Feng Chen

Assistant Professor

Department of Computer Science

UAB 426, 1215 Western Ave, Albany, NY 12222

Phone: (518) 442-2602

Email: fchen5 AT albany DOT edu

Research Interests

My research interests are in large-scale data mining, graph mining, and machine learning, with specific focus on event and anomalous pattern detection and forecasting in complex and heterogeneous network data. Examples of applications include disease outbreak detection using public health data, such as hospital visits and medication sales; detection and prediction of cyber attacks (e.g., spammers, fake users, and compromised normal users) using from social networks and financial data, discovery of anomalous or novel patterns from knowledge graph data, and crowdsourcing human mobility and social media data to detect traffic congestion, air pollution, and power leakage.

Quote:

"Today's AI is about new ways of connecting people to computers, people to knowledge, people to the physical world, and people to people."

~~~ PATRICK WINSTON

Background

I was previously a postdoctoral researcher in the Event and Pattern Detection (EPD) Laboratory and the iLab at Carnegie Mellon University, where I worked with Daniel B. Neill and Ramayya Krishnan . I got my Ph.D. from the Computer Science Depatment at Virginia Polytechnic Institute and State University under the advising of Chang-Tien Lu in Dec. 2012; M.S. from the School of Computer Science at Beijing University of Aeronautics & Astronautics University in Mar. 2004; and B.S. from the School of Computer and Communication at Hunan University in Jul. 2001. During my doctoral studies, I also worked at IBM T.J. Watson Research Labs, Hawthorne, NY during 2011 summer.

Teaching

2016 Fall, ICSI660 Anomalous Pattern Detection [Link]

2016 Fall, ICSI 535 Artificial Intelligence I [Link]

2016 Spring, ICSI431/ICSI531 Data Mining [Link]

2015 Spring, ICSI431/ICSI531 Data Mining [Link]

2015 Fall, ICSI660 Anomalous Pattern Detection [Link]

2014 Spring, ICSI431/ICSI531 Data Mining

2014 Fall, ICSI660 Anomalous Pattern Detection 

Publications

2018

  1. Deep Learning based Scalable Inference of Uncertain Opinions
    Xujiang Zhao, Feng Chen, and Jin-Hee Cho,
    in Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), 2017. (Full paper; Acceptance rate: 8.86%).
  2. Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator
    Zhiqian Chen, Feng Chen, Rongjie Lai, Xuchao Zhang, and Chang-Tien Lu,
    in Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), 2017. (Full paper; Acceptance rate: 8.86%).
  3. A Nonparametric Approach to Uncovering Connected Anomalies by Tree Shaped Priors
    Nannan Wu, Feng Chen, Jianxin Li, Jinpeng Huai, Baojian Zhou, Bo Li, Naren Ramakrishnan,
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018 (Impact Factor 3.438). (To Appear)
  4. Bi-Submodular Optimization (BSMO) for Detecting Drug-Drug Interactions (DDIs) from On-line Health Forum
    Yan Hu, Rui Wang, and Feng Chen,
    Journal of Healthcare Informatics Research (JHIR'18), 2018. (Minor Revision).
  5. Uncertainty Characteristics of Subjective Opinions
    Audun Jøsang, Jin-Hee Cho, and Feng Chen,
    in Proceedings of the IEEE International Conference on Information Fusion (FUSION'18), 2018. (To Appear)
  6. PSCluster: Differentially Private Spatial Cluster Detection for Mobile Crowdsourcing Applications
    Boyang Hu (*), Baojian Zhou (*), Qiben Yan, Alim Adil, Feng Chen, and Huacheng Zeng
    in Proceedings of the IEEE International Conference on Computer Communications and Network Security (CNS'18), 2018. (To Appear)
  7. Graph Anomaly Detection Based on Steiner Connectivity and Density
    Jose Cadena, Feng Chen, Anil Vullikanti,
    Proceedings of the IEEE, 2018 (Impact Factor 9.237). (To Appear)
  8. An Efficient Framework for Detecting Evolving Anomalous Subgraphs in Dynamic Networks
    Minglai Shao, Jianxin Li, Feng Chen, and Xunxun Chen
    in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM'18), 2018. (Regular paper; Acceptance rate: 19.2%; To Appear)

2017

  1. Parallel Algorithms for Anomalous Subgraph Detection
    Jieyu Zhao, Jianxin Li, Baojian Zhou, Feng Chen, Paul Tomchik, Wuyang Ju,
    in Journal of Concurrency and Computation: Practice and Experience (JCC), 29(3), 2017.
  2. Techniques for Efficient Detection of Rapid Weather Changes and Analysis of Their Impacts on a Highway Network
    Adil Alim, Aparna Joshi, Feng Chen, and Catherine T. Lawson
    in Proceedings of the 2nd IEEE International Workshop on Big Spatial Data (BSD 2017) at IEEE BigData, pages 3378-3387, 2017.
  3. Collective Subjective Logic: Scalable Uncertainty-based Opinion Inference
    Feng Chen, Chunpai Wang, and Jin-Hee Cho
    in Proceedings of the IEEE International Conference on Big Data (BigData'17), 2017. (Regular paper; Acceptance rate: 18%; To Appear)
  4. Discrn: A distributed storytelling framework for intelligence analysis,
    Manu Shukla, Ray Dos Santos, Feng Chen, and Chang-Tien Lu
    Big Data Journal, 2017 (To Appear)
  5. A Generic Framework for Interesting Subspace Cluster Detection in Multi-attributed Networks,
    Feng Chen, Baojian Zhou, Adil Alim, and Liang Zhao
    in Proceedings of the IEEE International Conference on Data Mining (ICDM 2017), pages 41-50, 2017. (Regular paper; Acceptance rate: 9.25%).
  6. Drug-Drug Interactions (DDIs) Detection from On-line Health Forums: Bi-Submodular Optimization (BSMO),
    Yan Hu, Rui Wang, and Feng Chen,
    in Proceedings of the IEEE International Conference on Healthcare Informatics (ICHI 2017), 163-170, 2017.
  7. Spatial Event Forecasting in Social Media with Geographically Hierarchical Regularization
    Liang Zhao, Junxiang Wang, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan
    Proceedings of the IEEE, 105(10), pages 1953--1970, 2017 (Impact Factor 9.237).
  8. Effective Online Software Anomaly Detection
    Yizhen Chen, Ming Ying, Daren Liu, Adil Alim, Feng Chen, and Mei-Hwa Chen
    in Proceedings of the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA'17), pages 136-146, 2017.
  9. Can Self-Censorship in News Media be Detected Algorithmically? A Case Study in Latin America
    Rongrong Tao, Baojian Zhou, Feng Chen, Naifeng Liu, David Mares, Patrick Butler, Naren Ramakrishnan
    arXiv, preprint arXiv:1611.06947, 2017.
  10. Making a Difference: Analytics for Quality Knowledge-Building Conversations
    Frank de Jong, Joan van den Ende, Hennie van Heijst, Yoshiaki Matsuzaw, Paul Kirschner, Jianwei Zhang, Mei-Hwa Chen, Feng Chen, et al.
    Philadelphia, PA: International Society of the Learning Sciences, 2017.
  11. Query-Driven Discovery of Anomalous subgraphs in Attributed Graphs
    Nannan Wu, Feng Chen, Jianxin Li, Jinpeng Huai, and Bo Li
    in Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), pages 3105-3111, 2017.
  12. Road Traffic Speed Prediction: A Probabilistic Model Fusing Multi-Source Data
    Lu Lin, Jianxin Li, Feng Chen, Jieping Ye, Jinpeng huai,
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2017 (Impact Factor 3.438). (To Appear)
  13. Spatial Prediction for Multivariate Non-Gaussian Data
    Xutong Liu, Feng Chen, Kevin Y. Lu, and Chang-Tien Lu
    ACM Transactions on Knowledge Discovery from Data (TKDD), volume 11, issue 3, pages 36:1-36:27, 2017.
  14. Tracking Multiple Social Media for Stock Market Event Prediction
    Fang Jin, Wei Wang, Prithwish Chakraborty, Nathan Self, Feng Chen, and Naren Ramakrishnan
    in Proceedings of the 2017 Industrial Conference on Data Mining (ICDM), 16-30, 2017.
  15. Feature Constrained Multi-Task Learning Models for Spatiotemporal Event Forecasting
    Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan
    IEEE Transactions on Knowledge and Data Engineering (TKDE), volume 29, issue 5, pages 1059--1072, 2017 (Impact Factor 3.438).
  16. Near Optimal and Practical Algorithms for Graph Scan Statistics
    Jose Cadena, Feng Chen, and Anil Vullikanti
    in Proceedings of the 2017 SIAM International Conference on Data Mining (SDM 2017), pages 624-632, 2017. (acceptance rate: 26%).
  17. Absenteeism Detection in Social Media
    Fang Jin, Feng Chen, Rupinder Paul Khandpur, Chang-Tien Lu, and Naren Ramakrishnan
    in Proceedings of the 2017 SIAM International Conference on Data Mining (SDM 2017), pages 606-614, 2017. (acceptance rate: 26%).
  18. An Efficient Approach to Event Detection and Forecasting in Dynamic Multivariate Social Media Networks
    Minglai Shao, Jianxin Li, Feng Chen, Hongyi Huang, Shuai Zhang, and Xunxun Chen
    in Proceedings of the 26th World Wide Web Conference (WWW 2017), pages 1631-1639, 2017. (acceptance rate: 17%).
  19. Nearest Neighbor Query, Definition
    Feng Chen and Chang-Tien Lu
    Encyclopedia of GIS 2017, pages 1433-1440, 2017.

2016

  1. Traffic Flow Prediction for Urban Networks Using a Spatio-Temporal Random Effects Model
    Yao-Jan Wu, Feng Chen, Chang-Tien Lu and Shu Yang,
    Journal of Intelligent Transportation Systems (JITS) , volume 20, issue 3, pages 282-293, 2016.
  2. From Twitter to Detector: Real-time Traffic Incident Detection using Social Media Data
    Yiming Gu, Sean Qian, Feng Chen
    Transportation Research Part C: Emerging Technologies, volume 67, pages 321-342, 2016. (Impact factor: 3.805)
  3. The Big Data of Violent Events: Algorithms for Association Analysis Using Spatio-Temporal Storytelling
    Raimundo F. Dos Santos, Arnold Boedihardjo, Sumit Shah, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan
    Journal of GeoInformatica, volume 20, issue 4, pages 879-921, 2016.
  4. Automatic Targeted-Domain Spatiotemporal Event Detection in Twitter
    Ting Hua, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan
    Journal of GeoInformatica, volume 20, issue 4, pages 765-795, 2016.
  5. Discovering Anomalies on Mixed-Type Data using a Generalized Student-t Based Approach
    Kevin Y. Lu, Feng Chen, Yating Wang, and Chang-Tien Lu
    IEEE Transactions on Knowledge and Data Engineering (TKDE), volume 28, issue 10, pages 2582-2595, 2016 (Impact Factor 3.438).
  6. Online Spatial Event Forecasting in Microblogs
    Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan
    ACM Transactions on Spatial Algorithms and Systems (TSAS), 2016. (To Appear)
  7. Twitter Popularity Diffusion of Presidential Candidates Through Detection of Twitter Bots
    Akanksha Atrey, Aatman Togadia, and Feng Chen,
    to be presented at the 2016 IEEE MIT Undergraduate Research Technology Conference (URTC 2016), 2016. (Poster)
  8. Graph-Structured Sparse Optimization for Connected Subgraph Detection
    Baojian Zhou and Feng Chen
    in Proceedings of the IEEE International Conference on Data Mining (ICDM 2016) , 2016. (Regular paper; acceptance rate: 8.4%). [Technical Report, Source Code]
  9. Multi-resolution Spatial Event Forecasting in Social Media
    Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan
    in Proceedings of the IEEE International Conference on Data Mining (ICDM 2016) , 2016. (Regular paper; acceptance rate: 8.4%).
  10. Graph Topic Scan Statistic for Spatial Event Detection
    Yu Liu, Baojian Zhou, Feng Chen, and David W. Cheung
    in Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM 2016), 2016. (Long paper, acceptance rate: 17.6%).
  11. Hierarchical Incomplete Multisource Feature Learning for Spatiotemporal Event Forecasting
    Liang Zhao, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan
    in Proceedings of the 22st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'16), pages 2085-2094, 2016.
  12. A Generalized Matching Pursuit Approach for Graph-Structured Sparsity
    Feng Chen and Baojian Zhou
    in Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), pages 1389-1395, 2016. [Technical Report, Source Code]
  13. Efficient Nonparametric Subgraph Detection using Tree Shaped Priors [PDF]
    Nannan Wu, Feng Chen, Jianxin Li, Baojian Zhou, Naren Ramakrishnan
    in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI'16), 2016.
  14. Topical Analysis of Interactions between News and Social Media [PDF]
    Hua Ting, Yue Ning, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan
    in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI'16), 2016.

2015

  1. Examining political mobilization of online communities through e-petitioning behavior in We the People
    Catherine L. Dumas, Daniel LaManna, Teresa M. Harrison, S. S. Ravi, Christopher Kotfila, Norman Gervais, Loni Hagen, and Feng Chen
    Journal of Big Data & Society, volume 2, issues 2, pages 1-20, 2015.
  2. Fast Adaptive Kernel Density Estimators for Data Stream [PDF]
    Arnold P. Boedihardjo, Chang-Tien Lu, Feng Chen
    in Knowledge and Information Systems: An International Journal (KAIS), pages 1-33, Springer, 2015.
  3. Human rights event detection from heterogeneous social media graphs [PDF]
    Feng Chen and Daniel B. Neill
    in Big Data Journal, volume 3, issue 1, pages 34-40, 2015.
  4. A framework for intelligence analysis using spatio-temporal storytelling [PDF]
    Raimundo F. Dos Santos, Sumit Shah, Arnold Boedihardjo, Feng Chen, Chang-Tien Lu, Patrick Butler, Naren Ramakrishnan
    Journal of GeoInformatica, pages 1-42, 2015.
  5. How Events Unfold: Spatiotemporal Mining in Social Media
    Ting Hua, Liang Zhao, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan,
    ACM SIGSPATIAL Newsletter, volume 7, issue 3, pages 19-25, 2015.
  6. Dynamic Theme Tracking in Twitter [PDF]
    Liang Zhao, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan
    in Proceedings of the IEEE International Conference on Big Data (BigData'15), pages 561-570, 2015.
  7. SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learnin [PDF]
    Liang Zhao, Jiangzhuo Chen, Feng Chen, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan
    in Proceedings of the IEEE International Conference on Data Mining (ICDM'15), pages 639-648, 2015.
  8. Multi-task learning for spatio-temporal event forecasting [PDF]
    Liang Zhao*, Qian Sun* (co-first author), Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan
    in Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1503-1512, 2015.
  9. Spatiotemporal Event Forecasting in Social Media [PDF]
    Liang Zhao, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan
    in Proceedings of the 2015 Siam International Conference on Data Mining (SDM'15), pages 963-971, 2015.

2014

  1. Non-Parametric Scan Statistics for Disease Outbreak Detection on Twitter [PDF]
    Feng Chen, Daniel B. Neill
    in Online Journal of Public Health Informatics, volume 6, issue 1, 2014.
  2. Analyzing Civil Unrest through Social Media [PDF]
    Ting Hua, Chang-Tien Lu, Naren Ramakrishnan, Feng Chen, Jaime Arredondo, David Mares, and Kristen Summers
    in Computer Magazine, volume 46, issue 12, pages 80-84, 2013.
  3. SpecMonitor: Towards Efficient Passive Traffic Monitoring for Cognitive Radio Networks [PDF]
    Qiben Yan, Ming Li, Feng Chen, Tingting Jiang, Weijing Lou, Y. Thomas Hou, Chang-Tien Lu
    in IEEE Transactions on Wireless Communication (TWC), 2014.
  4. Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling [PDF]
    Liang Zhao, Feng Chen, Jing Dai, Ting Hua, Chang-Tien Lu, and Naren Ramakrishnan
    in PLOS ONE, volume 9, issue 10: e110206. doi:10.1371/journal.pone.01102062014, 2014.
  5. Road Traffic Congestion Monitoring in Social Media with Hinge-Loss Markov Random Fields [PDF]
    Po-Ta Chen, Feng Chen, Zhen(Sean) Qian
    in Proceedings of the IEEE International Conference on Data Mining (ICDM'14), pages 80-89, 2014.
  6. Forecasting Location-based Events with Spatio-temporal Storytelling [PDF]
    Ray Dos Santos, Sumit Shah, Feng Chen, Arnold Boedihardjo, Chang-Tien Lu, Naren Ramakrishnan
    in Proceedings of the 7th ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN'14), 2014.
  7. Non-Parametric Scan Statistics for Event Detection and Forecasting in Heterogeneous Social Media Graphs [PDF]
    Feng Chen and Daniel B. Neill
    in Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14), pages 1166-1175, 2014.
  8. Modeling Mass Protest Adoption in Social Network Communities using Geometric Brownian Motion [PDF]
    Fang Jin, Rupinder Khandpur, Nathan Self, Edward Dougherty, Feng Chen, B. Aditya Prakash, and Naren Ramakrishnan
    in Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14), pages 1660-1669, 2014.
  9. Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators [PDF]
    With Naren Ramakrishnan and Others
    in Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14), pages 1799-1808, 2014.

2013

  1. On Detecting Spatial Categorical Outliers [PDF]
    Xutong Liu, Feng Chen, Chang-Tien Lu
    Journal of GeoInformatica, volume 18, issue 3, pages 501-536, 2013.
  2. A Carpooling REcommendation System Based on Social Vanet and Geo-Social Data [PDF]
    Ahmed Elbery, Mustafa EINainay, Chang-Tien Lu, Feng Chen, and Jeffrey Kendall
    in Proceedings of the 21th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM-GIS'13), 2013.
  3. Learning Thread Reply Structure on Patient Forums [PDF]
    Yunzhong Liu, Feng Chen, Yi Chen
    in Proceedings of the International Workshop on Data management and Analytics for Healthcare (DARE'13), CIKM, 2013.
  4. Automatic Event Detection and Storytelling in Social Media [PDF]
    Feng Chen
    NSF Workshop on Knowledge Discovery in Cyberspace and Big Data, 2013.
  5. STED: Semi-Supervised Targeted Event Detection [PDF]
    Ting Hua, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan
    inProceedings of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data (KDD'13), Demo Track, 2013.
  6. A Generalized Student-t Based Approach to Mixed-Type Anomaly Detection [PDF]
    Yen-Cheng Lu, Feng Chen, Yang Chen, Chang-Tien Lu
    in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI'13), 2013.
  7. Optimal Network Traffic Surveillance in Cognitive Radio Networks [PDF]
    Qiben Yan, Ming Li, Feng Chen, Tingting Jiang, Wenjing Lou, Chang-Tien Lu
    in Proceedings of the 32nd IEEE International Conference on Computer Communications (INFORCOM'13), pages 1240-1248, 2013.

2012

  1. Student-t Based Robust Spatio-Temporal Prediction [PDF]
    Yang Chen, Feng Chen, Jing Dai, T. Charles Clancy
    in Proceedings of the IEEE International Conference on Data Mining (ICDM'12), pages 151-160, 2012.
  2. Robust Inference and Outlier Detrection for Large Spatial Data Sets [PDF]
    Xutong Liu, Feng Chen, Chang-Tien Lu
    in Proceedings of the IEEE International Conference on Data Mining (ICDM'12), pages 469-478, 2012.
  3. Signal Disaggregation via Sparse Coding with Featured Discriminative Dictionary [PDF]
    Bingsheng Wang, Feng Chen, Haili Dong, Arnold Boedihardjo, and Chang-Tien Lu
    in Proceedings of the IEEE International Conference on Data Mining (ICDM'12), pages 1134-1139, 2012.
  4. Spatial Surrogates to Forecast Social Mobilization and Civil Unrests [PDF]
    Feng Chen, Jaime Arredondo, Rupinder Paul Khandpur, Chang-Tien Lu, David Mares, Dipak Gupta, and Naren Ramakrishnan
    in Computing Community Consortium (CCC) Workshop on "From GPS and Virtual Globes to Spatial Computing-2012," 2012
  5. Traffic Flow Prediction for Urban Network using Spatial Temporal Random Effects Model [PDF]
    Yao-Jan Wu, Feng Chen, Chang-Tien Lu, Brian Smith, Yang Chen
    the 91st Annual Meeting of the Transportation Research Board (TRB'12), 2012

2011

  1. Spatial Categorical Outlier Detection: Pair Correlation Function Based Approach [PDF]
    Xutong Liu, Feng Chen, and Chang-Tien Lu
    in Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS'11), pages 465-468, 2011
  2. Multi-granular Demand Forecasting in Smarter Water [PDF]
    Jing Dai, Ming Li, Sambit Sahu, Milind Naphade, Feng Chen
    in Proceedings of the 13th International Conference on Ubiquitous Computing (Ubicomp'11), pages 595-596, 2011
  3. Activity Analysis Based on Low Sample Rate Smart Meters [PDF]
    Feng Chen, Jing Dai, Bingsheng Wang, Sambit Sahu, Milind Naphade, Chang-Tien Lu
    in Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'11), pages 240-248, 2011
  4. On Path Anomaly Detection in a Large Transportation Network [PDF]
    Qifeng Lu, Feng Chen, Kathleen Hancock
    in Journal of Computers, Environment and Urban Systems (JCEU), volume 33, pages 448-462, 2009.

2010

  1. GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection [PDF]
    Feng Chen, Chang-Tien Lu, Arnold P. Boedihardjo
    in Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), pages 1069-1078, 2010
  2. Regional Behavior Change Detection via Local Spatial Scan [PDF]
    Jing Dai, Feng Chen, Sambit Sahu, Milind Naphade
    in Proceedings of the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS'10), 2010
  3. Spatial Outlier Detection: Random Walk Based Approaches [PDF]
    Xutong Liu, Chang-Tien Lu, Feng Chen
    in Proceedings of the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS'10), 2010

2008

  1. On Detecting Spatial Outliers [PDF]
    Dechang Chen, Chang-Tien Lu, Yufeng Kou, Feng Chen
    in Journal of Geoimformatica, volume 12, pages 455-475, 2008.
  2. On Locally Linear Classification by Pair-wise Coupling [PDF]
    Feng Chen, Chang-Tien Lu, Arnold P. Boedihardjo
    in Proceedings of the IEEE International Conference on Data Mining (ICDM'08), pages 749-754, 2008
  3. A Framework for Estimating Complex Probability Density Structures in Data Streams [PDF]
    Arnold P. Boedihardjo, Chang-Tien Lu, Feng Chen
    in Proceedings of the ACM 17th Conference on Information and Knowledge Management (CIKM'08), pages 619-628, 2008
  4. HOMES: Highway Operations and Monitoring and Evaluation System [PDF]
    Chang-Tien Lu, Arnold P. Boedihardjo, David Dai, Feng Chen
    in Proceedings of the ACM 16th International Conference on Advances in Geographic Information Systems (GIS'08), pages 529-530, 2008
  5. Nearest Neighbor Query [PDF]
    Feng Chen and Chang-Tien Lu
    Encyclopedia of Geographical Information Science (1st Edition), Springer-Verlag, pages 776-781, 2008
  6. An Entropy-Based Method for Assessing the Number of Spatial Outliers [PDF]
    Xutong Liu, Chang-Tien Lu, and Feng Chen
    in Proceedings of the IEEE International Conference on Information Reuse and Integration (IRI'08), pages 244-249, 2008

Book Sections

Feng Chen and Chang-Tien Lu, "Nearest Neighbor Query," Encyclopedia of Geographical Information Science (1st Edition), Springer-Verlag, pages 776-781, 2008

Patents

  1. "Behavior Change Detection," with Jing Dai, Sambit Sahu, Milind Naphade, IBM, T.J. Waston, 2012
  2. "Utility Consumption Disaggregation Through Human Activity Association," with Jing Dai, Sambit Sahu, Milind Naphade, IBM, T.J. Waston, 2012

Grants

  1. Lead Principal Investigator (with Xiaohua Tony Hu from Drexel University), National Science Foundation (NSF), ``A novel paradigm for detecting complex anomalous patterns in multi-modal, heterogeneous, and high-dimensional multi-source data sets,'' IIS-1815696, Duration 09/2018 - 09/2021, $499,718 (my share: $249,989)
  2. Early Faculty Career Development (CAREER) Award, National Science Foundation (NSF), ``CAREER: SPARK: A Theoretical Framework for Discovering Complex Patterns in Big Attributed Networks,'' IIS-1750911, Duration 05/01/2018 - 05/01/2023, $537,044
  3. Co-Principal Investigator (with Jianwei Zhang, Mei-Hwa Chen, Marlene Scardamalia, Carolyn Rose), National Science Foundation (NSF), ``Connecting Idea Threads across Communities for Sustained Knowledge Building,'' Duration: 09/2014 - 08/2018, $1,342,537.
  4. Co-Principal Investigator (with Tolga Soyata, Ming-Ching Chang, Chinwe Ekenna, Yelin Kim, Jeong-Hyon Hwang), SUNY Center-Scale Planning and Development Grant Program, ``A General, Intelligent, Bio-Inspired Computing Framework for Sensor Networks,'' duration 6/2018 to 1/2019, $25,000
  5. Principal Investigator, SUNY-A Faculty Research Award, ``A New Nonparametric and Deep Learning Framework for Anomalous Pattern Detection in Heterogeneous Multi-Source Data,'' Duration 2018-2021, $10,000.
  6. Principal Investigator, NIH Small Business Innovation Research (SBIR) Program, ``An Integrated, Open-source, Web Platform for Continuous Chronic Disease Surveillance on Social Media,'' Duration 9/20/2017 - 3/20/2018, $50,000.
  7. Principal Investigator, Army Research Office (ARO), ``Uncertainty Management for Dynamic Decision Making,'' Duration 9/1/2017 - 12/30/2019, $330,000.
  8. Co-Principal Investigator (with Jeong-Hyon Hwang and Petko B Bogdanov), UAlbany University Presidential Innovation Fund for Research and Scholarship (PIFRS) program, ``A Systems-Oriented Framework for Mining Complex Subgraphs,” Duration: 02/01/2017 -1/30/2018, $41,260.
  9. Principal Investigator (with Ozlem Uzuner from George Manson Univ.), Strategic Partnership for Industrial Resurgence (SPIR) Program at UAlbany, ``Data analytics on market insights from online news," Duration 5/1/17 - 7-30/2018, $92,000
  10. Co-Principal Investigator (with Catherine Lawson), US Department of Transportation (DOT), ``Techniques for Efficient Detection of Rapid Weather Changes and Analysis of their Impacts on a Highway Network,'' Duration 09/01/16 - 0901/17, $71,684.
  11. Principal Investigator, SUNY-B Faculty Research Award, ``Non-Parametric Graph Scan for Event Detection,''; 06/2014 – 04/2015, $3,324.
  12. Principal Investigatorr, IARPA, ``Early Model Based Event Recognition using Surrogates,'' 04/2015 – 06/2016, $120,000.
  13. Principal Investigator, IARPA, ``Early Model Based Event Recognition using Surrogates,'' 06/2014 – 04/2015, $124,861.
  14. Co-Principal Investigator (with Catherine Lawson, Jeong-Hyon Hwang, S. S. Ravi), US Department of Transportation (DOT), ``Techniques for Information Extraction from Compressed GPS Traces,'' 03/2014 - 02/2015, $100,000.

Services

  1. Publication Chair
    IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Nov. 13-15, Arlington, VA, 2006
  2. Session Chairs
    2015 Siam International Conference on Data Mining (SDM); 2015 IEEE International Conference on Data Mining (ICDM).
  3. PC Members
    KDD-16, ICDM-15, SDM-15, 16, IJCAI-13, UAI Bayesian Applications Workshop (BIBW-14, 15), IEEE International Workshop on Trust, Security and Privacy for Big Data (TrustData-14), Mobile Sensing, Mining and Visualization for Human Behavior Inference Workshop (MSMV-MBI-14), Digital Forensics Experiments and Results (DiFER-15), IEEE International Workshop on Big Data in Computational Epidemiology (BDCE-15), ACM International Workshop on Data Mining for Brain Science (BrainKDD-15).
  4. Journal Reviewer
    Information Science, IEEE Transactions on Knowledge and Data Engineering (TKDE), Computer Magazine. ACM Transactions on Knowledge Discovery from Data, IEEE Transaction on Big Data, Geoinformatica, Transactions on Intelligent Systems and Technology, Transactions on Services Computing, Knowledge and Information Systems, Journal of Meteorological Research
  5. Tutorials
    Feng Chen, Petko Bogdanov, Daniel B. Neill, and Ambug K. Singh, “Anomalous and Significant Subgraph Detection in Attributed Networks,” 2016 IEEE International Conference on Big Data (IEEE Big Data 2016).
  6. NSF Service
    NSF Review Panelist CISE (2016-03), NSF proposal review (2015).

Honors and Awards

  1. CAREER Award, National Science Foundation, 2018
  2. Faculty Research Award, SUNY, 2018
  3. Faculty Research Award, SUNY, 2014
  4. Department nominations for IBM Ph.D. fellowship Awards, 2011, 2012
  5. Student Travel Award, the 2012 IEEE International Conference on Data Mining, 2012
  6. Student Travel Award, the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM-KDD), San Diego, CA, August 21-24, 2011
  7. 2nd Place Poster Prize in Security Category, National Academy of Engineering Grand Challenges Summit Contest, Mar. 2-3, Durham, NC, 2009
  8. 2st Place Research Poster Prize, Virginia Tech Northern Capital Region Graduate Research Symposium, Mar. 23-27, Falls Church, VA, 2009
  9. Service Excellence Award as Publication Chair, IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Nov. 13-15, Arlington, VA, 2006