusion and Student Engagement Dean’s Scholar. 

    Tools/Software: R, Python, Github



    Headshot of Nicole Szembrot

    Nichole Szembrot
    RDC Administrator
    391 Pine Tree Road

    Interests: FSRDC Specialist 

    Bio: Nichole is available to assist the Cornell community with proposal development and other facets of FSRDC data access. Nichole Szembrot has a Ph.D. in Economics from Cornell University. Dr. Szembrot joined the Census Bureau in January 2018 and was assigned as the Administrator for the Cornell RDC. Before the Census Bureau, Dr. Szembrot was an Assistant Professor in the Department of Economics at Trinity College.

  • Headshot of Kimberly Williamson

    Kimberly Williamson
    Ph.D. Student, Senior Data Science Fellow
    Information Science

    Research Interests: Higher Education, DEI, Computational Social Science, Data Viz

    Bio: Kimberly is a third-year doctoral student in Information Science at Cornell University, advised by Rene Kizilcec in the Future of Learning Lab. Kimberly earned both a Master of Education in higher education and a Bachelor of Science in Industrial Engineering from Iowa State University. Before pursuing their doctorate degree, Kimberly worked for ten years in higher education data administration at multiple universities in the US. Kimberly’s research area uses learning analytics and educational data mining to explore the best ways to communicate educational data to higher education decision-makers. 

    Tools/Software: R, Python, Qualtrics, RShiny, Tableau, SQL, Git, Bash

  • Caiwei Zhang
    Masters Student of Public Administration

    Topics Data Cleaning, Data Manipulation, Summarizing Data, Data Visualization (R), Regression Analysis (R), Supervised Learning (R).

    Tools/Software: Stata, R, RStudio

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