Teaching: Current Courses

• IC411 (Fall 2023) -- Operating Sytems (calendar)

Research

My research focuses on how to mine useful information from networks of linked data. There are many examples of such data networks including:

• social networks (people linked by friendships/interactions)
• the World Wide Web (pages linked by hyperlinks)
• communication networks (people/phones linked by calls or messages)
• biological applications (such as proteins linked by interactions), and more.

I have been at USNA since 2005, was promoted to Associate Professor in 2010, and to Professor in 2016. During 2011-12, I had a great year visiting the Distributed Information Systems Laboratory of Prof. Karl Aberer in Lausanne, Switzerland. It's not often up to date, but you can check out my CV.

My Ph.D. in Computer Science is from the University of Washington. My advisors were Oren Etzioni and Alon Halevy. Earlier, I studied Electrical Engineering at Princeton University, advised by Margaret Martonosi.

Data for Link-based Classification problems

Collective Inference (learning in graph-based/networked data) (slides from a recent overview talk)

• Fully Heterogeneous Collective Regression. David J. Liedtka and Luke K. McDowell 2018 IEEE International Conference on Data Science and Advanced Analytics (DSAA2018), October 2016. An earlier version also appeared at the 14th International Workshop on Mining And Learning With Graphs (MLG2018), August 2018.
• Correcting Relational Bias to Improve Classification in Sparsely-Labeled Networks. Joshua R. King and Luke K. McDowell. 2016 IEEE/ACM International Conference on Data Science and Advanced Analytics (DSAA2016), October 2016.
• Leveraging Neighbor Attributes for Classification in Sparsely-Labeled Networks. Luke K. McDowell and David W. Aha. ACM Transactions on Knowledge Discovery from Data, Volume 11(1),2:1-2:37, 2016.
• Relational Active Learning for Link-Based Classification (Winner, Best Paper Award). Luke K. McDowell. 2015 IEEE/ACM International Conference on Data Science and Advanced Analytics (DSAA2015), October 2015.
• Evaluating and Extending Latent Methods for Link-based Classification . Luke K. McDowell, Aaron Fleming, and Zane Markel. Advances in Intelligent Systems and Computing (AISC) 346:227-256, March 2015 (Springer).
• A Hidden Treasure? Evaluating and Extending Latent Methods for Link-based Classification . Aaron Fleming, Luke K. McDowell and Zane Markel. 15th IEEE International Conference on Information Reuse and Integration (IRI 2014), August 2014.
• Labels or Attributes? Rethinking the Neighbors for Collective Classification in Sparsely-Labeled Networks. Luke K. McDowell and David W. Aha. 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013), October 2013, pgs. 847-852. (data)
• Transforming Graph Data for Statistical Relational Learning. Ryan A. Rossi, Luke K. McDowell, David W. Aha, and Jennifer Neville. Journal of Artificial Intelligence Research (JAIR), Volume 45: 363-441, 2012.
• Semi-Supervised Collective Classification via Hybrid Label Regularization. Luke K. McDowell and David W. Aha. 29th International Conference on Machine Learning (ICML 2012), June 2012. (data)
• Investigating Markov Logic Networks for Collective Classification. Robert Crane and Luke K. McDowell. Proceedings of the Fourth International Conference on Agents and Artificial Intelligence (ICAART 2012), February 2012, pgs. 5-15. An earlier version of this work (Evaluating Markov Logic Networks for Collective Classification) appeared at the MLG 2011 workshop.
• Meta-Prediction for Collective Classification. Luke K. McDowell, Kalyan Moy Gupta, and David W. Aha. 23rd International FLAIRS Conference (FLAIRS-23), May 2010.
• Cautious Collective Classification. Luke K. McDowell, Kalyan Moy Gupta, and David W. Aha. Journal of Machine Learning Research 10(Dec):2777-2836, 2009.
• Cautious Inference in Collective Classification. Luke K. McDowell, Kalyan Moy Gupta, and David W. Aha. 22nd AAAI Conference on Artificial Intelligence (AAAI-07), July 2007.
• Case-Based Collective Classification. Luke K. McDowell, Kalyan Moy Gupta, and David W. Aha. 20th International FLAIRS Conference (FLAIRS-20), May 2007.

Predictions from Mobile Data and Twitter

• Topick: Accurate Topic Distillation for User Streams. Anton Dimitrov, Alexandra Olteanu, Luke McDowell, and Karl Aberer. IEEE International Conference on Data Mining (ICDM 2012), Demo Session, December 2012, pgs. 882-885.
• Next Place Prediction using Mobile Data. Le-Hung Tran, Michele Catasta, Luke K. McDowell, Karl Aberer. Proceedings of the Mobile Data Challenge Workshop (MDC 2012), June 2012.
• Semantic Place Prediction using Mobile Data. Abson Sae-Tang, Michele Catasta, Luke K. McDowell, Karl Aberer. Proceedings of the Mobile Data Challenge Workshop (MDC 2012), June 2012.

Information Extraction from the Web (for the Semantic Web)

• Ontology-driven, Unsupervised Instance Population . Luke K. McDowell and Michael Cafarella. Journal of Web Semantics 6(3): 218-236, 2008.
• Ontology-driven Information Extraction with OntoSyphon . Luke K. McDowell and Michael Cafarella. Fifth International Semantic Web Conference (ISWC 2006), November 2006.

Dimensionality Reduction

• Enhancing Text Analysis via Dimensionality Reduction. David Underhill, Luke McDowell, David Marchette and Jeff Solka. 2007 IEEE International Conference on Information Reuse and Integration, August 2007.

Mangrove and Semantic Email: Making the Semantic Web Real

• Preparing Semantic Agents for an Unsuspecting and Unreliable World. Luke McDowell. First International Symposium on Agents and the Semantic Web (AAAI Fall Symposium Series), November 2005.
• Meaning for the Masses: Theory and Applications for Semantic Web and Semantic Email Systems. Luke McDowell. Ph. D. Dissertation, University of Washington, August 2004.
• Semantic Email: Theory and Applications Luke McDowell, Oren Etzioni, and Alon Halevy. Journal of Web Semantics 2(2):153-183, 2004.
• The Specification of Agent Behavior by Ordinary People: A Case Study. Luke McDowell, Oren Etzioni, and Alon Halevy. Third International Semantic Web Conference (ISWC 2004), November 2004.
• Semantic Email. Luke McDowell, Oren Etzioni, Alon Halevy, and Henry Levy. Thirteen International World Wide Web Conference (WWW2004), May 2004.
• Mangrove: Enticing Ordinary People onto the Semantic Web via Instant Gratification. Luke McDowell, Oren Etzioni, Steven Gribble, Alon Halevy, Henry Levy, William Pentney, Deepak Verma, and Stani Vlasseva. Second International Semantic Web Conference (ISWC 2003), October 2003.
• Semantic Email: Adding Lightweight Data Manipulation Capabilities to the Email Habitat. Oren Etzioni, Alon Halevy, Henry Levy, and Luke McDowell. Sixth International Workshop on the Web and Databases (WebDB 2003), June 2003.
• Evolving the Semantic Web with Mangrove. Luke McDowell, Oren Etzioni, Steven Gribble, Alon Halevy, Hank Levy, William Pentney, Deepak Verma, Stani Vlasseva (UW Tech Report February 2003).
• Crossing the Structure Chasm. Alon Halevy, Oren Etzioni, AnHai Doan, Zachary Ives, Jayant Madhavan, Luke McDowell, Igor Tatarinov. First Biennial Conference on Innovative Data Systems Research (CIDR 2003), Jan 2003.
• An Evolutionary Approach to the Semantic Web (ISWC 2002, poster)

Computer Architecture

• Improving Server Software Support for Simultaneous Multithreaded Processors. Luke McDowell, Susan Eggers, Steven Gribble. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP 03), June 2003.
• An Evaluation of Speculative Instruction Execution on Simultaneous Multithreaded Processors. Steve Swanson, Luke McDowell, Michael Swift, Susan Eggers, Henry Levy. ACM Transactions on Computer Systems 21(3): 314-340 (2003).

Computer Science Education

• Use of Classroom Presenter in Engineering Courses. Richard Anderson, Ruth Anderson, Luke McDowell, and Beth Simon. 35th ASEE/IEEE Frontiers in Education Conference, October 2005.