Afsaneh Doryab

My research is at the intersection of health, mobile and ubiquitous computing, AI, and Human Computer Interaction.

I work on computational modeling of human behavior from data streams collected through mobile, wearable, and embedded sensors. Examples of my work in the health domain include detection of behavior change in people with depression, predicting mania-depression episodes in bipolar disorder, estimation of symptom severity in cancer patients, and modeling of surgical activities inside the operating room.

I also work on intelligent applications for social good. My recent work in Context-aware Peer-to-Peer economic exchange is focused on connecting communities of people through mobile technology to enable successful and meaningful service transactions, especially in low-income communities. In my research, I draw on methods from Machine Learning, Data Mining, Statistics, and Human-Computer Interaction.

Announcements

Seeking PhD Students

The Intelligent Human-Centered Computing (IHCC) lab at the University of Virginia (https://engineering.virginia.edu/intelligent-human-centered-computing) is looking for PhD students and postdocs with a strong background in Computer Science, Math, Machine Learning, and AI to work on research projects in the area of ubiquitous and mobile computing and human-centered computing focused on social good and health.

The IHCC lab aims to intelligently explore the patterns inherent to human behavior through machine learning and computational models of passive data streams. From this knowledge, we can make predictions about potential health outcomes and suggest individualized improvements to promote a healthier, happier community.

TO APPLY: Please contact Dr. Afsaneh Doryab (ad4ks@virginia.edu) with qualifications and to discuss research fit.

News and Events

AAAI 2020 Conference

February 7th-12th, 2020

I presented my research in collaboration with Xi Chen at the 34th AAAI Conference on Artificial Intelligence in New York, New York. The paper proposes a novel approach to improving the accuracy of feature selection, specifically in data sets with large feature sets and a small number of data points. Existing methods of feature selection typically do not achieve high accuracy. The approach presented optimizes feature selection through Frequent Pattern Growth algorithm to identify frequently occurring sets that appear among the top features selected.

Find the paper here: Optimizing the Feature Selection Process for Better Accuracy in Datasets with a Large Number of Features

Doryab Presents the First Paper on Modeling Biobehavioral Rhythms for Predicting Rehospitalization Risk

ESE Weekly News | September 27th, 2019

The paper titled "Modeling Biobehavioral Rhythms with Passive Sensing in the Wild: A Case Study to Predict Readmission Risk after Pancreatic Surgery" was presented at Ubicomp, the Association for Computing Machinery (ACM) leading conference on ubiquitous and mobile computing.

Doryab's Paper on the Estimation of Symptom Severity During Chemotherapy from Passively Sensed Data Selected as the Best Cancer Informatics Paper by International Medical Informatics Association

ESE Weekly News | September 20th, 2019

The Editorial Board of the 2019 IMIA Yearbook of Medical Informatics selected article entitled: "Estimation of symptom severity during chemotherapy from passively sensed data: Exploratory study" which was led by Dr. Afsaneh Doryab for listing in the 2019 edition of the Yearbook as one of the best articles published in 2018 in the ‘Cancer Informatics’ subfield of medical informatics.

Chen and Doryab's poster presented at the 34th AAAI Conference on Artificial Intelligence

Research Coverage

Publications

2020

  • Can Smartphone Co-locations Detect Friendship? It Depends on How You Model It [PDF]

MM Malik, A Doryab, M Merrill, AK Dey

arXiv preprint arXiv:2008.02919, July 2020

  • A Deep Learning Framework for Prediction of Readmission Risk After Cancer Surgery From Mobile Data Streams

A Doryab

Proceedings of Deep Learning for Wellbeing Applications Leveraging Mobile Devices and Edge Computing, June 2020

  • Modeling Biological Rhythms to Predict Mental and Physical Readiness [PDF]

Ben Carper, Dillon McGowan, Samantha Miller, Joe Nelson, Leah Palombi, Lina Romeo, Kayla Spigelman, Afsaneh Doryab

2020 Systems and Information Engineering Design Symposium (SIEDS), April 2020

  • CoRhythMo: A Computational Framework for Modeling Biobehavioral Rhythms from Mobile and Wearable Data Streams [PDF]

Runze Yan, Xinwen Liu, Janine Dutcher, Michael Tumminia, Daniella Villalba, Sheldon Cohen, David Creswell, Kasey Creswell, Jennifer Mankoff, Anind Dey, Afsaneh Doryab

bioRxiv, Jan 2020

2019

  • A Robot’s Expressive Language Affects Human Strategy and Perceptions in a Competitive Game [PDF]

Aaron M Roth, Samantha Reig, Umang Bhatt, Jonathan Shulgach, Tamara Amin, Afsaneh Doryab, Fei Fang, Manuela Veloso

2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), Oct 2019

Xuhai Xu, Prerna Chikersal, Afsaneh Doryab, Daniella K Villalba, Janine M Dutcher, Michael J Tumminia, Tim Althoff, Sheldon Cohen, Kasey G Creswell, J David Creswell, Jennifer Mankoff, Anind K Dey

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Sept 2019

  • Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data [PDF]

Afsaneh Doryab, Daniella K Villalba, Prerna Chikersal, Janine M Dutcher, Michael Tumminia, Xinwen Liu, Sheldon Cohen, Kasey Creswell, Jennifer Mankoff, John D Creswell, Anind K Dey

JMIR mHealth and uHealth, July 2019

Jiawei Chen, Afsaneh Doryab, Benjamin V Hanrahan, Alaaeddine Yousfi, Jordan Beck, Xiying Wang, Victoria Bellotti, Anind K Dey, John M Carroll

International Conference on Information, March 2019

Afsaneh Doryab, Anind K Dey, Grace Kao, Carissa Low

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, March 2019

2018

  • Extraction of Behavioral Features from Smartphone and Wearable Data [PDF]

Afsaneh Doryab, Prerna Chikarsel, Xinwen Liu, Anind K Dey

arXiv preprint arXiv:1812.10394, Dec 2018

  • The Impact of Humanoid Affect Expression on Human Behavior in a Game-Theoretic Setting [PDF]

Aaron M Roth, Umang Bhatt, Tamara Amin, Afsaneh Doryab, Fei Fang, Manuela Veloso

arXiv preprint arXiv:1806.03671, June 2018

  • Identifying Symptoms Using Technology [PDF]

Afsaneh Doryab

Technology and Adolescent Mental Health, March 2018

2017

  • If It’s Convenient: Leveraging Context in Peer-to-Peer Variable Service Transaction Recommendations [PDF]

Afsaneh Doryab, Victoria Bellotti, Alaaeddine Yousfi, Shuobi Wu, John M Carroll, Anind K Dey

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Sept 2017

  • Estimation of Symptom Severity During Chemotherapy from Passively Sensed Data: Exploratory Study [PDF]

Afsaneh Doryab, Victoria Bellotti, Alaaeddine Yousfi, Shuobi Wu, John M Carroll, Anind K Dey

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Sept 2017

2016

AC BD, Christine Bauer, Afsaneh Doryab

Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, May 2016

  • 'MASTerful'Matchmaking in Service Transactions: Inferred Abilities, Needs and Interests versus Activity Histories [PDF]

Hyunggu Jung, Victoria Bellotti, Afsaneh Doryab, Dean Leitersdorf, Jiawei Chen, Benjamin V Hanrahan, Sooyeon Lee, Dan Turner, Anind K Dey, John M Carroll

Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, May 2016

  • Modeling Transit Patterns Via Mobile App Logs [PDF]

Anthony Tomasic, Aaron Steinfeld, John Zimmerman, Afsaneh Doryab

University Transportation Centers Program (US)

2015

  • Impact Factor Analysis: Combining Prediction With Parameter Ranking to Reveal the Impact of Behavior on Health Outcome [PDF]

Afsaneh Doryab, Mads Frost, Maria Faurholt-Jepsen, Lars V Kessing, Jakob E Bardram

Personal and Ubiquitous Computing, July 2015

2014

  • Can Your Smartphone Reveal If You Are Depressed? [PDF]

Afsaneh Doryab, Jun Ki Min, Jason Wiese, John Zimmerman, Jason Hong

KDD 2014 Workshop on Connected Health at Big Data Era, July 2014

  • Detection of Behavior Change in People with Depression [PDF]

Afsaneh Doryab, Jun Ki Min, Jason Wiese, John Zimmerman, Jason Hong

Modern Artificial Intelligence for Health Analytics Workshop at the Twenty-Eighth AAAI Conference on Artificial Intelligence, June 2014

  • BeWell: Sensing Sleep, Physical Activities and Social Interactions to Promote Wellbeing [PDF]

Nicholas D Lane, Mu Lin, Mashfiqui Mohammod, Xiaochao Yang, Hong Lu, Giuseppe Cardone, Shahid Ali, Afsaneh Doryab, Ethan Berke, Andrew T Campbell, Tanzeem Choudhury

Mobile Networks and Applications, June 2014

  • Toss'N'Turn: Smartphone as Sleep and Sleep Quality Detector [PDF]

Jun-Ki Min, Afsaneh Doryab, Jason Wiese, Shahriyar Amini, John Zimmerman, Jason I Hong

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, April 2014

2013

  • Supporting Disease Insight Through Data Analysis: Refinements of the MONARCA Self-Assessment System [PDF]

Mads Frost, Afsaneh Doryab, Maria Faurholt-Jepsen, Lars Vedel Kessing, Jakob E Bardram

Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Sept 2013

  • Disease Insights Through Analysis: Using Machine Learning to Provide Feedback in the MONARCA System [PDF]

Mads Frost, Afsaneh Doryab, Jakob E Bardram

Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare, May 2013

2012

Mu Lin, Nicholas D Lane, Mashfiqui Mohammod, Xiaochao Yang, Hong Lu, Giuseppe Cardone, Shahid Ali, Afsaneh Doryab, Ethan Berke, Andrew T Campbell, Tanzeem Choudhury

Proceedings of the Conference on Wireless Health, Oct 2012

  • Activity Recognition in Collaborative Environments

Afsaneh Doryab, Julian Togelius

The 2012 International Joint Conference on Neural Networks (IJCNN), June 2012

  • Activity-Aware Recommendation for Collaborative Work in Operating Rooms [PDF]

Afsaneh Doryab, Julian Togelius, Jakob Bardram

Proceedings of the 2012 ACM International Conference on Intelligent User Interfaces, Feb 2012

2011

  • Context- and Activity-awareness in Collaborative Environments [PDF]

Afsaneh Doryab, Jakob Bardram

Proceedings of the 2011 International Qorkshop on Situation Activity & Goal Awareness, Sept 2011

  • Bewell: A Smartphone Application to Monitor, Model and Promote Wellbeing [PDF]

Nicholas D Lane, Mashfiqui Mohammod, Mu Lin, Xiaochao Yang, Hong Lu, Shahid Ali, Afsaneh Doryab, Ethan Berke, Tanzeem Choudhury, Andrew Campbell

5th International ICST Conference on Pervasive Computing Technologies for Healthcare, May 2011

  • Phase Recognition During Surgical Procedures Using Embedded and Body-worn Sensors [PDF]

Jakob E Bardram, Afsaneh Doryab, Rune M Jensen, Poul M Lange, Kristian LG Nielsen, Søren T Petersen

2011 IEEE International Conference on Pervasive Computing and Communications (PerCom), March 2011

  • Activity Analysis: Applying Activity Theory to Analyze Complex Work in Hospitals [PDF]

Jakob Bardram, Afsaneh Doryab

Proceedings of the ACM 2011 Conference on Computer Supported Cooperative Work, March 2011

  • Designing Activity-aware Recommender Systems for Operating Rooms [PDF]

Afsaneh Doryab, Jakob E Bardram

Proceedings of the 2011 Workshop on Context-awareness in Retrieval and Recommendation, Feb 2011

2009

  • Clinical Surfaces – Activity-Based Computing for Distributed Multi-Display Environments in Hospitals [PDF]

Jakob Bardram, Jonathan Bunde-Pedersen, Afsaneh Doryab, Steffen Sørensen

IFIP Conference on Human-Computer Interaction, July 2009

  • Concurrent Activity Recognition for Clinical Work [PDF]

Afsaneh Doryab, Julian Togelius