The purpose of this program is to help faculty more efficiently complete contained research tasks such as creating figures, scraping websites, merging datasets, etc. If you are looking for long-term, research-support help we recommend you work with your divisional admin to identify and hire your own part-time research assistant.
Costs
- The Dean’s Office is subsidizing the cost of these research assistants.
- There is a charge of $10 per hour for the Data Analysts' time.
Scheduling RAs
To request an RA help, fill out our RA Request form including project details, expected timeline and other relevant information. Once submitted, out lab staff will review your request assign the appropriate Data Analyst to you.
We have a team of research assistants who can help with most general data-analytic tasks:
Ruoxuan Li
Appointment Date: March 19, 2024-December 30, 2024
Hours Per Week: 10
Ruoxuan Li is currently a Master of Science in Data Science student at Columbia University, with a particular interest in the fields of Exploratory Data Analysis (EDA), Natural Language Processing (NLP), and generative AI. Driven by a passion for uncovering insights through data, she aims to bridge the gap between complex data analyses and real-world applications. She also volunteers as a research assistant at the Living Lab, led by Professor Alfredo Spagna. Her hobbies include hiking, birding, and writing.
She is especially good Exploratory Data Analysis (EDA), Natural Language Processing (NLP), and generative AI but can help with most general data-analytic tasks.
Please find Ruoxuan’s resume.
Contact Ruoxuan Li.
Aneri Bijal Modi
Appointment Date: March 19, 2024-December 30, 2024
Hours Per Week: 10
Aneri Modi is currently enrolled in the M.S. program in Data Science at the Fu Foundation School of Engineering and Applied Science, Columbia University. Before enrolling in the program, she worked as a Natural Language Processing intern at Daikin Industries Limited (a global refrigeration company). She earned her undergraduate degree in Mechanical Engineering (with a minor in Data Science and Artificial Intelligence) from Indian Institute of Technology Bombay, India. Her technical strengths include the following programming languages: Python, R, and C++. She has experience with the following data science techniques: Machine Learning methods, Exploratory Data Analysis and Visualization, and Deep Learning. She also has extensive experience working with the following packages: Pandas, NumPy, scikit-learn, Matplotlib, Seaborn, ggplot2, and Keras. She has knowledge of statistical approaches and methods such as ANOVA tests, p tests, and regression analysis, from her core courses. In the past, she has worked with weekly sales data for forecasting, Climate reanalysis data from Google Earth Engine, datasets from Kaggle, etc. She also has experience with big data analysis using parallel computing tools such as Dask.
She is especially good at data analytics, visualization, and machine learning, however, can help with most data-analytic tasks. Hoping to make a meaningful impact to solve global issues like climate change with the tools and experience she possesses.
Please find Aneri’s resume.
Contact Aneri Bijal Modi.
Jun Shin
Appointment Date: March 19, 2024-December 30, 2024
Hours Per Week: 10
Jun Shin is an undergraduate in Columbia College, Columbia University majoring in computer science and mathematics. He has experience working on data science and software development tasks through internships at Kensho (S&P Global), Dunamu, Waterfall, and Gantu AI. He is also doing research on large language models at the Columbia Spoken Language Processing Lab. His technical strengths include the following programming languages: Python, R, and C++. He has experience with the following data science techniques: EDA, feature engineering, machine learning, deep learning, and natural language processing. He has extensive experience working with the following packages: Pandas, NumPy, scikit-learn, TensorFlow, PyTorch, Plotly, Matplotlib. He has experience with the following statistical approaches: regression, boosting, time series analysis. In the past, he has worked with the following databases: equities data, private market investment data, SEC filings data, vehicle dashboard camera videos for computer vision.
He is especially good at data analysis, visualization, and applying machine learning techniques using Python but can help with most general data-analytic tasks.
Please find Jun’s resume here.
Contact Jun Shin.
Zhixing Ni
Appointment Date: March 19, 2024-December 30, 2024
Hours Per Week: 10
Zhixing Ni is currently enrolled in the M.S. program in Business Analytics at the SEAS and Business School, Columbia University. Before enrolling in the program, he worked as an undergraduate research assistant at the Daniels School of Business, Purdue University. He earned his undergraduate degree in Economics Honors (Data Analytics Concentration) from Purdue. His technical strengths include the following programming languages: Python, STATA, and R. He has experience with the following data science techniques: Exploratory Data Analysis, Statistical Analysis, and Machine Learning. He has extensive experience working with the following packages: Numpy, Scikit-learn, Pandas, etc. He has some experience with the following statistical approach: time series analysis. In the past, he has worked with the following databases: National UNOS Standard Transplant Analysis Data, Multi-Radar/Multi-Sensor System Weather Data, and Chinese Macroeconomic Education Data.
He is especially good at regression analysis, A/B testing, visualization, and machine learning, but can help with experiment design and most general data analytics tasks. He hopes to pursue a doctoral degree in Economics after graduating.
Please find Zhixing’s resume here.
Contact Zhixing Ni.