Welcome to the Lab Page of Rumi Chunara, Assistant Professor at New York University.
The overarching goal of our research is to develop the principles needed to incorporate unstructured, Internet and mobile data into a better understanding of population-level health. We primarily develop computational methods across data mining, natural language processing, and machine learning to generate features for spatio-temporal population-level public health models.
*Excited to start work on our Gates Foundation Grand Challenges Exploration project. 05/19
*Our work on showing deep landscape features from satellite imagery improve disease prediction models accepted for presentation at the CVPR Workshop on Computer Vision for Global Challenges (oral presentation) 06/19
*Prof. Chunara gave Grand Rounds at Aga Khan University, Karachi 05/19
*Prof. Chunara giving talks at NYU Shanghai, the Oxford Suzhou Center for Advanced Research, Peking University and Tsinghua University 4/19
*Our paper “Race, Ethnicity and National Origin-based Discrimination in Social Media and Hate Crimes Across 100 U.S. Cities” accepted at ICWSM ’19.
*Prof. Chunara giving a talk at the Connective Media Brown Bag Lunch, Cornell Tech on 03/01
*Prof. Chunara received an NSF CAREER award! 01/19
*Our paper “Population-aware Hierarchical Bayesian Domain Adaptation” accepted at the NeurIPS Machine Learning for Health workshop 12/18
*Prof. Chunara gave an invited talk at the Epidemiology meets Data Mining and Knowledge discovery workshop at KDD 08/18
*“Creating Full Individual-level Location Timelines from Sparse Social Media Data” accepted as a full paper at ACM Sigspatial 2018. Congrats Nabeel!
*Paper accepted at CSCW 2018 “Socio-spatial Self-organizing Maps: Using Social Media to Assess Relevant Geographies for Exposure to Social Processes”. Congrats Kunal!
*New paper “Tracking Health Seeking Behavior During an Ebola Outbreak via Mobile Phones and SMS” accepted for publication in npj Digital Medicine 06/2018 (to appear)
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Watch the below video to learn about our research mission:
*New paper on arxiv: Domain Adaptation for Infection Prediction from Symptoms Based on Data from Different Study Designs and Contexts 06/2018
*First assessment of what people Tweet about in comparison to actual illness: What Do People Tweet When They’re Sick? A Preliminary Comparison of Symptom Reports and Twitter Timelines, to be presented at ICWSM Workshop on Social Media and Health 06/2018
*Feasibility of a Social Network Based Vascular Risk Reduction Program for Mild Stroke Survivors accepted for presentation at the World Stroke Congress 05/2018
*New paper on Socio-spatial Self-organizing Maps: Using Social Media to Assess Relevant Geographies for Exposure to Social Processes on arxiv 3/2018.
*“From the User to the Medium: Neural Profiling Across Web Communities” accepted as poster paper at ICWSM 3/2018.
*We continue our exploration of the need for community-sourced data in public health in our new paper on Etiology of respiratory tract infections in the community and clinic in Ilorin, Nigeria accepted (BMC Research Notes) 12/2017
*Our group selected as one of the Phase-I winners of the Healthy Behavior Data Challenge, a partnership between the Government of Canada, the Centers for Disease Control and Prevention and MaRS Discovery District 11/2017
*New paper on Using Sparse Digital Traces to Fill in Individual Level Mobility Timelines available on arxiv 10/2017.
*New paper on High-resolution Temporal Representations of Alcohol and Tobacco Behaviors from Social Media Data accepted for ACM CSCW 2018. Congrats Tom, Kunal and Anas!
*New NSF grant: Algorithms and Data for High-Frequency, Real-Time Anomaly Detection, with Dr. McCormick‘s group from UW! Awarded 08/2017
*Prof. Chunara invited speaker for the plenary session “Global public health threats in the 21st century” at the 15th Conference of the International Society of Travel Medicine. 05/2017
*Prof. Chunara gave an invited talk at The Center for Research and Interdisciplinarity – CRI. 03/2017
*Prof. Chunara invited keynote speaker at Joint Workshop on Health Intelligence at AAAI 2017. 02/2017
*Prof. Chunara invited attendee of CCC Discovery and Innovation in Smart and Pervasive Health Workshop. 12/2016
*Paper on “Denominator Issues for Personally-Generated Data in Population Health Monitoring” accepted (American Journal of Preventative Medicine). 10/2016
*Bisakha Ray’s work on “Predicting Acute Respiratory Infections from Participatory Data” accepted for an Oral Presentation at the 2016 International Society for Disease Surveillance conference 12/2016. Second Prize Award for Outstanding Student Abstract.
*Prof. Chunara to give an invited talk at the Federation of American Scientists 70th anniversary symposium in Washington DC 09/28/16
*New paper on Assessing Behavioral Stages From Social Media Data accepted for ACM CSCW 2017. Congratulations Jason!
*New paper on Network Inference from Multimodal data: A Review of Approaches from Infectious Disease Transmission (Journal of Biomedical Informatics). Congratulations Bisakha! 09/2016
*New NSF grant on Combining Community and Clinical Data for Augmenting Influenza Modeling with Dr. Shaman‘s group from Columbia! Awarded 09/2016
*Prof. Chunara to give an invited talk at Personalized Health in the Digital Age symposium at Campus Biotech in Switzerland September 2016
*Prof. Chunara to give an invited talk at CCS ’16 workshop on Digital Epidemiology and Surveillance September 2016
*Chunaralab undergrad researcher William Herrera accepted to the prestigious NIH Summer Internship Program in Biomedical Research.
*Nabeel Rehman will present his work on Using Propensity Score Matching to Understand the Relationship Between Online Health Information Sources and Vaccination Sentiment at the AAAI Spring Symposium at Stanford University in March 2016.
*Prof. Chunara was an invited speaker at a panel on Web-Based Public Health Informatics at IEEE BHI ’16 in February 2016.
*Bisakha Ray presented her work on Integrating Genomic Data in a Community-based Multi-modal Viral Transmission Model for Network Inference at the NIPS Workshop on ML for Healthcare in Montreal, December 2015.