Hi, I am Ipek. I am an Assistant Professor within the Department of Artificial Intelligence and Human Health at the Icahn School of Medicine and Hasso Plattner Institute for Digital Health at Mount Sinai. Previously, I was an Associate Research Scientist at the Data Science Institute at Columbia University in New York City. My research program focuses on mHealth and machine learning-based approaches to develop clinically relevant, ecologically valid digital patient reported outcome measures, and tools for chronic symptom self-management, grounded in women’s health conditions. (photo credit: Pam Pasco @pamashley)

Recent Updates:

• My talk at the nyhackR meetup is now available on youtube. Thank you to everyone who attended in person and virtually! I greatly enjoyed meeting everyone and the questions during the Q&A.
• A recent study with collaborators from Columbia University on breaking prolonged sedentary time was featured in the news. Being involved in this protocol with Keith and Andrea (the terrific senior and first authors of the manuscript) was a unique experience during my postdoctoral training. So the paper is particularly pleasing to see published.
• I was awarded an R01 grant by the National Institutes of Health (NICHD). This project will investigate a functional data analytic framework to design and evaluate mHealth measures of pain, quality of life, and treatment response using patient generated health data with high complexity and temporality. This study will test a novel application of Distributed Lag Models (DLMs) in this mHealth context to estimate “critical windows” of tracking analogous to the “window of susceptibility” (Further project details). We are searching for a postdoctoral research scientist who has experience with DLMs and/or FDA methods to join our team at Mt Sinai. Applications can be submitted through the LinkedIn post.

In our laboratory we conduct research on methods for combining actively-tracked and passively-collected mHealth data to investigate data methods for designing patient-centered mHealth measures, elucidating elucidating phenotypic and endotypic variation in women’s reproductive disorders (e.g., using electronic health records), and designing mHealth intervention tools for chronic symptom management. We are recruiting graduate students and postdoctoral fellows to various new projects on these topics.

1. Women’s reproductive health, participatory mHealth research

A central aim of my research is to re-tool patient-generated data via mHealth technology to better characterize conditions that are traditionally poorly documented and not well understood…

2. Digital phenotyping: Elucidating clinically meaningful variations in patient profiles

I use informatics and data-driven approaches to delineate symptom trajectories in diseases with a dynamic course (e.g., endometriosis, multiple sclerosis), and identification of self-management approaches for their effective management…

3. Symptom self-management and computational methods for patient-generated health data:

As a trained kinesiologist, a focus on physical activity and its health outcomes is a central theme across my projects…

An exhaustive meta-analytic review documenting a mysterious “women’s” issue, otherwise known as endometriosis.^[1] 

^[1]term used to describe a clinical etiology that thus far has only been identified in primates with a female reproductive system, an anatomical structure of decidedly lower importance in comparison to those of the male primate.

In the fall of 2020, I participated in the 13^th Annual Imagine Film Festival’s Symbiosis short film competition. I partnered with Camille Hollett-French to make a film that expresses our frustrations about endometriosis from multiple perspectives. Camille is a Vancouver-based filmmaker who herself has endometriosis. The end product is ENDOMIC, a “documentary” through the lens of satire about modern medicine’s and society’s take on endometriosis. Using a mock-meets-doc format, the film weaves in real patient experiences in parallel with a narrative exploration of its history in the scientific literature, disparities in diagnosis and treatment, and lack of research funding, to raise awareness and help sense-making for patients.

Dances with Films 2021

ENDOMIC is unique in several aspects. First, we crafted its satirical story-telling using content from published peer-reviewed research and real patient experiences (even though some of them sound fictional at times!). Next, it features some of my most recent academic work demonstrating how mobile health technology and direct patient input can be used to improve our understanding of endometriosis. The film also discusses inclusive medicine and healthcare, a first in this realm, and about a third of the production and acting crew include members with endometriosis in real life.

You can follow ENDOMIC (@abloodycrisis) on Instagram, Twitter, and Facebook. Click below to read more about the film’s world premiere at the 2021 Slamdance Film Festival, media coverage, and reviews.

I teach, advise students and direct a range of research programs as a part of my academic appointment.

Photo credit: Tian Zheng

I am 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:  I direct this Data for Good Project and work with 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 is being held in October 2021, through a workshop with classroom teachers. This project is an extension of the interactive data science education tool I developed with a team of graduate students back 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.

• A new article written by Dr. Karina Alexanyan was published in Data Science Institute News about my current role and research projects.
• I was awarded an R01 grant by the National Institutes of Health (NICHD) in September. This project will investigate a functional data analytic framework to design and evaluate mHealth measures of pain, quality of life, and treatment response using patient generated health data with high complexity and temporality. This study will test a novel application of Distributed Lag Models (DLMs) in this mHealth context to estimate “critical windows” of tracking analogous to the “window of susceptibility” (Further project details).
• My latest work on exercise behavior and pain symptom patterns in endometriosis has been been published in BMJ Open. It is available as open-access (aka. no paywall!).
• A new feature about Rights CoLab group, who participate in DSI’s Data for Good program, written by Karina Alexanyan, PhD, was recently published.
• I was a speaker at this year’s New York R Conference in June! I have been attending these events for several years so it was very exciting to be invited as a speaker. The event was held during June 8-10th as a hybrid conference. The recording of my talk on functional clustering using wearable data is available on youtube.
• I presented some of my latest work on integrating functional data methods with unsupervised learning for clustering daily physical activity trajectories at DSI’s Annual Data Science Day on April 6th.
• I had the great pleasure to join the Symbiosis Competition judges panel at this year’s Imagine Science Film Festival. The event was held October 15th-22nd in NYC. Symbiosis is where I met my co-director and partner in crime Camille Hollett-French last year. Moreover, I got to meet the festival directors and organizers in-person for the first time this year. Overall an exciting time. Congrats to this year’s Symbiosis winners Arianna and Rashu!
• ENDOMIC has been announced among the official selections by the 12th Awareness Film Festival! We are thrilled to be a part of this festival, whose mission is to inform and inspire audiences by spotlighting film-makers committed to making positive change throughout the world. This year’s event will be held October 21st-November 1st in 2021 Los Angeles.
• My presentation on digital health applications of unsupervised learning at the 2021 Annual DSI Data Science Day is now available online.
• A piece by Karina Alexanyan on my recent collaboration on ENDOMIC as inspired by my research is now live. It was great pleasure to chat with Karina and I am excited about how the piece turned out.
• My latest work on digital phenotyping of sleep using unsupervised machine learning was presented at the DSI Health Analytics Poster Session was held on April 2nd, 2021.
• Responsible Investor magazine recently covered (pdf version here) a project conducted by Rights CoLab, one of our Data for Good collaborators.
• With my colleagues at Columbia, I was recently awarded seed funds from the Data Science Institute to study digital sleep phenotypes and examine the associations of daily exposure to minority stressors (such as experiences of discrimination and anticipated discrimination) with sleep health among Black and Latinx sexual and gender minority adults. Read more on the aims of the project aims and the DSI Seed Funds
• Speaking at the DSI Summer Career Webinar Series
• Virtual Data Science Day 2020 at DSI
• 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”
• Guest Post on Thrive Global: “Making your wearables work for you“

Credit: Pam Pasco (@pamashley)

If you would like to contact me, you can reach me via Linkedin or my email at ipek.ensari@mssm.edu.

Thank you for visiting my website!