You can follow our lab website for current mentoring activities and research opportunities for students at the Ensari Lab at the Icahm School of Medicine at Mount Sinai.
Photo credit: Tian Zheng
Past work
Between 2020 and 2022, I served as the director of the DSI Scholars and Data for Good Programs, which aim to engage Columbia University’s undergraduate and master’s students in data science research through internships. The Scholars program connects students with research projects across Columbia and provides student researchers with an additional learning experience and networking opportunities. Through unique enrichment activities, this program aims to foster a learning and collaborative community in data science at Columbia.
The Data For Good program connects student volunteers to organizations and individuals working for the social good whose projects have developed a need for data science expertise. As “real world” problems with real-world data, these projects are excellent opportunities for students to learn how data science is practiced outside of the university setting and to learn how to work effectively with people for whom data science sits outside of their subject area.
Citizen Science Interactive (2021): This Data for Good Project was co-led by Jordan Siff, a graduate student in Biostatistics also at Columbia University (more info). CSI is a dashboard we designed and developed that aims to facilitate graph literacy and data science skills teaching by integrating topics from environmental sciences. The crosscutting disciplinary approach is further in line with the Next Generation Science Standards. For more information on the dashboard, you can check out the project’s Github page. The project is conducted as a part of a research collaboration with Cassie Quigley, Holly Plank (University of Pittsburgh) and Aileen Owens (EdTech Inc). Our first demo was held in October 2021, through a workshop with classroom teachers. This project is an extension of the interactive data science education tool we had developed with a team of graduate students in 2019 (see News and Events for more details). For more information on the history and trajectory of this collaboration, you can check out DSI’s feature article.
Past professional activities and former students:
- Between 2018 and 2020, I co-directed 4-day DSI Data Science Bootcamps for the Obama Foundation Scholars. The goal is to strengthen the scholars’ data literacy, understanding of the field of data science, and learn to collaborate with data scientists in a data-driven decision process. I planned the schedule of didactic lectures, hands-on data science activities for the scholars, and also help them prepare a “pitch” on their social impact project to present to members of the campus. I teach exploratory data analysis and data visualization, and also facilitate activities on algorithmic bias.
- One of my mentees, doctoral student Ashley Goodwin was named winner of the NEACSM 2020 Doctoral Category Student Investigator Competition for her presentation titled “Attenuated Response of Muscle Deoxygenation at Higher Workloads Determined by Near-Infrared Spectroscopy”. Further, as the highest ranked abstract of any graduate student, she was also awarded the President’s Cup, a competition of all research poster presentations at the Fall meeting. As a member of Ashley’s doctoral dissertation advising team, I provide data science guidance and I am very happy about this outcome. I proposed a novel data analytic framework in this work, an earlier version of which was presented at a prior ACSM meeting. So it is always exciting to see acceptance and appreciation for my interdisciplinary data science implementations within domain-specific research questions.
- Doctoral candidate Sylvia Cho’s work on fitness-for-use and quality issues in data from wearables and sensors was recently published in JMIR. This is a part of Sylvia’s doctoral work, which investigates core issues in the area of digital data, especially with respect to their secondary use.
- In June 2019, DSI participated in the Annual Columbia Alumni STEM Day for the first time. I organized and led a team of students representing the DSI at this event to create an interactive project that aimed to introduce kids to the field of data science, help them better understand how to visualize and interpret data, put it into context and disseminate their findings. We developed an interactive data science education tool that implements scientific methodology steps and aims to improve graph literacy in young children. I later led workshops held at Teachers’ College for elementary school teachers based on this tool: Leading Workshop on data literacy skills in K-12 classrooms
- This project later led to a white paper co-authored with Monica Chan, one of the doctoral students involved in the project, for which we won the Computing Community Consortium White Paper award for open source data science education.
- “Children are natural data scientists”
