TALKS & PUBLICATIONS

Journals

• E. Ramirez, N. Marinsek, B. Bradshaw, R. Kanard, L. Foschini. Continuous Digital Assessment for Weight Loss Surgery Patients. Digital Biomarkers (2020).
• X. Han, Y. Hu, L. Foschini, L. Chinitz, L. Jankelson, R. Ranganath. Deep learning models for electrocardiograms are susceptible to adversarial attack. Nature Medicine (2020).
• S. Deering, M.M. Grade, J.K. Uppal, L. Foschini, J.L. Juusola, A.M. Amdur, C.J. Stepnowsky. Accelerating Research With Technology: Rapid Recruitment for a Large-Scale Web-Based Sleep Study. JMIR research protocols (2019).
• M. Wildman, R. Eulogio, R. Singh, E. Ramirez, L. Foschini, Evidation Health; Amrutha Nadarajan, Brandon Booth, Karel Mundnich, Emilio Ferrara, Kristina Lerman, Shrikanth Narayanan. Comparison of Heart Rate Measurement Between the Fitbit Charge 2 and OMsignal Smart Garments: A Free Living Study. Annals of Behavioral Science (2019).
• T. Quisel, L. Foschini, S.M. Zbikowski, J.L. Juusola. The association between medication adherence for chronic conditions and digital health activity tracking. Journal of Medical Internet Research (2019).
• M. McDermott, S. Wang, N. Marinsek, R. Ranganath, M. Ghassemi, L. Foschini. Reproducibility in Machine Learning for Health. arXiv preprint arXiv (2019).
• X. Han, Y. Hu, L. Foschini, L. Jankelson, R. Ranganath. Adversarial Examples for Electrocardiograms. arXiv preprint arXiv (2019).
• J.L.A. Tran, S. Kumar, R. Eulogio, E. Ramirez, L. Foschini, J.L. Juusola. Pain Management Strategies and Activity Tracker Utilization in a Large-Scale Chronic Pain Study. Value in Health (2019).
• R. Chan, F. Jankovic, N. Marinsek, L. Foschini, L. Kourtis, A. Signorini, M. Pugh, J. Shen, R. Yaari, V. Maljkovic, M. Sunga, H. Hee Song, H. Joon Jun, B. Tseng, A. Trister. Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (2019).
• C. Bachireddy, A. Joung, L.K. John, F. Gino, B. Tuckfield, L. Foschini, K.L. Milkman. Effect of Different Financial Incentive Structures on Promoting Physical Activity Among Adults. JAMA network open (2019).
• C.J. Cerrada, C. Tai, S. Kumar, K. Scherer, R. Eulogio, E. Ramirez, L. Foschini, J. Juusola. African American Participants Experience Greater Pain Severity and Pain Interference Compared to Non­-Hispanic Whites in a Large Scale Virtual Study on Chronic Pain. 41st Annual Meeting of the Society for Medical Decision Making. (SMDM), 2019.
• S.I. Samson, K. Konty, W.N. Lee, T. Quisel, L. Foschini, D. Kerr, J. Liska, H. Mills, R. Hollingsworth, M. Greenberg, A.C. Beal. Quantifying the Impact of Influenza Among Persons With Type 2 Diabetes Mellitus: A New Approach to Determine Medical and Physical Activity Impact. Journal of diabetes science and technology (2019).
• W.N. Lee, D. Stück, K. Konti, C. Rivers, C.R. Brown, S.M. Zbikowski, L. Foschini. Large-scale influenza vaccination promotion on a mobile app platform: A randomized controlled trial. Vaccine (2019).
• T. Quisel, L. Foschini, S.M. Zbikowski, J.L. Juusola. The association between medication adherence for chronic conditions and digital health activity tracking. Journal of medical Internet research (2019).
• M.S. Patel, L. Foschini, G.W. Kurtzman, J. Zhu, W. Wang, C.A.L. Rareshide, S.M. Zbikowski. Using Wearable Devices and Smartphones to Track Physical Activity: Initial Activation, Sustained Use, and Step Counts Across Sociodemographic Characteristics in a National Sample. Annals of Internal Medicine (2017).
• J.L. Juusola, T. Quisel, L. Foschini, J. Ladapo. The Impact of an Online Crowdsourcing Diagnostic Tool on Health Care Utilization: A Case Study Using a Novel Approach to Retrospective Claims Analysis. Journal of Medical Internet Research (2016).
• A. Pourzanjani, T. Quisel, L. Foschini. Adherent Use of Digital Health Trackers Is Associated with Weight Loss. Plos One (2016).
• A.E. Feldmann, L. Foschini. Balanced Partitions of Trees and Applications. Algorithmica (2013).
• L. Foschini, J. Hershberger, and S. Suri. On the Complexity of Time-Dependent Shortest Paths. Algorithmica (2012).
• L. Foschini, R. Grossi, A. Gupta, and J.S. Vitter. When indexing equals compression: Experiments with compressing suffix arrays and applications. The ACM Transactions on Algorithms (2006).
• L. Valcarenghi, L. Foschini, F. Paolucci, F. Cugini, and P. Castoldi. Topology Discovery Services for Monitoring the Global Grid. Communications Magazine (2006).

Conferences and Workshops

• H. Hallgrímsson, F. Jankovic, T. Althoff, L. Foschini. Learning Individualized Cardiovascular Responses from Large-scale Wearable Sensors Data. Neural Information Processing Systems , Workshop on Machine Learning for Health (2018).
• D. Stück, W. Lee, L. Foschini, R. Harpaz, W. DuMouchel, S.M. Zbikowski, C.R. Brown. Predicting Influenza Vaccinations using Administrative Claims and Consumer Health Data. Society for Medical Decision Making (2018).
• S. Kumar, W. Lee, J. LA Tran, L. Foschini, J.L. Juusola.  Activity Tracker-Based Behavioral Data Is Correlated with Validated Quality-of-Life Metrics. Society for Medical Decision Making (2018).
• D. Stück, H. Tómas, G. Ver Steeg, A. Epasto, L. Foschini. Novel Digital Voice Biomarkers of Dementia from the Framingham Study.  Alzheimer’s Association International Conference (2018). 
• S. Samson, W. Lee, T. Quisel, L. Foschini, J. Liska, H. Mills, R. Hollingsworth, M. Greenberg, A.C. Beal. Using Claims and Wearable Devices Data to Quantify Influenza Outcomes Among Type 2 Diabetes Patients. American Diabetes Association (2018). 
• S. Kumar, J. Tran, W. Lee, B. Bradshaw, L. Foschini, J. Juusola. Longitudinal Data from Activity Trackers Show that Those with Greater Inconsistency in Activity Levels Are More Likely to Develop More Severe Depression. International Society for Pharmacoeconomics and Outcomes Research (2018). 
• S. Kumar, T. Quisel, L. Foschini, J. Juusola. Digital Tracker Data from Over 100,000 Individuals Show Lower Activity Levels in Individuals with Multiple Chronic Conditions. Society of Behavioral Medicine (2018). 
• L. Foschini, J. Medin, V. Bezlyak, D. Stuck, D. Silva, W. Lee. Real-World Use of Wearable Devices in a Large Multiple Sclerosis Cohort. American Academy of Neurology (2018).
• L. Cheng, D. Stück, T. Quisel, L. Foschini. The Impact of Missing Data in User-Generated mHealth Time Series.Neural Information Processing Systems , Workshop on Machine Learning for Health (2017). 
• S. Kumar, D. Stück, W. Lee, J. Juusola, L. Foschini. Digital Activity Tracker-Based Behavioral Characteristics Associated with Comorbid Mental Health Illness Symptoms Among Individuals With Diabetes. American Medical Informatics Association (2017).
• S. Kumar, H. Moseson, W. Lee, D. Stück, L. Foschini, J. Juusola. Activity Trackers Show That Inconsistent Sleep Patterns are Associated with Severe Forms of Anxiety and Depression. Society for Medical Decision Making (2017).
• T. Quisel, L. Foschini, A. Signorini, D.C. Kale. Collecting and Analyzing Millions of mHealth Data Streams. Knowledge Discover and Data Mining (2017). 
• T. Quisel, W. Lee, L. Foschini. Observation Time vs. Performance in Digital Phenotyping. ACM MobiSys (2017).
• S. Kumar, T. Quisel, L. Foschini, J. Juusola. Digital Trackers show that High Intensity Exercising and Consistent Sleep patterns are Associated with Positive Self-Reported Health Status. International Society for Pharmacoeconomics and Outcomes Research (2017).
• D. Stück, H. Tómas, G. Steeg, A. Epasto, L. Foschini. The Spread of Physical Activity Through Social Networks. ACM World Wide Web Conference (2017). 
• T. Quisel, L. Foschini, C. Axelrod, D. Kerr. Self-Care Tracking and Blood Glucose Stability Among One Drop Mobile App Users. Society of Behavioral Medicine (2017). 
• L. Oley, D. Stück, L. Foschini, J. Juusola, S. Kumar, J. Torous.  Impact of Pokémon GO on Physical Activity: A Pre-post Analysis. Society of Behavioral Medicine (2017). 
• T. Quisel, J. Torous, L. Foschini. Restless Sleep is Associated with Weight Gain: A Within-Subject Analysis. Society of Behavioral Medicine (2017). 
• T. Quisel, R. Milani, L. Foschini. Improving Heart Failure Unit Readmission Prediction. American College of Cardiology (2017).
• T. Quisel, D. Kale, L. Foschini. Intra-day Activity Better Predicts Chronic Conditions. Neural Information Processing Systems , Workshop on Machine Learning for Health (2016). 
• T. Quisel, L. Foschini, A. Signorini. Behavioral Phenotyping of Digital Health Tracker Data. SIAM Data Mining (2016). 
• L. John, K.L. Milkman, F. Gino, B. Tuckfield, L. Foschini. The Role of Incentive Salience in Habit Formation. Harvard Business School (2016). 
• A. Pourzanjani, T. Quisel, D. Sontag, L. Foschini. Fully Bayesian Unsupervised Disease Progression Modeling. Neural Information Processing Systems (2015). 
• T. Quisel, L. Foschini, J. Juusola. Health Activity Tracking Is Associated With Higher Medication Adherence. Society for Medical Decision Making (2015).
• A. E. Feldmann and L. Foschini. Balanced Partitions of Trees and Applications. Symposium on Theoretical Aspects of Computer Science (STACS 2012).
• H. Yıldız, L. Foschini, J. Hershberger, and S. Suri. The Union of Probabilistic Boxes: Maintaining the Volume. European Symposium on Algorithms (ESA 2011).
• L. Cavedon, L. Foschini, and G. Vigna. Getting the Face Behind the Squares: Reconstructing Pixelized Video Streams. USENIX Workshop on Offensive Technologies (WOOT 2011).
• S. Gauglitz, L. Foschini, M. Turk, and T. Höllerer. Efficiently Selecting Spatially Distributed Keypoints for Visual Tracking. IEEE International Conference on Image Processing (ICIP 2011).
• F. Uyeda, L. Foschini, S. Suri, and G. Varghese. Efficiently Measuring Bandwidth at All Time Scales. Symposium on Networked Systems Design and Implementation (NSDI 2011).
• L. Foschini, J. Hershberger, and S. Suri. On the Complexity of Time-Dependent Shortest Paths. The ACM-SIAM Symposium on Discrete Algorithms (SODA 2011).
• S. Gandhi, L. Foschini, and S. Suri. Space-efficient Online Approximation of Time Series Data: Streams, Amnesia, and Out-of-order. International Conference on Data Engineering (ICDE 2010).
• C. Buragohain, L. Foschini, and S. Suri. Untangling the Braid: Finding Outliers in a Set of Streams. Workshop on Algorithm Engineering and Experiments (ALENEX 2010).
• A. Gulli, S. Cataudella, and L. Foschini. TC-SocialRank: Ranking the Social Web. Workshop on Algorithms and Models for the Web Graph (WAW 2009).
• L. Foschini, A. V. Thapliyal, L. Cavallaro, C. Kruegel, and G. Vigna. A Parallel Architecture for Stateful, High-Speed Intrusion Detection. International Conference on Information Systems Security (ICISS 2008).
• M. Cococcioni, L. Foschini, B. Lazzerini, and F. Marcelloni. Complexity Reduction of Mamdani Fuzzy Systems through Multi-valued Logic Minimization. IEEE International Conference on Systems, Man and Cybernetics (SMC 2008).
• L. Valcarenghi, F. Paolucci, L. Foschini, F. Cugini, and P. Castoldi. Centralized and Distributed Grid Topology Discovery Service Implementations. Poster (Hot Interconnects 13, 2005).
• L. Foschini, R. Grossi, A. Gupta, and J. S. Vitter. Fast Compression with a static model in High-Order Entropy. IEEE Data Compression Conference (DCC 04).

Professional Service

Theses