Qi Yu Headshot

Qi Yu

Professor

School of Information
Golisano College of Computing and Information Sciences
Graduate Program Director
qi.yu@rit.edu
585-475-6929
Office Hours
No teaching for this semester.
Office Location
GOL-2113

Qi Yu

Professor

School of Information
Golisano College of Computing and Information Sciences
Graduate Program Director

Education

BE, Zhejiang University (China); MS, National University of Singapore (Singapore); Ph.D., Virginia Polytechnic Institute and State University

qi.yu@rit.edu
585-475-6929
Personal Links
Personal Website
Google Scholar
Areas of Expertise
Artificial Intelligence
Data Science
Health Informatics
Machine Learning

Select Scholarship

Published Conference Proceedings
Zheng, Ervine, et al. "Knowledge Acquisition for Human-In-The-Loop Image Captioning." Proceedings of the AISTATS. Ed. None. Valencia, Spain: n.p., 2023. Web.
Li, Jintang, et al. "Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks." Proceedings of the AAAI. Ed. None. Washington, DC, USA: n.p., 2023. Web.
Zheng, Ervine, Qi Yu, and Zhi Zheng. "Sparse Maximum Margin Learning from Multimodal Human Behavioral Patterns." Proceedings of the AAAI. Ed. None. Washington, DC, USA: n.p., 2023. Web.
Pandey, Deep Shankar and Qi Yu. "Evidential Conditional Neural Processes." Proceedings of the AAAI. Ed. None. Washington, DC, USA: n.p., 2023. Web.
Yu, Dayou, Weishi Shi, and Qi Yu. "STARS: Spatial-Temporal Active Re-sampling for Label-Efficient Learning from Noisy Annotations." Proceedings of the AAAI. Ed. None. Washington, DC, USA: n.p., 2023. Web.
Sapkota, Hitesh and Qi Yu. "Adaptive Robust Evidential Optimization For Open Set Detection from Imbalanced Data." Proceedings of the ICLR. Ed. None. Kigali, Rwanda: n.p., 2023. Web.
Wang, Dingrong, et al. "Deep Temporal Sets with Evidential Reinforced Attentions for Unique Behavioral Pattern Discovery." Proceedings of the ICML. Ed. None. Honolulu, Hawaii: n.p., 2023. Web.
Yu, Dayou, Weishi Shi, and Qi Yu. "Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning." Proceedings of the ICML. Ed. None. Honolulu, Hawaii: n.p., 2023. Web.
Pandey, Deep Shankar and Qi Yu. "Learn to Accumulate Evidence from All Training Samples: Theory and Practice." Proceedings of the ICML. Ed. None. Honolulu, Hawaii: n.p., 2023. Web.
Zheng, Ervine and Qi Yu. "Evidential Interactive Learning for Medical Image Captioning." Proceedings of the ICML. Ed. None. Honolulu, Hawaii: n.p., 2023. Web.
Sapkota, Hitesh, et al. "Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training." Proceedings of the NeurIPS. Ed. None. New Orleans, LA: n.p., 2023. Web.
Yu, Dayou, Weishi Shi, and Qi Yu. "Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice." Proceedings of the NeurIPS. Ed. None. New Orleans, LA: n.p., 2023. Web.
Neupane, Krishna Prasad, et al. "A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations." Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022. Ed. Vasant Honavar and Matthijs Spaan. Virtual, None: n.p., 2022. Print.
Zheng, Ervine, et al. "Dual-Level Adaptive Information Filtering for Interactive Image Segmentation." Proceedings of the AISTATS. Ed. None. Virtual, None: n.p., 2022. Print.
Bao, Wentao, Yu Kong, and Qi Yu. "OpenTAL: Towards Open Set Temporal Action Localization." Proceedings of the CVPR. Ed. None. New Orleans, LA: n.p., 2022. Print.
Sapkota, Hitesh and Qi Yu. "Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection." Proceedings of the CVPR. Ed. None. New Orleans, LA: n.p., 2022. Print.
Pandey, Deep Shankar and Qi Yu. "Multidimensional Belief Quantification for Label-Efficient Meta-Learning." Proceedings of the CVPR. Ed. None. New Orleans, LA: n.p., 2022. Print.
Zhu, Yuansheng, Wentao Bao, and Qi Yu. "Towards Open Set Video Anomaly Detection." Proceedings of the ECCV. Ed. None. Tel Aviv, Israel: n.p., 2022. Print.
Deshpande, Niranjana, et al. "Online Learning Using Incomplete Execution Data for Self-Adaptive Service-Oriented Systems." Proceedings of the ICWS. Ed. None. Barcelona, Spain: n.p., 2022. Print.
Zhu,, Zulun, et al. "Spiking Graph Convolutional Networks." Proceedings of the IJCAI. Ed. None. Vienna, Austria: n.p., 2022. Print.
Alshangiti, Moayad, et al. "Hierarchical Bayesian multi-kernel learning for integrated classification and summarization of app reviews." Proceedings of the ESEC/SIGSOFT FSE. Ed. None. Singapore, Singapore: n.p., 2022. Print.
Sapkota, Hitesh and Qi Yu. "Balancing Bias and Variance for Active Weakly Supervised Learning." Proceedings of the KDD. Ed. None. Washington, DC: n.p., 2022. Print.
Zheng, E, et al. "A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation." Proceedings of the Proceedings of the AAAI Conference on Artificial Intelligence. Ed. None. Virtual, None: AAAI, 2021. Web.
Bao, Wentao, Qi Yu, and Yu Kong. "Evidential deep learning for open set action recognition." Proceedings of the Proceedings of the IEEE/CVF International Conference on Computer Vision. Ed. None. Virtual, None: IEEE, 2021. Web.
Bao, Wentao, Qi Yu, and Yu Kong. "DRIVE: Deep reinforced accident anticipation with visual explanation." Proceedings of the Proceedings of the IEEE/CVF International Conference on Computer Vision. Ed. None. None, Virtual: n.p., 2021. Web.
Deshpande, Niranjana, et al. "R-CASS: Using Algorithm Selection for Self-Adaptive Service Oriented Systems." Proceedings of the 2021 IEEE International Conference on Web Services (ICWS). Ed. None. Virtual, Virtual: IEEE, 2021. Web.
Zhu, Yuansheng, et al. "Uncertainty-Aware Multiple Instance Learning from Large-Scale Long Time Series Data." Proceedings of the IEEE BigDat. Ed. None. Virtual, Virtual: IEEE, 2021. Web.
Neupane, Krishna, Ervine Zheng, and Qi Yu. "MetaEDL: Meta Evidential Learning For Uncertainty-Aware Cold-Start Recommendations." Proceedings of the ICDM. Ed. None. Virtual, Virtual: IEEE, 2021. Web.
Wang, Dingrong, et al. "Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval." Proceedings of the ICDM. Ed. None. Virtual, Virtual: IEEE, 2021. Web.
Sapkota, Hitesh, et al. "Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning." Proceedings of the AISTATS. Ed. None. Virtual, Virtual: n.p., 2021. Web.
Shi, Weishi and Qi Yu. "Active Learning with Maximum Margin Sparse Gaussian Processes." Proceedings of the AISTATS. Ed. None. Virtual, Virtual: n.p., 2021. Web.
Shi, Weishi, Dayou Yu, and Qi Yu. "A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning." Proceedings of the Advances in Neural Information Processing Systems. Ed. None. Virtual, Virtual: n.p., 2021. Web.
Kang, Jai W., et al. "Analytics Prevalent Undergraduate IT Program." Proceedings of the SIGITE. Ed. Deepak Khazanchi. virtual, virtual: ACM, Web.
El-Glaly,, Yasmine N., et al. "Presenting and Evaluating the Impact of Experiential Learning in Computing Accessibility Education." Proceedings of the ICSE (SEET). Ed. Gregg Rothermel. virtual, virtual: IEEE, Web.
Shi, Weishi, et al. "Experiential Learning in Computing Accessibility Education." Proceedings of the ICSE (Companion Volume). Ed. Gregg Rothermel. virtual, virtual: IEEE, 2020. Web.
Bao, Wentao, Qi Yu, and Yu Kong. "Object-Aware Centroid Voting for Monocular 3D Object Detection." Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Ed. Ayanna Howard. virtual, virtual: IEEE, 2020. Web.
Bao, Wentao, Qi Yu, and Yu Kong. "Uncertainty-based Traffic Accident Anticipation with SpatioTemporal Relational Learning." Proceedings of the ACM Multimedia. Ed. Guo-Jun Qi. virtual, virtual: ACM, 2020. Web.
Zheng, Ervine, et al. "Dynamic Fusion of Eye Movement Data and Verbal Narrations in Knowledge-rich Domains." Proceedings of the Advances in Neural Information Processing Systems 32 (NIPS 2020). Ed. Hugo Larochelle. virtual, virtual: n.p., Web.
Shi, Weishi, et al. "Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning." Proceedings of the Advances in Neural Information Processing Systems 32 (NIPS 2020). Ed. Hugo Larochelle. virtual, virtual: n.p., Web.
Kang, Jai W., et al. "Complementing Course Contents Between IT/CS: A Case Study on Database Courses." Proceedings of the SIGITE Conference. Ed. Bryan S. Goda, et al. Tacoma, WA: ACM, Web.
Alshangiti, Moayad, et al. "Why is Developing Machine Learning Applications Challenging? A Study on Stack Overflow Posts." Proceedings of the ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. Ed. N/A. Porto de Galinhas, Recife: IEEE, Web.
Shi, Weishi and Qi Yu. "Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning." Proceedings of the Proceedings of the 36th International Conference on Machine Learning (ICML). Ed. Kamalika Chaudhuri and Ruslan Salakhutdinov. Long Beach, CA: PMLR, Web.
Shi, Weishi and Qi Yu. "Integrating Bayesian and Discriminative Sparse Kernel Machines for Multi-class Active Learning." Proceedings of the Advances in Neural Information Processing Systems 32 (NIPS 2019) pre-proceedings. Ed. N/A. Vancouver, Canada: n.p., Web.
Shi, Weishi and Qi Yu. "An Efficient Many-Class Active Learning Framework for Knowledge-Rich Domains." Proceedings of the IEEE International Conference on Data Mining. Ed. Dacheng Tao and Bhavani Thuraisingham. New York, NY: IEEE, Web.
Kang, Jai W., et al. "IT Curriculum: Coping with Technology Trends & Industry Demands." Proceedings of the Proceedings of the Proceedings of the 19th Annual Conference on Information Technology Education. Ed. Thomas Ayers and Daniel Bogaard. New York, NY: ACM, Print.
Obot, Nse, et al. "From Novice to Expert Narratives of Dermatological Disease." Proceedings of the PerCom Workshops. Ed. Daniele Riboni and Petteri Nurmi. New York, NY: IEEE, Print.
Guo, Xuan, et al. "Modeling Physicians\\\' Utterances to Explore Diagnostic Decision-making." Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. Ed. Carles Sierra. Melbourne, Australia, NA: IJCAI, 2017. Print.
Shi, Weishi, Xumin Liu, and Qi Yu. "Correlation-Aware Multi-Label Active Learning for Web Service Tag Recommendation." Proceedings of the 2017 IEEE International Conference on Web Services. Ed. Ilkay Altintas and Shiping Chen. New York, NY: IEEE, 2017. Print.
Peng, Shunshun, Hongbing Wang, and Qi Yu. "Estimation of Distribution with Restricted Boltzmann Machine for Adaptive Service Composition." Proceedings of the 2017 IEEE International Conference on Web Services. Ed. Ilkay Altintas and Shiping Chen. New York, NY: IEEE, 2017. Print.
Wang, Hongbing, Zhengping Yang, and Qi Yu. "Online Reliability Prediction via Long Short Term Memory for Service-Oriented Systems." Proceedings of the 2017 IEEE International Conference on Web Services. Ed. Ilkay Altintas and Shiping Chen. New York, NY: IEEE, 2017. Print.
Wang, Hongbing, et al. "Large-Scale and Adaptive Service Composition Using Deep Reinforcement Learning." Proceedings of the Service-Oriented Computing - 15th International Conference. Ed. E. Michael Maximilien. New York, NY: Springer, 2017. Print.
Kang, Jai, Qi Yu, and Erik Golen. "Teaching IoT (Internet of Things) Analytics." Proceedings of the Proceedings of the 18th Annual Conference on Information Technology Education. Ed. Thomas Ayers and Daniel Bogaard. Rochester, NY: ACM, 2017. Print.
Wang, Hongbing, Xingzhi Zhang, and Qi Yu. "Integrating POMDP and SARSA(λ) for Service Composition with Incomplete Information." Proceedings of the ICSOC. Ed. Quan Z. Sheng et al. Banff, Canada: n.p., Print.
Liu, Xumin, et al. "An LDA-SVM Active Learning Framework for Web Service Classification." Proceedings of the ICWS. Ed. Stephan Reiff-Marganiec. San Francisco, CA: n.p., Web.
Wang, Hongbing, Guicheng Huang, and Qi Yu. "Automatic Hierarchical Reinforcement Learning for Efficient Large-Scale Service Composition." Proceedings of the ICWS. Ed. Stephan Reiff-Marganiec. San Francisco, CA: n.p., Web.
Wan, Yao, et al. "Incorporating Heterogeneous Information for Mashup Discovery with Consistent Regularization." Proceedings of the PAKDD. Ed. James Bailey et al. Auckland, New Zealand: n.p., Print.
Guo, Xuan, et al. "An Expert-in-the-loop Paradigm for Learning Medical Image Grouping." Proceedings of the PAKDD. Ed. James Bailey et al. Auckland, New Zealand: n.p., Web.
Bullard, Joseph, et al. "Towards Early Dementia Detection: Fusing Linguistic and Non-Linguistic Clinical Data." Proceedings of the CLPsych@HLT-NAACL. Ed. Kristy Hollingshead and Lyle H. Ungar. San Diego, CA: n.p., Web.
Kang, Jai W., et al. "Security Requirements Embedded in MS Programs in Information Sciences and Technologies." Proceedings of the SIGITE/RIIT. Ed. Deborah Boisvert and Stephen J. Zilora. Boston, MA: n.p., Web.
Jain, Aditi, Xumin, Liu, and Yu, Qi. "Aggregating Functionality, Use History, and Popularity of APIs to Recommend Mashup Creation." Proceedings of the Service-Oriented Computing - 13th International Conference, ICSOC 2015, Goa, India, November 16-19, 2015. Ed. Alistair Barros, et al. New York, NY: Springer, Print.
Wang, Hongbing, et al. "Integrating Gaussian Process with Reinforcement Learning for Adaptive Service Composition." Proceedings of the Service-Oriented Computing - 13th International Conference, ICSOC 2015, Goa, India, November 16-19, 2015. Ed. Alistair Barros, et al. New York, NY: Springer, Print.
Liu, Xumin, et al. "Extracting, Ranking, and Evaluating Quality Features of Web Services through User Review Sentiment Analysis." Proceedings of the 2015 IEEE International Conference on Web Services, ICWS 2015, New York, NY, USA, June 27 - July 2, 2015. Ed. John A. Miller and Hong Zhu. New York, NY: IEEE, Web.
Chen, Liang, et al. "WS-HFS: A Heterogeneous Feature Selection Framework for Web Services Mining." Proceedings of the 2015 IEEE International Conference on Web Services, ICWS 2015, New York, NY, USA, June 27 - July 2, 2015. Ed. John A. Miller and Hong Zhu. New York, NY: IEEE, Web.
Yu, Qi, Wang, Hongbing, and Chen, Liang. "Learning Sparse Functional Factors for Large-Scale Service Clustering." Proceedings of the 2015 IEEE International Conference on Web Services, ICWS 2015, New York, NY, USA, June 27 - July 2, 2015. Ed. John A. Miller and Hong Zhu:. New York, NY: IEEE, Web.
Wan, Yao, et al. "Time-Aware API Popularity Prediction via Heterogeneous Features." Proceedings of the 2015 IEEE International Conference on Web Services, ICWS 2015, New York, NY, USA, June 27 - July 2, 2015. Ed. John A. Miller and Hong Zhu. New York, NY: IEEE, Web.
Wang, Hongbing, Zhou, Shuxiang, and Yu, Qi. "Discovering Web Services to Improve Requirements Decomposition." Proceedings of the 2015 IEEE International Conference on Web Services, ICWS 2015, New York, NY, USA, June 27 - July 2, 2015. Ed. John A. Miller and Hong Zhu. New York, NY: IEEE, Web.
Kang, Jai, Holden, Edward P., and Yu, Qi. "Pillars of Analytics Applied in MS Degree in Information Sciences and Technologies." Proceedings of the Proceedings of the 16th Annual Conference on Information Technology Education, SIGITE 2015, Chicago, Illinois, USA, September 30 - October 3, 2015. Ed. Amber Settle, Terry Steinbach, and Deborah Boisvert. New York, NY: ACM, Web.
Bullard, Joseph, et al. "Inference from Structured and Unstructured Electronic Medical Data for Dementia Detection." Proceedings of the 14th INFORMS Computing Society Conference Richmond, Virginia, January 11{13, 2015. Ed. Brian Borchers, J. Paul Brooks, and Laura McLay. Baltimore, MD: INFORMS, Web.
Guo, Xuan, et al. "Infusing Perceptual Expertise and Domain Knowledge into a Human-centered Image Retrieval System: A Prototype Application." Proceedings of the ETRA 2014. Ed. Pernilla Qvarfordt and Dan Witzner Hansen. Safety Harbor, FL: ACM, Print.
Guo, Xuan, et al. "Fusing Multimodal Human Expert Data to Uncover Hidden Semantics." Proceedings of the GazeIn@ICMI 2014. Ed. Hung-Hsuan Huang, et al. Istanbul, Turkey: ACM, Print.
Bullard, Joseph, et al. "Towards Multimodal Modeling of Physicians' Diagnostic Confidence and Self-awareness Using Medical Narratives." Proceedings of the COLING 2014. Ed. Jan Hajic and Junichi Tsujii. Dublin, Ireland: ACL, 2014. Print.
Wang, Hongbing, et al. "Integrating On-policy Reinforcement Learning with Multi-agent Techniques for Adaptive Service Composition." Proceedings of the ICSOC 2014. Ed. Xavier Franch, et al. Paris, France: Springer, Print.
Wang, Hongbing, et al. "Adaptive and Dynamic Service Composition via Multi-agent Reinforcement Learning." Proceedings of the ICWS 2014. Ed. David De Roure, Bhavani Thuraisingham, and Jia Zhang. Anchorage, Alaska: IEEE, Print.
Wang, Hongbing, et al. "A Novel Online Reliability Prediction Approach for Service-Oriented Systems." Proceedings of the ICWS 2014. Ed. David De Roure, Bhavani Thuraisingham, and Jia Zhang. Anchorage, Alaska: IEEE, Print.
Hochberg, Limor, et al. "Towards Automatic Annotation of Clinical Decision-Making Style." Proceedings of the 8th Linguistic Annotation Workshop. Ed. Lori Levin and Manfred Stede. Dublin, Ireland: n.p., Print.
Kang, Jai W, Edward P Holden, and Qi Yu. "Design of an Analytic Centric MS Degree in Information Sciences and Technologies." Proceedings of the 15th Annual Conference on Information Technology Education. Ed. Rob Friedman and Ken Baker. Atlanta, Georgia: ACM, 2014. Print.
Wang, L., et al. "Online Reliability Time Series Prediction for Service-Oriented System of Systems." Proceedings of the 11th International Conference on Service Oriented Computing (ICSOC). Ed. S. Basu. Berlin, Germany: Springer, 2013. Print.
Chen, L., et al. "WT-LDA: User Tagging Augmented LDA for Web Service Clustering." Proceedings of the 11th International Conference on Service Oriented Computing (ICSOC). Ed. S. Basu. Berlin, Germany: n.p., 2013. Print.
Wang, H., X. Wang, and Q. Yu. "Optimal Self-Healing of Service-Oriented Systems with Incomplete Information." Proceedings of the IEEE Big Data Congress. Ed. P. Hofmann. Santa Clara, CA: n.p., 2013. Print.
Wang, H., H. Sun, and Q. Yu. "Reliable Service Composition via Automatic QoS Prediction." Proceedings of the 10th International Conference on Services Computing (SCC 2013). Ed. Michael Goul. Santa Clara, CA: n.p., 2013. Print.
Naik, S. and Q. Yu. "Evolutionary User Selection to Maximize the Influence of Viral Marketing." Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). Ed. Tansel Ozyer. Niagara Falls, Canada: n.p., 2013. Print.
Yu, Q., Z. Zheng, and H. Wang. "Trace Norm Regularized Matrix Factorization for Service Recommendation." Proceedings of the IEEE International Conference on Web Services (ICWS). Ed. Michael Lyu. Santa Clara, CA: n.p., 2013. Print.
Yu, Q. "Decision Tree Learning from Incomplete QoS to Bootstrap Service Recommendation." Proceedings of the IEEE International Conference on Web Services (ICWS). Ed. Carole A. Goble, Peter P. Chen, and Jia Zhang. Honolulu, HI: IEEE, 2012. Print.
Yu, Q. "Sparse Functional Representation for Large-scale Service Clustering." Proceedings of the 10th International Conference on Service Oriented Computing (ICSOC 2012). Ed. C. Liu, et al. Shanghai, China: Springer, Print.
Yu, Qi. "Place Semantics into Context: Service Community Discovery from the WSDL Corpus." Proceedings of the Service-Oriented Computing - 9th International Conference, ICSOC 2011. Ed. Gerti Kappel, Zakaria Maamar, and Hamid R. Motahari-Nezhad. Germany: Springer, Print.
Knight, Andrew, Qi Yu, and Manjeet Rege. "Efficient Range Query Processing on Uncertain Data." Proceedings of the IEEE International Conference on Information Reuse and Integration, IRI 2011. Ed. Reda Alhajj, James B. D. Joshi, and Mei-Ling Shyu. Las Vegas, NV: IEEE, 2011. Web.
Journal Paper
Shi, Weishi, et al. "ALL: Supporting Experiential Accessibility Education and Inclusive Software Development." ACM Transactions on Software Engineering and Methodology 33. 2 (2023): 1-30. Web.
Liu, Rui, et al. "A survey of immersive technologies and applications for industrial product development." Computers & Graphics 100. (2021): 137-151. Web.
Alshangit, Moayad, et al. "A Bayesian Learning Model for Design-phase Service Mashup Popularity Prediction." Expert Systems with Applications 149. (2020): 113-231. Print.
Wang, Hongbing, et al. "Integrating Recurrent Neural Networks and Reinforcement Learning for Dynamic Service Composition." Future Generation Computer Systems 107. (2020): 551-563. Web.
Wang, Hongbing, et al. "Integrating Reinforcement Learning and Skyline Computing for Adaptive Service Composition." Information Sciences 519. (2020): 141-160. Web.
Yin, Peng-Nien, et al. "Histopathological Distinction of Non-invasive and Invasive Bladder Cancers Using Machine Learning Approaches." BMC Medical Informatics & Decision Making 20. 1 (2020): 162. Web.
Wang, Hongbing, Shunshun Peng, and Qi Yu. "A Parallel Refined Probabilistic Approach for QoS-aware Service Composition." Future Generation Computer Systems 98. (2019): 609-626. Print.
Wang, Hongbing, et al. "A Motifs-based Maximum Entropy Markov Model for Realtime Reliability Prediction in System of Systems." Journal of Systems and Software 151. (2019): 180-193. Print.
Wang, Hongbing, et al. "Personalized Service Selection Using Conditional Preference Networks." Knowledge Based Systems 164. (2019): 292-308. Print.
Wang, Hongbing, et al. "Adaptive and large-scale service composition based on deep reinforcement learning." Knowledge Based Systems 180. (2019): 75-90. Print.
Wang, Hongbing, et al. "Learning the Evolution Regularities for BigService-Oriented Online Reliability Prediction." IEEE Transactions on Services Computing 12. 3 (2019): 398-411. Web.
Lima, Eduardo, et al. "Integrating Multi-level Tag Recommendation with External Knowledge Bases for Automatic Question Answering." ACM Transactions on Internet Technology 19. 3 (2019): 34:1-34:22. Print.
KC, Kishan, et al. "GNE: A Deep Learning Framework for Gene Network Inference by Aggregating Biological Information." BMC Systems Biology 13. (2019): 38:1-38:14. Web.
Wang, Hongbing, et al. "Effective BigData-Space Service Selection over Trust and Heterogeneous QoS Preferences." IEEE Transactions on Services Computing 11. 4 (2018): 644-657. Print.
Liu, Xumin, et al. "Log Sequence Clustering for Workflow Mining in Multi-workflow Systems." Data & Knowledge Engineering 117. (2018): 1-17. Print.
Zheng, Ervine, et al. "Tag-aware Dynamic Music Recommendation." Expert System with Applications 106. (2018): 244-251. Print.
Wang, Hongbing, et al. "Incorporating Both Qualitative and Quantitative Preferences for Service Recommendation." Journal of Parallel Distributed Computing 114. (2018): 46-69. Print.
Wang, Hongbing, et al. "A Proactive Approach Based on Online Reliability Prediction for Adaptation of Service-oriented Systems." Journal of Parallel Distributed Computing 114. (2018): 70-84. Print.
Wang, Hongbing, et al. "Integrating Modified Cuckoo Algorithm and Creditability Evaluation for QoS-aware Service Composition." Knowledge-Based Systems 140. (2018): 64-81. Print.
Wang, Hongbing, et al. "Online Reliability Time Series Prediction via Convolutional Neural Network and Long Short Term Memory for Service-oriented Systems." Knowledge-Based Systems 159. (2018): 132-147. Print.
Liu, Xumin, et al. "Statistical Learning of Domain-Specific Quality-of-Service Features from User Reviews." ACM Transactions on Internet Technology 17. 2 (2017): 22:1-22:24. Print.
Wang, Hongbign, et al. "Integrating Reinforcement Learning with Multi-Agent Techniques for Adaptive Service Composition." ACM Transactions on Autonomous and Adaptive Systems 12. 2 (2017): 8:1-8:42. Print.
Wang, Hongbing, et al. "Combining Quantitative Constraints with Qualitative Preferences for Effective Non-functional Properties-aware Service Composition." Journal of Parallel and Distributed Computing 100. (2017): 71-84. Print.
Bouguettaya, Athman, et al. "A Service Computing Manifesto: The Next 10 Years." Communications of ACM 60. 4 (2017): 64-72. Print.
Guo, Xuan, et al. "Intelligent Medical Image Grouping through Interactive Learning." International Journal of Data Science and Analytics (JDSA) 2. 3 (2016): 95-105. Print.
Wang, Hongbing, et al. "Effective Service Composition Using Multi-agent Reinforcement Learning." Knowledge-Based Systems 92. (2016): 151-168. Print.
Wang, Hongbing, et al. "Online Reliability Prediction via Motifs-based Dynamic Bayesian Networks for Service-Oriented Systems." IEEE Transactions on Software Engineering (TSE). (2016): 24 pages. Print.
Wang,, Hongbing, et al. "Effective BigData-Space Service Selection over Trust and Heterogeneous QoS Preferences." IEEE Transactions on Services Computing (TSC). (2016): 14 pages. Print.
Sheng, Michael, et al. "Guest Editorial: Big Data Analytics and the Web." IEEE Trans. Big Data 2. 3 (2016): 189. Print.
Bouguettaya, Athman, et al. "Efficient agglomerative hierarchical clustering." Expert Syst. Appl. 42. 5 (2015): 2785-2797. Print.
Yu, Qi. "CloudRec: A Framework for Personalized Service Recommendation in the Cloud." Knowl. Inf. Syst. 43. 2 (2015): 417-443. Print.
Wu, Jian, et al. "Trust-aware Media Recommendation in Heterogeneous Social Networks." World Wide Web 18. 1 (2015): 139-157. Print.
Guo, Xuan, et al. "From Spoken Narratives to Domain Knowledge: Mining Linguistic Data for Medical Image Understanding." Artificial Intelligence in Medicine 62. 2 (2014): 79-90. Print.
Yu, Qi. "QoS-aware Service Selection via Collaborative QoS Evaluation." World Wide Web 17. 1 (2014): 33-57. Print.
Wu, J., et al. "Selecting Skyline Services for QoS-aware Composition by Upgrading MapReduce Paradigm." Cluster Computing 16. 4 (2013): 693-706. Print.
Andhale, J. P., M. Rege, and Q. Yu. "Discovering Heterogeneous Evolving Web Service Communities Using Semi-Supervised Non Negative Matrix Factorization." International Journal of Machine Learning and Computing (IJMLC) 3. 2 (2013): 201-205. Print.
Yu, Q. "Efficient Large-scale Service Clustering via Sparse Functional Representation and Accelerated Optimization." International Journal of Cooperative Information Systems (IJCIS) 22. 4 (2013): 1-26. Print.
Yu, Q. and A. Bouguettaya. "Efficient Service Skyline Computation for Composite Service Selection." IEEE Transactions on Knowledge and Data Engineering (TKDE) 25. 4 (2013): 776-789. Web.
Chen, Xi, et al. "Web Service Recommendation via Exploiting Location and QoS Information." IEEE Trans. Parallel Distrib. Syst. 25. 7 (2013): 1913-1924. Print.
Yu, Q. and A. Bouguettaya. "Multi-Attribute Optimization in Service Selection." World Wide Web Journal (WWWJ) 15. 1 (2012): 1-31. Print.
Yu, Q. and J. Kang. "Integrating User Invocation Data and Extended Semantics for Service Community Discovery." International Journal of Next-Generation Computing (IJNGC) 3. 2 (2012): 1-19. Print.
Yu, Qi and Athman Bouguettaya. "Multi-Attribute Optimization in Service Selection." World Wide Web Journal (WWWJ) 15. 1 (2012): 1-31. Print.
Bouguettaya, Athman, et al. "Service-Centric Framework for a Digital Government Application." IEEE Transactions on Services Computing (TSC) 4. 1 (2011): 3-16. Print.
Xu, Kai, et al. "Web Service Management System for Bioinformatics Research: A Case Study." Service Oriented Computing and Applications 5. 1 (2011): 1-15. Print.
Liu, Xumin, et al. "Efficient Change Management in Long-Term Composed Services." Service Oriented Computing and Applications 5. 2 (2011): 87-103. Print.
Full Length Book
Pahl, Claus, et al. Service-Oriented Computing - 16th International Conference, ICSOC 2018, Hangzhou, China, November 12-15, 2018, Proceedings. 16 ed. Berlin, Germany: Springer, 2018. Web.
Liu, C., et al. 10th International Conference, ICSOC 2012 Shanghai, China,. 10 ed. Shanghi, China: Springer, 2012. Print.
Ghose, A., et al. Service-Oriented Computing - ICSOC 2012 Workshops - ICSOC 2012, International Workshops ASC, DISA, PAASC, SCEB, SeMaPS, WESOA, and Satellite Events. Shanghai, China: Springer, 2013. Print.
External Scholarly Fellowships/National Review Committee
7/15/2018 - 6/30/2021
     National Science Foundation
     Amount: 497,423
10/1/2018 - 9/30/2022
     Office of Naval Research
     Amount: 1,586,800
Book Chapter
Kang,, Jai W, et al. "Web-Based Implementation of Data Warehouse Schema Evolution." New Trends in Intelligent Information and Database Systems. New York, NY: Springer, 2015. 313-322. Web.
Naik, Sanket Anil and Yu, Qi. "Evolutionary Influence Maximization in Viral Marketing." Recommendation and Search in Social Networks. New York, NY: Springer, 2015. 217-247. Web.
Yu, Qi. "On Bootstrapping Web Service Recommendation." Web Services Foundations. Ed. Athman Bouguettaya, Quan Z. Sheng, and Florian Daniel. New York, NY: Springer, 2014. 589-608. Print.
Invited Keynote/Presentation
Yu, Qi. "Big Data Analytics In Service Computing." S&T Seminars. University of Rochester. Rochester, NY. 25 Apr. 2014. Lecture.
Yu, Qi. "On Large-scale Service Clustering: Sparse Learning and Probabilistic Modeling." RMIT Workshop in Service Computing. RMIT. Melbourne, VIC. 8 Dec. 2014. Lecture.
Yu, Qi. "Big Data Analytics in Service Computing." Upstate New York Oracle User Group Educational Workshop. Upstate New York Oracle User Group. Buffalo, NY. 7 Jun. 2013. Conference Presentation.

Currently Teaching

HCIN-795
MS HCI Project
3 Credits
In this course, students will apply the theories and methodologies to the investigation of a problem in the HCI domain. Students who have already prepared a proposal for their capstone project,will design and implement a solution to a problem, and communicate the results.
HCIN-796
MS HCI Thesis
1 - 6 Credits
Students electing a research capstone experience will work closely with an adviser on a current research project or one self-developed and guided by the adviser. Permission of the capstone committee and the graduate program director is required.
HCIN-909
Proposal Development
0 Credits
This course is part of a capstone experience for graduate students who are just beginning the thesis topic development process. Students must submit an accepted proposal as a prerequisite for formal thesis work. Requires permission of the program director for enrollment.
ISTE-780
Data Driven Knowledge Discovery
3 Credits
Rapidly expanding collections of data from all areas of society are becoming available in digital form. Computer-based methods are available to facilitate discovering new information and knowledge that is embedded in these collections of data. This course provides students with an introduction to the use of these data analytic methods, with a focus on statistical learning models, within the context of the data-driven knowledge discovery process. Topics include motivations for data-driven discovery, sources of discoverable knowledge (e.g., data, text, the web, maps), data selection and retrieval, data transformation, computer-based methods for data-driven discovery, and interpretation of results. Emphasis is placed on the application of knowledge discovery methods to specific domains.
ISTE-790
Thesis in Information Technology and Analytics
1 - 6 Credits
The thesis capstone experience for the Master of Science in Information Technology and Analytics program. Students must submit an approved capstone proposal in order to enroll. (Permission of capstone committee and graduate coordinator).
ISTE-791
Project in Information Technology and Analytics
3 Credits
The project-based culminating experience for the Master of Science in Information Technology and Analytics program. A MS project will typically include a software system development component requiring a substantial and sustained level of effort. Students must submit an approved project proposal in order to enroll. (Permission of project committee and graduate program director).
ISTE-909
Proposal Development
0 Credits
This course supports the proposal development process for graduate students who are beginning the thesis experience. Students begin the development of an accepted proposal as a prerequisite for formal thesis registration.
MEDI-909
Proposal Development
0 Credits
This course is part of a capstone experience for graduate students who are beginning the capstone experience. Students will submit an accepted proposal as a prerequisite for the formal thesis. Permission of the graduate adviser is required.

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