Selected
Publications
M.
Rakic, S. Gai, E. Chollet, J. Guttag, and A. Dalca, “Pancakes: Consistent
Multi-Protocol Image Segmentation Across Biomedical Domains,” NeurIPS 2025, December 2025.
D.
Shanmugam, S. Sadhuka, M. Raghavan, J. Guttag, B.
Berger, and E. Pierson, “Estimating Classifier Performance With Limited
Labels,” NeurIPS 2025, December 2025.
H.
Wong, J. Ortiz, J. Guttag, and A. Dalca, “MultiverSeg:
Scalable Interactive Segmentation of Biomedical Imaging Datasets with
In-context Guidance,” ICCV 2025, October, 2025.
D.
Shanmugam, H. Lu, S. Swaminarayan, and J. Guttag, “Test-time augmentation Improves
Efficiency in Conformal Prediction,” CVPR 2025, June 2025.
M. Abulnaga, A. Hoopes, N. Dey, M. Hoffmann, B. Fischl, J.Guttag, and A. Dalca, “MultiMorph:
On-demand Atlas Construction,” CVPR 2025, June 2025.
K.
Matton, R. Ness, J. Guttag, and E. Kiciman, “Walk the
Talk? Measuring the Faithfulness of Large Language Model Explanations,” ICLR
2025, April 2025.
H.
Wong, M. Rakic, J. Guttag, and A. Dalca, “ScribblePrompt:
Fast and Flexible Interactive Segmentation for Any Medical Image,” ECCV 2024,
September 2024.
I.
Perros, J. Tran, M. Saeed, A. Fendrick, J. Guttag and Z. Syed, “Reducing Fraud,
Waste, and Abuse through Real-time AI-based Screening: Prospective Results in
Deployment,” NEJM Catalyst, September 2024.
M.
Rakic, H. Wong, J. Ortiz. B. Cimini, J. Guttag, and A. Dalca, “Tyche: Stochastic
In-Context Learning for Medical Image Segmentation,” CVPR 2024, June
2024.
J.
Ortiz, J. Guttag, and A. Dalca, “Magnitude Invariant Parameterizations Improve Hypernetwork
Learning,” ICLR 2024, May 2024.
J.
Ortiz, J. Guttag, and A. Dalca, “Scale-space Hypernetworks for Efficient
Biomedical Image Analysis,” NeurIPS 2023,
December 2023.
V.
Butoi, J. Ortiz*, T. Ma, J. Guttag, M. Sabuncu, and A.
Dalca, “UniverSeg: Universal Medical Image
Segmentation,” ICCV 2023, October 2023.
R.
Movva, D. Shanmugam, K. Hou, P. Pathak, J. Guttag, N. Garg, and E. Pierson, “Course
race data conceals disparities in clinical risk score performance,” MLHC 2023,
August 2023.
A.
Raghu, P. Chandak, R. Alam, J. Guttag, and C. Stultz, “Sequential
Multi-Dimensional Self-Supervised Learning for Clinical Time Series,” ICML
2023, July 2023.
R.
Lewis, K. Matton, R. Picard and J. Guttag, “Contrastive Learning of
Electrodermal Activity Representations for Stress Detection,” CHIL 2023,
June 2023.
Saliency Cards: A Framework to
Characterize and Compare Saliency Methods,” 2023 ACM Conference on
Fairness, Accountability, and Transparency. FAccT '23, June 2023.
H.
Suresh, D. Shanmugam, A. Bryan, T. Chen, A.D’Amour,
J. Guttag, and A.Satyanarayan, “Kaleidoscope:
Semantically-grounded, context-specific model evaluation,” CHI Conference on Human Factors in Computing Systems
(CHI ’23), April 2023.
O.
Murton, G. Dec, R. Hillman, M. Majmudar, J. Steiner, J. Guttag, and D.Mehta, “Acoustic voice and speech biomarkers of treatment
status during hospitalization for acute decompensated heart failure.” Applied
Sciences, February 2023.
D. Shanmguam, K. Lewis, J. Oritz, A. Kurant, and J. Guttag,
“At the Intersection of Conceptual Art and Deep Learning: The End of
Signature,” NeurIPS Workshop on Broadening
Research Collaborations, December 2022.
K. Matton, R. Lewis, J. Guttag, and R. Picard, “Contrastive Learning of Electrodermal Activity Representations for Stress Detection,” NeurIPS Learning from Time Series for Health Workshop, December 2022.
A. Raghu, P. Chandak, R. Alam, J. Guttag, and C.
Stultz, “Contrastive Pre-Training for Multimodal Medical Time Series,” NeurIPS Workshop on Learning from Time Series for
Health, December 2022.
K. Matton, R. Picard, and J.
Guttag, “Invariance-based Causal Estimation in the Presence of Concept Drift,” Uncertainty
in AI Workshop on Causal Representation Learning, August 2022.
H.
Lu, D. Shanmugam, H. Suresh, and J. Guttag, “Improved Text Classification via
Test-Time Augmentation,” Updatable ML, July 2022.
A.
Hoopes, M. Hoffmann, D. Greve, B. Fischl, J Guttag, and A. Dalca, “Learning the
effect of registration hyperparameters with hypermorph,” Machine Learning
for Biomedical Imaging (MELBA), July 2022.
M. Namasivayam , P.
Myers, J. Guttag, R. Capoulade , P. Pibarot , M. Picard, J. Hung, and C. Stultz, “Predicting
outcomes in patients with aortic stenosis using machine learning: the Aortic
Stenosis Risk (ASteRisk) score,” Open Heart, May 2022.
A.
Hoopes, M. Hoffmann, B. Fischl, J. Guttag, A.V. Dalca, “Learning the Effect of
Registration Hyperparameters with HyperMorph,” Machine
Learning for Biological Engineering, April, 2022.
A.
Raghu, D. Shanmugam, E. Pomerantsev, J. Guttag, and C. Stultz, “Data Augmentation for
Electrocardiograms,” CHIL 2022, April 2022.
H.
Suresh, K. Lewis, J. Guttag, and A. Satyanarayan, “Intuitively assessing ml model
reliability through example-based explanations and editing model inputs,”
International Conference on Intelligent User Interfaces, March 2022.
E.
Mu, S. Jabbour, A. Dalca, J. Guttag, J. Wiens, and M. Sjoding,
“Augmenting Existing Deterioration Indices with Chest Radiographs to Predict
Clinical Deterioration,” PLOS One, February 2022.
D.
Shanmugam, D. Blalock, G. Balakrishnan, J. Guttag, "Better Aggregation in Test-Time
Augmentation". ICCV 2021, October 2021.
H.
Suresh, and J. Guttag, “A Framework of Potential Sources of Harm Throughout the
Machine Learning Life Cycle,” ACM conference on Equity and Access in
Algorithms, Mechanisms, and Optimization, October 2021.
H. Suresh,
and J. Guttag, “Understanding Potential Sources of Harm throughout the Machine
Learning Life Cycle,” MIT Case Studies in Social and Ethical
Responsibilities of Computing, August 2021.
M. Makar, L. West, D. Hooper, E. Horvitz, E. Shenoy, and J. Guttag, “Exploiting Structured Data for Learning Contagious Diseases under Incomplete Testing,” ICML 2021, July 2021.
D. Blalock,
and J. and Guttag, “Multiplying Matrices Without Multiplying,” ICML 2021,
July 2021.
A.
Hoopes, M. Hoffmann, B. Fischl, J. Guttag, A.V. Dalca, “HyperMorph:
Amortized Hyperparameter Learning for Image Registration,” IPMI: Information
Processing and Medical Imaging, June 2021.
A.
Raghu, J. Guttag, K. Young, E. Pomerantsev, A. Dalca,
and C. Stultz, “Learning to Predict with Supporting Evidence: Applications to
Clinical Risk Prediction,” ACM Conference on Health, Inference, and Learning
(CHIL), April 2021.
S. Gaube, S., H. Suresh, M. Raue, A. Merritt, S. Berkowitz, E.
Lermer, J. Coughlin, J. Guttag, E. Colak, and M.
Ghassemi, “Do as AI say: susceptibility in deployment of clinical
decision-aids,” npj Digital Medicine,
4, 31, February 2021.
A.
Raghu, C. Stultz, and J. Guttag, “Learning to Predict and Support for Clinical
Risk Stratification,” ML4Health NEURIPS Workshop, December 2020.
M.
Saeed, D. Goyal, J. Guttag, Z. Syed, R. Mehta, and Z. Elahi, “Recommending
Providers for Surgical Care: Comparing Consumer Ratings, Quality Stars,
Reputation Rankings, Average Volumes, Average Outcomes and Machine Learning for
Recommending Orthopedic Surgery Hospitals in a Metro Region,” Journal of
Medical Internet Research, November 2020.
T. Zhan, D. Goyal, J. Guttag, R. Mehta, Z. Elahi, Z. Syed, M. Saeed, “Machine Intelligence for Early Targeted Precision Management and Response to Outbreaks of Respiratory Infections, American Journal of Managed Care, October 2020.M. Makar, F. Johansson, J. Guttag, and D. Sontag, “Estimation of Utility-Maximizing Bounds on Potential Outcomes,” ICML 2020, July 2020.M. Rakic, J. Guttag, and A. Dalca, “Anatomical Predictions Using Subject-specific Medical Data,” Medical Imaging with Deep Learning (MIDL), July 2020.K. Lewis, J. Guttag, and A. Dalca, “Fast Learning-based Registration of Sparse 3D Clinical Images,” ACM Conference on Health, Inference, and Learning (CHIL), July 2020.
A.
Zhao, G. Balakrishnan, K. M. Lewis, F. Durand, J. Guttag, A.V. Dalca, “Painting
Many Pasts: Synthesizing Time Lapse Videos of Paintings,“ CVPR, June
2020.
D. Blalock, J.J.G. Ortiz, J. Frankel, and J. Guttag,
“What Is the State of Neural Network Pruning,” Machine Learning and Systems 2020,
March 2020.
A.V. Dalca, M. Rakic, M.R. Subuncu,
J. Guttag, “Learning Conditional Deformable Templates with Convolutional
Networks,” NeurIPS 2019, December 2019.
G. Balakrishan, A. Zhao, W. Freeman, F. Durand, J.
Guttag, and A. Dalca, “Visual
Deprojection: Probabilistic
Recovery of Collapsed Dimensions for Images and Videos,” ICCV 2019,
October 2019.
D. Shanmugam, D. Blalock, and J. Guttag, “Multiple Instance Learning for ECG Risk Stratification,” Machine Learning for Healthcare, August 2019.J.J.G Ortiz, D. Mehta, J. Van Stan, R.E., Hillman, J. Guttag, and M. Ghassemi, “Learning from Few Subjects with Large Amounts of Voice Monitoring Data,” Machine Learning for Healthcare, August 2019.A.V. Dalca, G. Balakrishnan, J. Guttag, and M. R. Sabuncu, “Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces,” Medical Image Analysis, July 2019.A. Soleimany, H. Suresh, J.Ortiz, D. Shanmugam, N. Gural, J. Guttag. and S. Bhatia, “Image Segmentation of Liver Stage Malaria Infection with Spatial Uncertainty Sampling,” ICML Workshop on Computational Biology, June 2019.A. Zhao, G. Balakrishnan, F. Durand, J. Guttag, and A. Dalca, “Data Augmentation Using Learned Transforms for One-shot Medical Image Segmentation,” CVPR 2019, June 2019.A. Nistala and J. Guttag, “Using Deep Learning to Understand Patterns of Player Movement in the NBA,” Sloan Sports Analytics Conference, March 2019.G. Balakrishnan, A. Zhao, M. R. Sabuncu, J. Guttag, and A. Dalca, “VoxelMorph: A Learning Framework for Deformable Medical Image Registration,” IEEE Transactions on Medical Imaging, January 2019.
J.P. Cortes,
V. Espinoza, M. Ghassemi, D. Mehta, J. Van Stan, R. Hillman, J. Guttag, and M. Zanartu, “Ambulatory Assessment of Phonotraumatic
Vocal Hyperfunction Using Glottal Airflow Measures Estimated from Neck-surface
Acceleration, PLOS One, January 2019.
D. Blalock, S. Madden, and J. Guttag, “Sprintz: Time Series Compression for the Internet of
Things,” ACM Journal on Interactive, Mobile, Wearable, and Ubiquitous
Technologies, September 2018.
J. Gong and J. Guttag, “Learning to Summarized
Electronic Health Records Using Cross-Modality Correspondences,” Machine Learning in Healthcare, August
2018.
A.V. Dalca, G. Balakrishnan, J. Guttag, and M. R. Sabuncu, “Unsupervised Learning for Fast Probabilistic
Diffeomorphic Registration,” MICCAI, September 2018.
H. Suresh, J. Gong, and J. Guttag, “Learning Tasks
for Multitask Learning: Heterogeneous Patient Populations in the ICU,” KDD
2018, August 2018.
G. Balakrishnan, A. Zhao, A.V. Dalca, F. Durand, and
J. Guttag, “Synthesizing Images of Humans in Unseen Poses,” CVPR: Conference
on Computer Vision and Pattern Recognition, June 2018.
G. Balakrishnan, A. Zhao, M. R. Sabuncu,
J. Guttag, and A.V. Dalca, “An Unsupervised Learning Model for Deformable
Medical Image Registration,” CVPR: Conference on Computer Vision and Pattern
Recognition, June 2018.
A.V. Dalca, J. Guttag, and M. R. Sabuncu,
“Anatomical Priors in Convolutional Networks for Unsupervised Biomedical
Segmentation, CVPR: Conference on Computer Vision and Pattern Recognition,
June 2018.
J.P. Cortes, V. Espinoza, M. Ghassemi, D. Mehta, J. Van Stan, R. Hillman, J. Guttag, and M. Zañartu,“Using Aerodynamic Features and Their Uncertainty for the Ambulatory Assessment of Phonotraumatic Vocal Hyperfunction,” IEEE International Conference on Biomedical and Health Informatics, March 2018.
J. Oh, M. Makar, C. Fusco, R. McCaffrey, K. Rao, E.
Ryan, L. Washer, L. West, V. Young, J. Guttag, D. Hooper, E. Shenoy, and J.
Wiens, “A generalizable, data-driven approach to predict daily risk of
Clostridium difficile infection at two large academic health centers,” Infection
Control & Hospital Epidemiology, April 2018.
M. Makar, J. Wiens, and J. Guttag, “Learning the Probability of
Activation in the Presence of Latent Spreaders,” AAAI, February 2018.
R. Jaroensri, A. Zhao, G. Balakrishnan, D.
Lo, J. Schmahmann, F. Durand, and J. Guttag, “A
Video-based Method for Automatically Rating Ataxia,” Machine Learning in Healthcare, August 2017.
D. Blalock and J. Guttag, “Bolt: Accelerated Data Mining with Fast
Vector Compression,” KDD 2017, August 2017.
J. Gong, T. Naumann, P. Szolovits, and J.
Guttag, “Predicting Clinical Outcomes Across Changing Electronic Health Record
Systems,” KDD 2017, August 2017.
D. Blalock and J. Guttag, “EXTRACT: Strong Examples from Weakly-labeled
Sensor Data,” ICDM 2016, December 2016.
J. Brooks, M. Kerr, and J. Guttag, “Developing a Data-driven Player
Ranking in Soccer Using Predictive Model Weights, KDD 2016, August 2016.
J. Gong, M. Gong, D. Levy-Lambert, J. Green, T. Hogan, and J. Guttag,
“Towards an Automated Screening Tool for Developmental Speech and Language
Impairments,” Interspeech 2016, September 2016.
M. Ghassemi, J. Hillman, D. Mehta, J. Van Stan, Z. Syed, and J. Guttag,
“Uncovering Voice Misuse Using Symbolic Mismatch,” Machine Learning in Healthcare, August 2016.
Y. Liu, C. Stultz, and J. Guttag, “Transferring Knowledge from Text to
Predict Disease Onset,” Machine Learning
in Healthcare, August 2016.
J. Brooks, M. Kerr, and J. Guttag, “Using Machine Learning to Draw
Inferences from Pass Location Data in Soccer,” Statistical Analysis and Data Mining, August 2016.
J. Wiens, J. Guttag, and E. Horvitz, “Patient Risk Stratification with
Time-varying Parameters: a Multitask Learning Approach, Journal of Machine Learning Research, 17(77), June 2016.
A. McIntyre, J. Brooks, J. Guttag, and J. Wiens, “Recognizing and
Analyzing Ball-screen Defense in the NBA,” Sloan Sports Analytics Conference,
March 2016.
J.P. Cortes, V. Espinoza, M. Zanartu, M. Ghassemi, J. Guttag, D. Mehta, J. Van Stan, and
R. Hillman, “Discriminating patients with vocal
fold nodules from matched controls using acoustic and aerodynamic features from
ambulatory voice monitoring data,” 10th International
Conference on Voice Physiology and Biomechanics, March 2016.
Balakrishnan, G., Durand, F., and Guttag, J., “Video Diff: Highlighting
Differences Between Similar Actions in Videos, SIGGRAPH Asia, November 2015.
Van Esbroeck, M. Saeed, B. Scirica, C. Stultz,
J. Guttag, S. Baveja, D. Morrow, and Z. Syed, “Looking beyond left ventricular
ejection fraction: investigating the utility of multi-factorial computational
modeling to predict sudden cardiac death following acute coronary syndrome in
the MERLIN-TIMI36 trial,” American Heart Association (AHA) Scientific Sessions,
November 2015.
Mehta, D. D., Van Stan, J. H., Zañartu, M.,
Ghassemi, M., Guttag, J. V., Espinoza, V. M., Cortés, J. P., Cheyne, H. A., and
Hillman, R. E., “Using ambulatory voice monitoring to investigate common voice
disorders: Research update,” Frontiers in
Bioengineering and Biotechnology, October 2015.
J. Gong, T. Sundt, J. Rawn, and J. Guttag, “Instance Weighting for Patient-specific Risk Stratification Models,” KDD 2015, August 2015.A. Singh, G. Nadkarni; O. Gottesman; S.B. Ellis; E.P. Bottinger; and J.V. Guttag, “Incorporating Temporal EHR data in Predictive Models for Risk Stratification of Renal Function Deterioration,” Journal of Biomedical Informatics, December 2014.
RE Hillman, D Mehta, JH Van Stan, M Zanartu,
M Ghassemi, JV Guttag, “Subglottal ambulatory monitoring of
vocal function to improve voice disorder assessment,” The Journal of the Acoustical Society of
America 136 (4), 2260-2260, October 2014.
A. Singh, G. Nadkarni, E. Bottinger, and J.V. Guttag, “Leveraging Hierarchy in Medical Codes for Predictive Modeling,” ACM Conference on Bioinformatics, Computational Biology and Health Informatics, Sept. 2014.G. Ganeshpapillai, J. Brooks, and J. Guttag, “Rapid Data Exploration and Visual Data Mining on Relational Data,” Proceedings of the KDD 2014 Workshop on Interactive Data Exploration and Analytics, August 2014.
J. Wiens, W. Campbell, E. Franklin, E. Horvitz, and J. Guttag, "Learning Data-Driven Patient Risk Stratification Models for Clostridium difficile," Open Forum Infectious Diseases, July 2014.M. Ghassemi, J. Van Stan, D. D. Mehta, M. Zañartu, H. A. Cheyne II, R. E. Hillman, and J. V. Guttag “Learning to detect vocal hyperfunction from ambulatory neck-skin acceleration features: Initial results for vocal fold nodules”, IEEE Trans. Biomed. Eng., Vol. 61(6), pp.1668-1675, June 2014.A. McQueen, J. Wiens, and J. Guttag, “Automatically Recognizing On-Ball Screens,” Sloan Sports Analytics Conference, March 2014.G. Ganeshpapillai and J. Guttag, “In-game Decision Making in MLB,” KDD 2013, Sloan Sports Analytics Conference, March 2014.
J. Wiens, E. Horvitz, and J. Guttag, “A Study in Transfer Learning: Leveraging Data from Multiple Hospitals to Enhance Hospital-Specific Predictions,” Journal of the American Medical Informatics Association, January 2014.G. Ganeshpapillai and J. Guttag, “A Data-driven Method for In-game Decision Making in MLB,” KDD 2013, August 2013.
R. E. Hillman, J. H. Van Stan, D. D. Mehta, M. Zañartu, M. Ghassemi, H. A. Cheyne II, J. V. Guttag, “Future directions in the development of ambulatory monitoring for clinical voice assessment,” Proceedings of the 10th International Conference on Advances in Quantitative Laryngology, Voice and Speech Research, Cincinnati, OH, June 2013G. Ganeshpapillai, A. Lo, and J. Guttag, “Learning Connections in Financial Time Series,” ICML 2013, June 2013.
G. Balakrishnan, F. Durand, and J. Guttag, “Detecting Pulse from Head Motion,” IEEE Conference on Computer Vision and Pattern Recognition, June 2013.J. Wiens, G. Balakrishnan, J. Brooks, and J. Guttag, “To Crash or Not to Crash, A Quantitative Look at the Relationship Between Offensive Rebounding and Transition Defense in the NBA,” MIT Sloan Sports Analytics Conference, March 2013.A. Singh and J.Guttag, “Collaborative Filtering for Identifying Prescription Omissions in an ICU,” BIOSIGNALS 2013, February 2013.J. Wiens, E. Horvitz, and J. Guttag, “Patient Risk Stratification for Hospital-Associated C. Diff as a Time-Series Classification Task,” NIPS 2012, December 2012.
M. Ghassemi, E. Shih, D. D.
Mehta, S. W. Feng, J. Van Stan, R. E. Hillman, and J. Guttag, “Detecting voice
modes for vocal hyperfunction prevention,” in Proceedings of the 7th Annual
Workshop for Women in Machine Learning/Neural Information Processing Systems
(NIPS) Conference, Lake Tahoe, NV, USA, 2012.
Hao-Yu Wu, Michael Rubinstein, Eugene Shih, John
Guttag, Fredo Durand, William T. Freeman Eulerian Video Magnification for
Revealing Subtle Changes in the World ACM Transactions on Graphics,
Volume 31, Number 4 (Proc. SIGGRAPH) 2012.
J. Wiens, E. Horvitz, and J. Guttag, “Learning
Evolving Patient Risk Processes for C. Diff Colonization, ICML 2012 Workshop on Clinical Data Analysis, June 2012.
G. Gartheeban and J.
Guttag, “Predicting the Next Pitch,” MIT Sloan Sports Analytics Conference,
March 2012. (Also in ESPN, The Magazine.)
A. Shoeb,
A. Kharbouch, J. Soegaard,
S. Schachter, and J. Guttag. “A Machine-Learning Algorithm for Detecting
Seizure Termination in Scalp EEG,” Epilepsy
and Behavior, December 2011.
A. Kharbouch, A. Shoeb, J.
Guttag, and S. Cash, “An Algorithm for Seizure Onset Detection Using
Intracranial EEG,” Epilepsy and Behavior, December 2011.
Z. Syed. C. Stultz, B. Scirica B, and J. Guttag, “Computationally generated
cardiac biomarkers for risk stratification following acute coronary syndrome,” Science Translational Medicine (Science/AAAS
Journal), September 2011.
A. Shoeb, T. Pang, J.
Guttag, and S. Schachter, “Vagus Nerve Stimulation
Triggered by Machine-Learning Based Seizure Detection: Initial Implementation
and Evaluation.” Epilepsy: The
Intersection of Neurosciences, Biology, Mathematics, Physics, and
Engineering. Editors: Osorio I,
Zaveri HP, Frei MG, Arthurs S, CRC
Press, 2011.
Shoeb,
A. Kharbouch, J. Soegaard,
S. Schachter, and J. Guttag. “An
Algorithm for detecting seizure termination in Scalp EEG.” 33rd International Conference of the IEEE Engineering in
Medicine and Biology (EMBS), September 2011.
J. Wiens and J. Guttag, “Patient-specific
Ventricular Beat Classification without Patient-specific Expert Knowledge: A
Transfer Learning Approach,” 33rd Annual International Conference of the
IEEE Engineering in Medicine and Biology Society (EMBC), August 2011.
G. Gartheeban and J.
Guttag, “Reconstruction of ECG Signals in The Presence of Corruption” 33rd
Annual International Conference of the IEEE Engineering in Medicine and Biology
Society (EMBC), August 2011.
A. Singh and J. Guttag, “A Comparison of Non-Symmetric Entropy-Based Classification Trees and
Support Vector Machine for Cardiovascular Risk Stratification,” 33rd
Annual International Conference of the IEEE Engineering in Medicine and Biology
Society (EMBC), August 2011.
Z. Syed and
J. Guttag, “Unsupervised similarity-based risk stratification for
cardiovascular events using long-term time-series data,” Journal of Machine Learning Research, 2011;12(3):999-1024.
J. Wiens and J. Guttag, “Active Learning
Applied to Patient-Adaptive Heartbeat Classification,” NIPS 2010, December
2010.
Z. Syed and J. Guttag, “Identifying
Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic
Mismatch,” NIPS 2010, December 2010.
Z. Syed, B. Scirica, S. Mohanavelu, D. Morrow, C. Stutz, and J. Guttag,
“Association of Heart Rate Turbulence, Deceleration Capacity, and Morphologic
Variability with Sudden Cardiac Death Following Non-ST-Elevation Acute Coronary
Syndrome: Results from the MERLIN-TIMI 36 Trial,” American Heart Association
Annual Meeting, November 2010.
A. Qureshi, I. Fan, J. Carlisle, D. Brezinski, M.
Kleinman, and J. Guttag, “Improving
Patient Care by Unshackling Telemedicine: Adaptively Constructing Rich Wireless
Communication Channels to Facilitate Continuous Remote Collaboration,” AMIA 2010
Annual Symposium, November 2010.
J. Wiens and J. Guttag, “Patient-Adaptive Ectopic Beat Classification using Active Learning,” Computing
in Cardiology 2010, September 2010.
A. Singh, J.
Liu, and J. Guttag, “Categorization of Continuous ECG Based Risk Metrics Using
Asymmetric and Warped Entropy Measures,” Computing in Cardiology 2010,
September 2010.
N. Verma, A. Shoeb, J. Bohorquez, J. Dawson, J. Guttag, and A.
Chandrakasan, "A Micro-power EEG Acquisition SoC with Integrated
Feature-Extraction Processor for a Chronic Seizure Detection System," IEEE Journal of Solid State Circuits,
Vol. 45(4), January 2010.
Z. Syed, C. Stultz, M.
Kellis, P. Indyk, and J. Guttag, “Motif Discovery in Physiological Datasets: A Methodology
for Inferring Predictive Elements,” ACM Transactions on Knowledge Discovery
in Data, January 2010.
Z. Syed, B, Scirica, C. Stultz, and J. Guttag, “Electrocardiographic prediction of arrhythmias,” Computers in Cardiology, September 2009.
Z. Syed, P. Indyk, and J. Guttag, “Learning Approximate
Sequential Patterns for Classification,” Journal
of Machine Learning Research, Vol. 10(9), August 2009.
A. Qureshi, H. Balakrishnan,
J. Guttag, B. Maggs, R. Weber, “Cutting the Electric Bill for Internet-Scale
Systems,” SIGCOMM 2009, (August 2009).
A. Shoeb, J. Guttag, T. Pang, and S. Schachter, “Non-invasive
Computerized System For Automatically Initiating Vagus
Nerve Stimulation Following Patient-Specific Detection of Seizures or
Epileptiform Discharges,” International Journal of
Neural (2009).
N. Verma, A. Shoeb, J. Guttag, and A. Chandrakasan, “A Micro-power EEG Acquisition SoC with Integrated Seizure
Detection Processor for Continuous Patient Monitoring,” 2009 Symposium on VLSI Circuits, June 2009.
E. Shih, A. Shoeb, and J. Guttag, “Building a Customized, Wearable,
Energy-Efficient Medical Event Detection System,” 7th
Annual International Conference on Mobile Systems, Applications and Services (MobiSys '09), June 2009.
P. Sung, Z. Syed, and J. Guttag, “Quantifying
Morphology Changes in Time Series Data with Skew,” 2009 International Conference on Acoustics, Speech,
and Signal Processing, April 2009.
Z. Syed, P. Sung, B.
Scirica, D. Morrow, C. Stultz, and J.
Guttag, “Spectral energy of ECG morphologic differences to predict
death,” Cardiovascular Engineering, Vol. 9, No. 1, March 2009.
Z. Syed, B. Scirica, D. Morrow, S. Mohanavelu,
C. Stultz, C., and J. Guttag, “ECG markers to predict cardiovascular death:
Heart rate variability, deceleration capacity and morphologic variability in
non-ST-elevation ACS from the MERLIN-TIMI 36 trial,” American Heart Association Scientific Sessions, November 2008.
A. Shoeb, S. Schachter, T. Pang and J. Guttag, “Implementation of Closed-Loop, EEG-Triggered Vagus Nerve Stimulation using Patient-Specific Seizure Onset Detection From Scalp EEG,” American Epilepsy Society 61st Annual, Meeting, December 2007.Z. Syed, C. Stultz, B. Scirica, C. Cannon, S. Mohanavelu, I. Stebsletova, K. Attia, and J. Guttag, “Morphological Variability: A New Electrocardiographic Technique for Risk Stratification After NSTEACS,” abstract, American Heart Association Annual Meeting, November 2007.
Ali Shoeb, Trudy Pang,
Steven C. Schachter, John Guttag, “Implementation of Closed-Loop, EEG-Triggered
Vagus Nerve Stimulation using Patient-Specific
Seizure Onset Detection From Scalp EEG,” Third
International Workshop on Epileptic Seizure Prediction, September 2007.
A. Shoeb, S. Schachter, B. Bourgeois, S.T. Treves, and J Guttag, “Impact of Patient-Specificity on Seizure Onset Detection Performance,” 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, August 2007.
Z. Syed and J. Guttag, “Prototypical Biological Signals,” 2007 International Conference on Acoustics, Speech, and Signal Processing, April 2007.
Z.
Syed, D. Curtis, D. Leeds, R. Levine, F. Nesta, and J. Guttag, “A Framework for
the Analysis of Acoustical Cardiac Signals,” IEEE Transactions on Biomedical Engineering, Vol. 54, no. 4, April
2007.
Z. Syed, J. Guttag, and C. Stoltz, “Clustering and Symbolic Analysis of Cardiovascular Signals: Discovery and Visualization of Medically Relevant Patterns in Long-Term Data with Limited Prior Knowledge,” EURASIP Journal on Applied Signal Processing, March 2007.
A.
Qureshi, J. Carlisle, and J. Guttag, “Tavarua: Video
Streaming with WWAN Striping,” ACM Multmedia 2006, October 2006.
E. Glassman and J. Guttag, “Reducing the Number of
Channels for an Ambulatory Patient-Specific EEG-based Epileptic Seizure
Detector by Applying Recursive Feature Elimination,” 28th Annual International Conference of the IEEE
Engineering in Medicine and Biology Society, August 2006.
Z. Syed, D. Curtis, F. Nesta, R.
Levine, and J. Guttag, “Software Enhanced Learning of Cardiac
Auscultation,” 28th Annual
International Conference of the IEEE Engineering in Medicine and Biology
Society, August 2006.
Z. Syed, D. Leeds, D. Curtis, F.
Nesta, R. Levine, and J. Guttag, “Audio-Visual Tools for
Computer-Assisted Diagnosis of Cardiac Disorders,” Computer Based Medical
Systems 2006, June 2006.
S. Schachter, A. Shoeb, B. Bourgeois, S.T. Treves,
and J. Guttag, “Feasibility of Detecting Seizure Onsets in Ambulatory Patients:
Initial Implementation,” American Epilepsy Society 59th Annual, Meeting,
December 2005.
A. Shoeb, S.
Schachter, B. Bourgeois, S.T. Treves, and J Guttag, “Automated Seizure Onset
Detection as a New Method of On-Demand VNS Stimulation: Initial Technical
Development and Findings,” American Epilepsy Society 59th Annual, Meeting,
December 2005.
A. Qureshi , A. Shoeb, and J. Guttag, “Building a
High-Quality Mobile Telemedicine System Using Network Striping over Dissimilar
Wireless Wide Area Networks,” 27th
Annual International Conference of the IEEE Engineering in Medicine and Biology
Society, September 2005.
A. Shoeb, S. Schachter , D. Schomer , B. Bourgeois ,
S. Treves , and J. Guttag , “Detecting Seizure Onset in the Ambulatory Setting:
Demonstrating Feasibility,” 27th
Annual International Conference of the IEEE Engineering in Medicine and Biology
Society, September 2005.
A. Qureshi and J. Guttag, “Horde: Separating Network
Striping Policy from Mechanism,” MobiSys 2005, June
2005.
J. Guttag (ed.), The Electron
and the Bit, EECS at MIT 1902-2002, May 2005.
G. Tan and J. Guttag, “'The 802.11 MAC Protocol
Leads to Inefficient Equilibria,” IEEE
INFOCOM 2005, March 2005.
A. Shoeb, B. Bourgeois; T.
Treves, and J. Guttag, "Patient-Specific Seizure Onset Detection to
Optimize Ictal SPECT,” American Epilepsy Society 58th Annual Meeting,
December 2004.
E. Shih, V. Bychkovsky, D.
Curtis, and J. Guttag, “Continuous, Remote Medical,” Abstract and
demonstration, Proceedings of the Second
Annual International Conference on Embedded Networked Sensor Systems,
November 2004.
A. Shoeb, H.
Edwards; J. Connolly; B. Bourgeois; T. Treves, and J. Guttag, “Patient-Specific
Epileptic Seizure Onset Detection,” 26th
Annual International Conference of the IEEE Engineering in Medicine and Biology
Society, September 2004.
G. Tan and J. Guttag, “Long-term Time-share
Guarantees are Necessary for WLANs,” 11th ACM SIGOPS European Workshop, September 2004.
A. Shoeb, H.
Edwards; J. Connolly; B. Bourgeois; T. Treves, and J. Guttag, “Patient-Specific
Seizure Onset Detection,” Epilepsy and
Behavior, August 2004.
G. Tan and J. Guttag, “Time-based Fairness Improves
Performance in Multi-rate WLANs,” 2004 USENIX Annual Technical Conference, June
2004.
G. Tan, M. Poletto, F. Kaashoek, and J. Guttag, “Role
Classification of Hosts within Enterprise Networks Based on Connection Patterns,”
2003 USENIX Annual Technical Conference, June 2003.
G. Tan and J. Guttag, “A Locally Coordinated
Scatternet Scheduling Algorithm,” 27th Annual IEEE Conference on
Local Computer Networks, November 2002.
G. Tan, A. Miu, J. Guttag, and H. Balakrishnan. “An Efficient Scatternet Formation Algorithm
for Dynamic Environments,” IASTED Communications and Computer
Networks (CCN), Cambridge, MA, November, 2002.
J. Guttag, “Abstract Data Types, Then and Now,” Software Pioneers, Contributions to Software Engineering, Springer-Verlag, (2002).
G. Tan, A. Miu, J. Guttag and H. Balakrishnan, Forming
Scatternets from Bluetooth Personal Area Networks, MIT-LCS-TR-826, October
2001.
<ui>D. Wetherall, V. Bose, and
J. Guttag, “RadioActive Networks: Freedom from the
Worst Case Design,” MobiCom, August 1999.
<ui>V. Bose, M. Ismert, M.
Welborn, J. Guttag, “Virtual Radios,” IEEE
Journal on Selected Areas in Communications, vol. 17, no. 4, April 1999.
D. Wetherall, J. Guttag, and D. Tennenhouse, “ANTS:
Network Services Without the Red Tape,” IEEE Computer, vol. 32, no. 4, April
1999.
U. Legedza and J. Guttag, “Using Network Level Support to Improve Cache Routing,” Computer Networks and ISDN Systems, vol. 20, no. 22-23, November 1998.
D. Bailey, R. Brooks, J. Guttag, and T. Unger, “The Year 2000 Crisis as a Management Liability Issue, A Practical Guide for Directors and Officers,” Prepared for Nation Union Fire Insurance Company, 1998.
D. Wetherall, U. Legedza, and J. Guttag, “Introducing New Internet Services: Why and How,” IEEE Network, July/August 1998.
U. Legedza and J. Guttag, “Using Network Level Support to Improve Cache Routing,” 3rd International WWW Caching Workshop, June 1998.
D. Wetherall, J. Guttag, and D. Tennenhouse, “ANTS: A Toolkit for Building and Dynamically Deploying Network Protocols,” IEEE OpenArch ’98, April 1998.
U. Legedza, D. Wetherall, and J. Guttag, “Improving
The Performance of Distributed Applications Using Active Networks,” IEEE INFOCOM ‘98, April 1998.
R. Stata and J. Guttag, “Modular Reasoning in the
Presence of Subclassing,” Object-Oriented
Programming Systems, Languages, and Applications (1995).
A. Agarwal, J. Guttag, C. Hadjicostis,
and M. Papaefthymiou, “Memory Assignment for Multiprocessor Caches through Grey
Coloring,” Parallel Architectures and
Languages Europe 1994, Springer-Verlag
Lecture Notes in Computer Science, (1994).
M. Vandevoorde and J. Guttag, “Using Specialized
Procedures and Specification-Based Analysis to Reduce the Runtime Costs of
Modularity, Proceedings of the ACM
SIGSOFT Symposium on the Foundations of Software Engineering , New Orleans,
LA (1994).
D. Evans, J. Guttag, J. Horning, and Y.M. Tan,
“LCLint, A Tool for Using Specifications to Check Code, Proceedings of the ACM SIGSOFT Symposium on the Foundations of Software
Engineering , New Orleans, LA (1994).
J.V. Guttag, “Goldilocks and the Three
Specifications,” Proc. Fourth
International Joint Conference on the Theory and Practice of Software
Development, Orsay, France (1993).
Stephen J. Garland, John V. Guttag, and James J.
Horning, "An overview of Larch," Functional Programming,
Concurrency, Simulation, and Automated Reasoning, Lecture Notes in Computer
Science 693, Peter E.
Lauer (editor), Springer-Verlag, 1993, pages 329-348.
J.V. Guttag, “A Brief Introduction to CLU,” Proc. History of Programming Languages
Conference, Cambridge, MA (1993).
Jørgen F. Søgaard-Andersen, Stephen J. Garland, John
V. Guttag, Nancy A. Lynch, and Anya Pogosyants,
"Computed-assisted simulation proofs," Computer-Aided
Verification, Fifth International Conference, CAV '93, Elounda, Greece,
June/July 1993, Lecture Notes in Computer Science 697,
Costas Courcoubetis (editor), Springer-Verlag, pages
305-319.
J.B. Saxe, S.J. Garland, J.V. Guttag, and J.J.
Horning, “Using Transformations and Verification in Circuit Design,”Formal Methods in System Design, Kluwer (1993). also in Proc. IFIP Workshop on Designing Correct
Circuits, Lyngby, Denmark, North-Holland (1992).
P. Penfield, J.V. Guttag, C.L. Searle, and W.M.
Siebert, “Shifting the Boundary: A Professional Master's Program for 2000 and
Beyond,” Proc. Frontiers in Education
Annual Conference (1992).
J. Staunstrup, S. J. Garland, and J. Guttag.
“Mechanized verification of circuit descriptions using the Larch Prover,” Proc. IFIP Work. Conf. Theorem Provers in
Circuit Design: Theory, Practice, and Experience, NijmegenNorth-Holland
(1992).
J.V. Guttag, “Why Programming is Too Hard and What
to Do About It,” Research Directions in
Computer Science, an MIT Perspective, MIT Press, Cambridge, MA (1991).
D.L. Clark, et
al., Computers at Risk: Safe
Computing in the Information Age, National Academy Press, Washington, D.C.
(1990).
Balzer et al.
“Prototyping,” Annual Review of Computer
Science, Vol. 4, 1989 - 1990, Annual Reviews, Palo Alto, CA (1990).
J. Staunstrup, S. J. Garland, and J. V. Guttag,
"Localized Verification of Circuit Descriptions,'' Proceedings of an International Workshop on Automatic Verification
Methods for Finite State Systems, Grenoble, France, June 1989, Lecture Notes in Computer Science 407,
Springer-Verlag (1989).
S. J. Garland and J. V. Guttag, "An Overview of
LP, the Larch Prover,'' Proceedings of
the Third International Conference on Rewriting Techniques and Applications,
Chapel Hill, NC, April 1989, Lecture
Notes in Computer Science 355, Springer-Verlag (1989).
S. J. Garland and J. V. Guttag, "Inductive
methods for reasoning about abstract data types,'' Proc. of the Fifteenth ACM Symposium on Principles of Programming
Languages, San Diego, CA (1988).
S. J. Garland and J. V. Guttag, "LP: The Larch
Prover,'' Proceedings of the Ninth
International Conference on Automated Deduction, Argonne, Illinois, Lecture Notes in Computer Science 310,
Springer-Verlag (1988).
S. J. Garland, J. V. Guttag, and J. Staunstrup,
"Verification of VLSI circuits using LP,'' The Fusion of Hardware Design and Verification, Proceedings of an IFIP
WG 10.2 Working Conference, Glasgow, Scotland North Holland (1988).
A.D. Birrell, J.V. Guttag, J.J. Horning, and R.
Levin, "Synchronization primitives for a multiprocessor: a formal
specification.'' Operating Systems Review
21(5), (1987).
B.L Liskov and J.V. Guttag, Abstraction and Specification in Program Development, MIT Press and
McGraw Hill (1986).
J.V. Guttag and J.J. Horning, "A Larch Shared
Language Handbook,'' Science of Computer
Programming 6 (1986).
J.V. Guttag and J.J. Horning, "Report on the
Larch Shared Language,'' Science of
Computer Programming 6 (1986).
J.V. Guttag, J.J. Horning, and J.M. Wing, "The
Larch Family of Specification Languages,'' IEEE Software 2(5) (1985).
R. Forgaard, J.V. Guttag,
“REVE: A Term Rewriting System Generator with a Failure-Resistant
Knuth-Bendix,” Proceedings of an NSF
Workshop on the Rewrite Rule Laboratory (1984).
J.V. Guttag, D. Kapur, and D.R. Musser, "On
Proving Uniform Termination and Restricted Termination of Rewriting Systems,''SIAM Journal of Computing, vol. 12, no. 1
(1983).
J.V. Guttag and J.J. Horning, "An Introduction
to the Larch Shared Language,'' Proc.
IFIP Ninth World Computer Congress, Paris, France (1983).
Guttag, J. V., "Notes on Using Types and Type
Abstraction in Functional Programming,'' Functional
Programming and its Applications, An Advanced Course, (eds. J. Darlington,
P. Henderson and D. A. Turner), North Holland (1982).
J.V. Guttag, D. Kapur, and D.R. Musser,
"Derived Pairs, Overlap Closures, and Rewrite Dominoes: New Tools for
Analyzing Term Rewriting Systems,''Proceedings of the
1982 ICALP Conference, Lecture Notes
in Computer Science 140, Springer-Verlag (1982).
J.V. Guttag, J.J. Horning, and J.M. Wing, “Some
Notes on Putting Formal Specifications to Productive Use,” Science of Computer Programming, vol. 2 (1982).
J.V. Guttag, J.J. Horning, and J. Williams, "FP
with Data Abstraction and Strong Typing,'' Proceedings
of a Conference on Functional Programming and Computer Architecture (1981).
J.V. Guttag and J.J. Horning, "Formal
Specification as a Design Tool,''Seventh ACM Symposium
Principles of Programming Languages, Las Vegas (1980).
J.V. Guttag, "Notes on Type Abstraction,
Version 2,''IEEE Transactions on Software
Engineering vol. SE-6, no. 1 (1980).
J.V. Guttag and J.J. Horning, "The Algebraic
Specification of Abstract Data Types,'' Acta
Informatica 10(1) (1978).
J.V. Guttag, E. Horowitz, and D.R. Musser,
"Abstract Data Types and Software Validation,'' Communications of the ACM, vol. 21, no. 12 (1978).
Ralph L. London, John V. Guttag, James J. Horning, Butler W. Lampson, James G. Mitchell, Gerald J. Popek: “Proof Rules for Euclid,” Program
Construction 1978: 133-163 (1978)
R.L. London, J.V. Guttag, J.J. Horning, B.W.
Lampson, J.G. Mitchell, and G.J. Popek, "Proof Rules for the Programming
Language Euclid,'' Acta Informatica,
vol. 10, no. 1 (1978).
J.V. Guttag, J.J. Horning, and R.L. London, "A
Proof Rule for Euclid Procedures,'' Proceedings
of IFIP Working Conference on Formal Description of Programming Concepts,
Saint Andrews, N. B. (1977).
J.V. Guttag, E. Horowitz, and D.R. Musser,
"Some Extensions to Algebraic Axioms,'' Proceedings of an ACM Conference on Language Design for Reliable
Software, Chapel Hill, NC (1977).
J.V. Guttag, "Abstract Data Types and the
Development of Data Structures,'' Communications
of the ACM, vol. 20, no. 6 (1977).
J.V. Guttag, E. Horowitz, and D.R. Musser, "The
Design of Data Type Specifications,'' Proceedings
Second International Conference on Software Engineering, San Francisco, CA
(1976).
J.V. Guttag, The
Specification and Application to Programming of Abstract Data Types, Ph.D.
Thesis, Dept. of Computer Science, University of Toronto (1975).