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Ankur Teredesai
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- affiliation: Rochester Institute of Technology, Henrietta, NY, USA
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2020 – today
- 2024
- [c75]Jodi Chiam, Aloysius Lim, Ankur Teredesai:
NudgeRank: Digital Algorithmic Nudging for Personalized Health. KDD 2024: 4873-4884 - [c74]Ankur Teredesai, Michael Zeller, Mohak Shah, Shenghua Bao, Wee Hyong Tok, Linsey Pang:
The 2nd International Workshop: From Innovation to Scale (I2S) - Successfully Build, Commercialize, and Scale AI Innovations. KDD 2024: 6739-6740 - [i10]Jodi Chiam, Aloysius Lim, Cheryl Nott, Nicholas M. Mark, Ankur Teredesai, Sunil Shinde:
Co-Pilot for Health: Personalized Algorithmic AI Nudging to Improve Health Outcomes. CoRR abs/2401.10816 (2024) - [i9]Jodi Chiam, Aloysius Lim, Ankur Teredesai:
NudgeRank: Digital Algorithmic Nudging for Personalized Health. CoRR abs/2407.20241 (2024) - 2023
- [j9]Alberto Arias Maestro, Oscar Sanjuán Martínez, Ankur Teredesai, Vicente García-Díaz:
Blockchain Based Cloud Management Architecture for Maximum Availability. Int. J. Interact. Multim. Artif. Intell. 8(1): 88 (2023) - [c73]Tucker Stewart, Katherine Stern, Grant E. O'Keefe, Ankur Teredesai, Juhua Hu:
NPRL: Nightly Profile Representation Learning for Early Sepsis Onset Prediction in ICU Trauma Patients. IEEE Big Data 2023: 1843-1852 - [c72]Ankur Teredesai, Michael Zeller, Shenghua Bao, Wee Hyong Tok, Linsey Pang:
From Innovation to Scale (I2S) - Discuss and Learn How to Successfully Build, Commercialize, and Scale AI Innovations in Challenging Market Conditions. KDD 2023: 5888-5889 - [c71]Ankur Teredesai:
Social Public Health Infrastructure for a Smart City Citizen Patient: Advances and Opportunities for AI Driven Disruptive Innovation. WSDM 2023: 1297-1298 - [i8]Kevin Ewig, Xiangwen Lin, Tucker Stewart, Katherine Stern, Grant E. O'Keefe, Ankur Teredesai, Juhua Hu:
Multi-Subset Approach to Early Sepsis Prediction. CoRR abs/2304.06384 (2023) - [i7]Tucker Stewart, Katherine Stern, Grant E. O'Keefe, Ankur Teredesai, Juhua Hu:
NPRL: Nightly Profile Representation Learning for Early Sepsis Onset Prediction in ICU Trauma Patients. CoRR abs/2304.12737 (2023) - 2022
- [c70]Ankur Teredesai, Sijin Huang, Tucker Stewart, Juhua Hu, Armaan Thakker, Katherine Stern, Grant E. O'Keefe:
Sub-Sequence Graph Representation Learning on High Variability Data for Dynamic Risk Prediction in Critical Care. IEEE Big Data 2022: 2082-2092 - 2021
- [c69]Christine Allen, Juhua Hu, Vikas Kumar, Muhammad Aurangzeb Ahmad, Ankur Teredesai:
Interpretable Phenotyping for Electronic Health Records. ICHI 2021: 161-170 - [c68]Muhammad Aurangzeb Ahmad, Eduardo Trujillo-Rivera, Pollack M. D. Murray, Eckert M. D. Carly, Patel M. D. Anita, Ankur Teredesai:
Machine Learning Approaches for Patient State Prediction in Pediatric ICUs. ICHI 2021: 422-426 - [c67]Muhammad Aurangzeb Ahmad, Barrett Larson, Steve Overman, Vikas Kumar, Jing Xie, Alan Rossington, Ankur Patel, Ankur Teredesai:
Machine Learning Approaches for Pressure Injury Prediction. ICHI 2021: 427-431 - [c66]Muhammad Aurangzeb Ahmad, Carly Eckert, Christine Allen, Vikas Kumar, Juhua Hu, Ankur Teredesai:
Fairness in Healthcare AI. ICHI 2021: 554-555 - [c65]Muhammad Aurangzeb Ahmad, Steve Overman, Christine Allen, Vikas Kumar, Ankur Teredesai, Carly Eckert:
Software as a Medical Device: Regulating AI in Healthcare via Responsible AI. KDD 2021: 4023-4024 - [i6]Karthik K. Padthe, Vikas Kumar, Carly M. Eckert, Nicholas M. Mark, Anam Zahid, Muhammad Aurangzeb Ahmad, Ankur Teredesai:
Emergency Department Optimization and Load Prediction in Hospitals. CoRR abs/2102.03672 (2021) - [i5]Ming Yuan, Vikas Kumar, Muhammad Aurangzeb Ahmad, Ankur Teredesai:
Assessing Fairness in Classification Parity of Machine Learning Models in Healthcare. CoRR abs/2102.03717 (2021) - [i4]Aloysius Lim, Ashish Singh, Jody Chiam, Carly Eckert, Vikas Kumar, Muhammad Aurangzeb Ahmad, Ankur Teredesai:
Machine Learning Approaches for Type 2 Diabetes Prediction and Care Management. CoRR abs/2104.07820 (2021) - 2020
- [c64]Karthik K. Padthe, Vikas Kumar, Carly M. Eckert, Nicholas M. Mark, Anam Zahid, Muhammad Aurangzeb Ahmad, Ankur Teredesai:
Emergency Department Optimization and Load Prediction in Hospitals. AI4SG@AAAI Fall Symposium 2020 - [c63]Ming Yuan, Muhammad Ahmad, Vikas Kumar, Ankur Teredesai:
Assessing Fairness in Classification Parity of Machine Learning Models in Healthcare. AI4SG@AAAI Fall Symposium 2020 - [c62]Muhammad Aurangzeb Ahmad, Ankur Teredesai, Carly Eckert:
Fairness, accountability, transparency in AI at scale: lessons from national programs. FAT* 2020: 690 - [c61]Muhammad Aurangzeb Ahmad, Arpit Patel, Carly Eckert, Vikas Kumar, Ankur Teredesai:
Fairness in Machine Learning for Healthcare. KDD 2020: 3529-3530 - [i3]Boris Kovalerchuk, Muhammad Aurangzeb Ahmad, Ankur Teredesai:
Survey of explainable machine learning with visual and granular methods beyond quasi-explanations. CoRR abs/2009.10221 (2020)
2010 – 2019
- 2019
- [j8]Carly Eckert, Neris Nieves-Robbins, Elena Spieker, Tom Louwers, David Hazel, James Marquardt, Keith Solveson, Anam Zahid, Muhammad Ahmad, Richard Barnhill, T. Greg McKelvey, Robert Marshall, Eric A. Shry, Ankur Teredesai:
Development and Prospective Validation of a Machine Learning-Based Risk of Readmission Model in a Large Military Hospital. Appl. Clin. Inform. 10(02): 316-325 (2019) - [j7]Abdeltawab M. Hendawi, Jayant Gupta, Jiayi Liu, Ankur Teredesai, Naveen Ramakrishnan, Mohak Shah, Shaker H. Ali El-Sappagh, Kyung-Sup Kwak, Mohamed H. Ali:
Benchmarking large-scale data management for Internet of Things. J. Supercomput. 75(12): 8207-8230 (2019) - [c60]Muhammad Aurangzeb Ahmad, Carly Eckert, Ankur Teredesai:
The Challenge of Imputation in Explainable Artificial Intelligence Models. AISafety@IJCAI 2019 - [e1]Ankur Teredesai, Vipin Kumar, Ying Li, Rómer Rosales, Evimaria Terzi, George Karypis:
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019. ACM 2019, ISBN 978-1-4503-6201-6 [contents] - [i2]Muhammad Aurangzeb Ahmad, Carly Eckert, Ankur Teredesai:
The Challenge of Imputation in Explainable Artificial Intelligence Models. CoRR abs/1907.12669 (2019) - 2018
- [c59]Muhammad A. Ahmad, Carly Eckert, Greg McKelvey, Kiyana Zolfaghar, Anam Zahid, Ankur Teredesai:
Death vs. Data Science: Predicting End of Life. AAAI 2018: 7719-7726 - [c58]Muhammad Aurangzeb Ahmad, Carly Eckert, Ankur Teredesai:
Interpretable Machine Learning in Healthcare. BCB 2018: 559-560 - [c57]Abdeltawab M. Hendawi, Jayant Gupta, Jiayi Liu, Ankur Teredesai, Naveen Ramakrishnan, Mohak Shah, Mohamed H. Ali:
Distributed NoSQL Data Stores: Performance Analysis and a Case Study. IEEE BigData 2018: 1937-1944 - [c56]Kyle Fritchman, Keerthanaa Saminathan, Rafael Dowsley, Tyler Hughes, Martine De Cock, Anderson C. A. Nascimento, Ankur Teredesai:
Privacy-Preserving Scoring of Tree Ensembles: A Novel Framework for AI in Healthcare. IEEE BigData 2018: 2413-2422 - [c55]Muhammad Aurangzeb Ahmad, Ankur Teredesai, Carly Eckert:
Interpretable Machine Learning in Healthcare. ICHI 2018: 447 - 2017
- [c54]Jianle Chen, Tianqi Xiao, Jie Sheng, Ankur Teredesai:
Gender prediction on a real life blog data set using LSI and KNN. CCWC 2017: 1-6 - [c53]Qiaozhi Li, Jie Sheng, Ankur Teredesai:
Kernel based principal axis tree. CCWC 2017: 1-4 - [c52]Abdeltawab M. Hendawi, Aqeel Rustum, Amr A. Ahmadain, David Hazel, Ankur Teredesai, Dev Oliver, Mohamed H. Ali, John A. Stankovic:
Smart Personalized Routing for Smart Cities. ICDE 2017: 1295-1306 - 2016
- [c51]Shanu Sushmita, Garima Khulbe, Aftab Hasan, Stacey Newman, Padmashree Ravindra, Senjuti Basu Roy, Martine De Cock, Ankur Teredesai:
Predicting 30-Day Risk and Cost of "All-Cause" Hospital Readmissions. AAAI Workshop: Expanding the Boundaries of Health Informatics Using AI 2016 - [c50]Chun Pan Hon, Mayana Pereira, Shanu Sushmita, Ankur Teredesai, Martine De Cock:
Risk Stratification for Hospital Readmission of Heart Failure Patients: A Machine Learning Approach. BCB 2016: 491-492 - [c49]Abdeltawab M. Hendawi, Aqeel Rustum, Amr A. Ahmadain, Dev Oliver, David Hazel, Ankur Teredesai, Mohamed H. Ali:
Dynamic and Personalized Routing in PreGo. MDM 2016: 357-360 - 2015
- [j6]Sergio Davalos, Altaf Merchant, Gregory M. Rose, Brenton Lessley, Ankur Teredesai:
'The good old days': An examination of nostalgia in Facebook posts. Int. J. Hum. Comput. Stud. 83: 83-93 (2015) - [c48]Abdelrahman Elogeel, Andrey Kolobov, Matthew Alden, Ankur Teredesai:
Selecting Robust Strategies in RTS Games via Concurrent Plan Augmentation. AAMAS 2015: 155-162 - [c47]Golnoosh Farnadi, Zeinab Mahdavifar, Ivan Keller, Jacob Nelson, Ankur Teredesai, Marie-Francine Moens, Martine De Cock:
Scalable adaptive label propagation in Grappa. IEEE BigData 2015: 1485-1491 - [c46]Shanu Sushmita, Stacey Newman, James Marquardt, Prabhu Ram, Viren Prasad, Martine De Cock, Ankur Teredesai:
Population Cost Prediction on Public Healthcare Datasets. Digital Health 2015: 87-94 - [c45]Sarah Vluymans, Yvan Saeys, Chris Cornelis, Ankur Teredesai, Martine De Cock:
Fuzzy Rough Set Prototype Selection for Regression. FUZZ-IEEE 2015: 1-8 - [c44]Senjuti Basu Roy, Ankur Teredesai, Kiyana Zolfaghar, Rui Liu, David Hazel, Stacey Newman, Albert Marinez:
Dynamic Hierarchical Classification for Patient Risk-of-Readmission. KDD 2015: 1691-1700 - [c43]Abdeltawab M. Hendawi, Amruta Khot, Aqeel Rustum, Anas Basalamah, Ankur Teredesai, Mohamed H. Ali:
COMA: Road Network Compression for Map-Matching. MDM (1) 2015: 104-109 - [c42]Abdeltawab M. Hendawi, Amruta Khot, Aqeel Rustum, Anas Basalamah, Ankur Teredesai, Mohamed H. Ali:
A Map-Matching Aware Framework for Road Network Compression. MDM (1) 2015: 307-310 - [c41]Sarah Vluymans, Hasan Asfoor, Yvan Saeys, Chris Cornelis, Matthew E. Tolentino, Ankur Teredesai, Martine De Cock:
Distributed fuzzy rough prototype selection for Big Data regression. NAFIPS/WConSC 2015: 1-6 - 2014
- [c40]Ji Zhang, Jie Sheng, Ankur Teredesai:
Visual Tracking via Supervised Similarity Matching. ACCV (5) 2014: 146-161 - [c39]Si-Chi Chin, Rui Liu, Ankur Teredesai:
Cohort-Based Discretization of Continuous Clinical Features to Discover Readmission Risk Factors for Heart Failure Patients. AMIA 2014 - [c38]Aniruddha Desai, Muaz Mian, David Hazel, Ankur Teredesai, Gregory Benner:
Data Visualization in Educational Datasets Using a Rule-Based Inference System. BigData Congress 2014: 462-469 - [c37]Muaz Mian, Ankur Teredesai, David Hazel, Sreenivasulu Pokuri, Krishna Uppala:
Work in Progress - In-Memory Analysis for Healthcare Big Data. BigData Congress 2014: 778-779 - [c36]Hasan Asfoor, Rajagopalan Srinivasan, Gayathri Vasudevan, Nele Verbiest, Chris Cornelis, Matthew E. Tolentino, Ankur Teredesai, Martine De Cock:
Computing fuzzy rough approximations in large scale information systems. IEEE BigData 2014: 9-16 - [c35]Si-Chi Chin, Kiyana Zolfaghar, Senjuti Basu Roy, Ankur Teredesai, Paul Amoroso:
Divide-n-Discover - Discretization based Data Exploration Framework for Healthcare Analytics. HEALTHINF 2014: 329-333 - [c34]James Marquardt, Golnoosh Farnadi, Gayathri Vasudevan, Marie-Francine Moens, Sergio Davalos, Ankur Teredesai, Martine De Cock:
Age and Gender Identification in Social Media. CLEF (Working Notes) 2014: 1129-1136 - [c33]Amruta Khot, Abdeltawab M. Hendawi, Anderson C. A. Nascimento, Raj S. Katti, Ankur Teredesai, Mohamed H. Ali:
Road network compression techniques in spatiotemporal embedded systems: a survey. IWGS 2014: 33-36 - [c32]YiRu Li, Sarah George, Craig Apfelbeck, Abdeltawab M. Hendawi, David Hazel, Ankur Teredesai, Mohamed H. Ali:
Routing service with real world severe weather. SIGSPATIAL/GIS 2014: 585-588 - [c31]Lim-Kwan Kong, Jie Sheng, Ankur Teredesai:
Basic Micro-Aerial Vehicles (MAVs) obstacles avoidance using monocular computer vision. ICARCV 2014: 1051-1056 - [c30]Rui Liu, Kiyana Zolfaghar, Si-Chi Chin, Senjuti Basu Roy, Ankur Teredesai:
A Framework to Recommend Interventions for 30-Day Heart Failure Readmission Risk. ICDM 2014: 911-916 - [c29]James Marquardt, Stacey Newman, Deepa Hattarki, Rajagopalan Srinivasan, Shanu Sushmita, Prabhu Ram, Viren Prasad, David Hazel, Archana Ramesh, Martine De Cock, Ankur Teredesai:
HealthSCOPE: An Interactive Distributed Data Mining Framework for Scalable Prediction of Healthcare Costs. ICDM Workshops 2014: 1227-1230 - [c28]Yuqing Zhu, Yiwei Jiang, Weili Wu, Ling Ding, Ankur Teredesai, Deying Li, Wonjun Lee:
Minimizing makespan and total completion time in MapReduce-like systems. INFOCOM 2014: 2166-2174 - [c27]Yitao Li, Ling Ding, Jie Sheng, Cong Liu, Ankur Teredesai:
An Effective Message Forwarding Algorithm for Delay Tolerant Network with Cyclic Probabilistic Influences. MSN 2014: 179-185 - [p1]Nele Verbiest, Karel Vermeulen, Ankur Teredesai:
Evaluation of Classification Methods. Data Classification: Algorithms and Applications 2014: 633-656 - 2013
- [c26]Archana Ramesh, Ankur Teredesai, Ashish Bindra, Sreenivasulu Pokuri, Krishna Uppala:
Audience segment expansion using distributed in-database k-means clustering. AdKDD@KDD 2013: 5:1-5:9 - [c25]Kiyana Zolfaghar, Naren Meadem, Ankur Teredesai, Senjuti Basu Roy, Si-Chi Chin, Brian Muckian:
Big data solutions for predicting risk-of-readmission for congestive heart failure patients. IEEE BigData 2013: 64-71 - [c24]Robert L. Walter, Sergey Berezin, Ankur Teredesai:
ChronoZoom: travel through time for education, exploration, and information technology research. RIIT 2013: 31-36 - [i1]Kiyana Zolfaghar, Nele Verbiest, Jayshree Agarwal, Naren Meadem, Si-Chi Chin, Senjuti Basu Roy, Ankur Teredesai, David Hazel, Paul Amoroso, Lester Reed:
Predicting Risk-of-Readmission for Congestive Heart Failure Patients: A Multi-Layer Approach. CoRR abs/1306.2094 (2013) - 2012
- [c23]Junqing Shang, Eric P. Pepin, Eric Johnson, David Hazel, Ankur Teredesai, Alan Kristal, Alexander V. Mamishev:
Dietary intake assessment using integrated sensors and software. Multimedia on Mobile Devices / Multimedia Content Access: Algorithms and Systems 2012: 830403 - [c22]Mohamed H. Ali, John Krumm, Travis Rautman, Ankur Teredesai:
ACM SIGSPATIAL GIS Cup 2012. SIGSPATIAL/GIS 2012: 597-600 - [c21]Ashish Bindra, Srinivasulu Pokuri, Krishna Uppala, Ankur Teredesai:
Distributed Big Advertiser Data Mining. ICDM Workshops 2012: 914 - 2011
- [j5]Patricia Victor, Chris Cornelis, Martine De Cock, Ankur Teredesai:
Trust- and Distrust-Based Recommendations for Controversial Reviews. IEEE Intell. Syst. 26(1): 48-55 (2011) - [c20]Junqing Shang, Kishore Sundara-Rajan, Levi Lindsey, Alexander V. Mamishev, Eric Johnson, Ankur Teredesai, Alan Kristal:
A pervasive Dietary Data Recording System. PerCom Workshops 2011: 307-309 - [c19]Jeremiah Miller, Miles Raymond, Josh Archer, Seid Adem, Leo Hansel, Sushma Konda, Malik Luti, Yao Zhao, Ankur Teredesai, Mohamed H. Ali:
An Extensibility Approach for Spatio-temporal Stream Processing Using Microsoft StreamInsight. SSTD 2011: 496-501 - 2010
- [c18]Michael Munsey, Jonathan Veilleux, Sindhura Bikkani, Ankur Teredesai, Martine De Cock:
Born to trade: A genetically evolved keyword bidder for sponsored search. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c17]Rinkesh Nagmoti, Ankur Teredesai, Martine De Cock:
Ranking Approaches for Microblog Search. Web Intelligence 2010: 153-157
2000 – 2009
- 2009
- [c16]Ashish Bindra, Ankur Teredesai, Mohamed H. Ali, Walid G. Aref:
Multi-dimensional phenomenon-aware stream query processing. GIS 2009: 476-479 - [c15]Patricia Victor, Chris Cornelis, Martine De Cock, Ankur Teredesai:
A Comparative Analysis of Trust-Enhanced Recommenders for Controversial Items. ICWSM 2009 - [c14]David Thaler, Ankur Teredesai:
Maximizing Ridesharing Matches for Dynamic Carpooling. Intelligent Environments 2009: 489-492 - 2008
- [j4]Patricia Victor, Chris Cornelis, Martine De Cock, Ankur Teredesai:
Key figure impact in trust-enhanced recommender systems. AI Commun. 21(2-3): 127-143 (2008) - [c13]Patricia Victor, Chris Cornelis, Ankur Teredesai, Martine De Cock:
Whom should I trust?: the impact of key figures on cold start recommendations. SAC 2008: 2014-2018 - 2007
- [j3]Fei Hu, Ankur Teredesai:
A Pervasive Computing Curriculum for Engineering and Science Students. IEEE Pervasive Comput. 6(1): 88-91 (2007) - 2006
- [j2]Ankur Teredesai, Muhammad A. Ahmad, Juveria Kanodia, Roger S. Gaborski:
CoMMA: a framework for integrated multimedia mining using multi-relational associations. Knowl. Inf. Syst. 10(2): 135-162 (2006) - [c12]Muhammad A. Ahmad, Ankur Teredesai:
Modeling Proliferation of Ideas in Online Social Networks. AusDM 2006: 185-190 - [c11]Jason B. Peltzer, Ankur Teredesai, Garrett Reinard:
AQUAGP: Approximate QUery Answers Using Genetic Programming. EuroGP 2006: 49-60 - [c10]Ankur Teredesai, Yuanfeng Zhu:
SoNEA: Sensing Online Novelty Using Event Archives. MASS 2006: 616-621 - 2005
- [j1]Ankur Teredesai, Venugopal Govindaraju:
GP-based secondary classifiers. Pattern Recognit. 38(4): 505-512 (2005) - [c9]Derek M. Johnson, Ankur Teredesai, Robert T. Saltarelli:
Genetic Programming in Wireless Sensor Networks. EuroGP 2005: 96-107 - [c8]Muhammad A. Ahmad, Ankur Teredesai:
Domain Independent Integrated Multimedia Data Mining is a Frivolous Exercise: Classicism vs. Connectionism Debate Revisited. Wissensmanagement 2005: 587-594 - 2004
- [c7]Ankur Teredesai, Venu Govindaraju:
Issues in evolving GP based classifiers for a pattern recognition task. IEEE Congress on Evolutionary Computation 2004: 509-515 - [c6]Roger S. Gaborski, Vishal S. Vaingankar, Vineet Chaoji, Ankur Teredesai:
VENUS: A System for Novelty Detection in Video Streams with Learning. FLAIRS 2004: 232-238 - [c5]Roger S. Gaborski, Vishal S. Vaingankar, Vineet Chaoji, Ankur Teredesai, Aleksey Tentler:
Detection of inconsistent regions in video streams. Human Vision and Electronic Imaging 2004: 202-210 - 2002
- [c4]Ankur Teredesai, Eugene H. Ratzlaff, Jayashree Subrahmonia, Venu Govindaraju:
On-Line Digit Recognition Using Off-Line Features. ICVGIP 2002 - 2001
- [c3]Venu Govindaraju, Zhixin Shi, Ankur Teredesai:
Secondary classification using key features. Document Recognition and Retrieval 2001: 272-279 - [c2]Ankur Teredesai, Jaehwa Park, Venu Govindaraju:
Active Handwritten Character Recognition Using Genetic Programming. EuroGP 2001: 371-380 - [c1]Ankur Teredesai, Venu Govindaraju:
Active Digit Classifiers: A Separability Optimization Approach to Emulate Cognition. ICDAR 2001: 401-405
Coauthor Index
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