For more recent and complete information, please see my Curriculum Vitae.

About Me

I am a Ph.D. Student in Computer Science at Purdue University. My research is focused on machine learning and data mining algorithms for large dynamic networks. My research interests lie in artificial intelligence, machine learning, graph algorithms, network analysis, security, and information retrieval. I am also a member of the Statistical Machine Learning group at Purdue University. My research is generously supported by the NSF Graduate Research Fellowship (NSF GRFP), National Defense Science and Engineering Graduate Fellowship (NDSEG) and the Purdue Frederick N. Andrews Fellowship.

Publications (Peer-reviewed)

Ryan Rossi, Sonia Fahmy, and Nilothpal Talukder: A Multi-Level Approach for Evaluating Internet Topology Generators, Networking, pages 1-9, 2013. (To appear)   [ ] 

@inproceedings{rossi2013topology,
  title={A Multi-Level Approach for Evaluating Internet Topology Generators},
  author={Ryan A. Rossi and Sonia Fahmy and Nilothpal Talukder},
  booktitle={Networking},
  pages={1--9},
  year={2013}
}
Ryan A. Rossi, David F. Gleich, Assefaw H. Gebremedhin, Md. Mostofa Ali Patwary, A Fast Parallel Maximum Clique Algorithm for Large Sparse Graphs and Temporal Strong Components, (In Submission).   [ ] 

@article{rossi2013parallel-cliques,
  title={A Fast Parallel Maximum Clique Algorithm for Large Sparse Graphs 
    and Temporal Strong Components},
  author={Ryan A. Rossi and David F. Gleich and Assefaw H. Gebremedhin and 
    Mostofa A. Patwary},
  journal={arXiv preprint arXiv:1302.6256},
  pages={1--9},
  year={2013}
}
Ryan A. Rossi, David F. Gleich, Assefaw H. Gebremedhin, Triangle Core Decomposition and Maximum Cliques, SIAM Workshop on Network Science, 1-2, 2013.   [ ] 

@inproceedings{rossi2013trianglecores,
  title={Triangle Core Decomposition and Maximum Cliques},
  author={Ryan A. Rossi and David F. Gleich and Assefaw H. Gebremedhin},
  booktitle={SIAM Workshop on Network Science},
  pages={1--2},
  year={2013}
}
David F. Gleich, Ryan A. Rossi, A Dynamical System for PageRank with Time-Dependent Teleportation, (In Submission). [ ] 

@article{gleich2012dynamical,
  title={A Dynamical System for PageRank with Time-Dependent Teleportation},
  author={David F. Gleich and Ryan A. Rossi},
  journal={arXiv preprint arXiv:1211.4266},
  pages={1--30},
  year={2012}
}
Ryan Rossi, Brian Gallagher, Jennifer Neville, Keith Henderson: Modeling Dynamic Behavior in Large Evolving Graphs, In Proceedings of the Sixth ACM International Conference on Web Search and Data Mining (WSDM), pages 667-676, 2013.
[ ] 

@inproceedings{rossi2013modeling,
  title={Modeling Dynamic Behavior in Large Evolving Graphs},
  author={Ryan A. Rossi and Brian Gallagher and Jennifer Neville and 
    Keith Henderson},
  booktitle={WSDM},
  pages={667--676},
  year={2013}
}
Ryan Rossi, Luke K. McDowell, David W. Aha, Jennifer Neville: Transforming Graph Data for Statistical Relational Learning, Journal of Artificial Intelligence Research (JAIR), pages 363-441. AAAI Press, 2012. [ ] 

@article{rossi2012transforming,
  title={Transforming Graph Data for Statistical Relational Learning},
  author={Ryan A. Rossi and Luke K. McDowell and David W. Aha and 
    Jennifer Neville},
  journal={Journal of Artificial Intelligence Research (JAIR)},
  volume={45},
  pages={363--441},
  year={2012},
  publisher={AAAI Press}
}
Ryan Rossi and David Gleich: Dynamic PageRank using Evolving Teleportation, Algorithms and Models for the Web Graph, volume 7323 of Lecture Notes in Computer Science, pages 126-137. Springer, 2012.   [ ] 

@article{rossi2012dynamic,
  author = {Ryan A. Rossi and David F. Gleich},
  title = {Dynamic {PageRank} using Evolving Teleportation},
  booktitle = {Algorithms and Models for the Web Graph},
  year = {2012},
  editor = {Anthony Bonato and Jeannette Janssen},
  volume = {7323},
  series = {Lecture Notes in Computer Science},
  pages = {126--137},
  publisher = {Springer}
}
Ryan Rossi, Brian Gallagher, Jennifer Neville, Keith Henderson: Role-Dynamics: Fast Mining of Large Dynamic Networks, Proceedings of the 21st ACM International Conference Companion on World Wide Web (WWW), pages 997-1005, 2012.
[ ] 

@inproceedings{rossi2012role,
  title={Role-Dynamics: Fast Mining of Large Dynamic Networks},
  author={Ryan Rossi and Brian Gallagher and Jennifer Neville and 
    Keith Henderson},
  booktitle={Proceedings of the 21st International Conference Companion 
    on World Wide Web (WWW)},
  pages={997--1006},
  year={2012},
  organization={ACM}
}
Ryan Rossi and Jennifer Neville: Time-Evolving Relational Classification and Ensemble Methods, In Proceedings of the Pacific-Asia International Conference on Knowledge Discovery and Data Mining (PAKDD), LNCS 7301, pages 1-13. Springer, 2012.   [ ] 

@inproceedings{rossi2012dynamic-srl,
  title={Time-evolving Relational Classification and Ensemble Methods},
  author={Ryan Rossi and Jennifer Neville},
  booktitle={PAKDD},
  pages={1--13},
  year={2012},
  publisher={Springer}
}
Ryan Rossi and Jennifer Neville: Modeling the Evolution of Discussion Topics and Communication to Improve Relational Classification, In Proc. of the 1st SOMA Workshop, 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 89-97, 2010.   [ ] 

@inproceedings{rossi2010modeling,
  title={Modeling the Evolution of Discussion Topics and Communication
     to Improve Relational Classification},
  author={Ryan Rossi and Jennifer Neville},
  booktitle={SIGKDD SOMA},
  pages={89--97},
  year={2010}
}
Jean-Louis Lassez, Ryan A. Rossi, Axel E. Bernal: Crick's Hypothesis Revisited: The Existence of a Universal Coding Frame, IEEE International Conference on Bioinformatics and Life Science Computing, AINAW/BLSC, 745-751, 2007. Presented in the US, Russia, Japan, Thailand and Canada at various conferences and keynotes.
[ ] 

@inproceedings{rossi2007crick,
  title={Cricks Hypothesis Revisited: The Existence of a Universal
    Coding Frame},
  author={Jean-Louis Lassez and Ryan A. Rossi and Axel E. Bernal},
  booktitle={AINAW},
  volume={1},
  pages={745--751},
  year={2007}
}
Jean-Louis Lassez, Ryan Rossi, Kumar Jeev: Ranking Links on the Web: Search and Surf Engines, New Frontiers in Applied Artificial Intelligence (IEA/AIE), volume 5027 of Lecture Notes of Artificial Intelligence, pages 199-208. Springer, 2008.
[ ] 

@article{lassez2008ranking,
  title={Ranking Links on the Web: Search and Surf Engines},
  author={Jean-Louis Lassez and Ryan Rossi and Kumar Jeev},
  journal={New Frontiers in Applied Artificial Intelligence (IEA/AIE)},
  pages={199--208},
  year={2008},
  publisher={Springer}
}
Jean-Louis Lassez, Ryan Rossi, Stephen Sheel, Srinivas Mukkamala: Signature Based Intrusion Detection using Latent Semantic Analysis, IEEE International Joint Conference of Neural Networks, IJCNN, 1068-1074, 2008.   [ ] 

@inproceedings{lassez2008signature,
  title={Signature based Intrusion Detection using Latent Semantic Analysis},
  author={Jean-Louis Lassez and Ryan Rossi and Stephen Sheel and 
    Srinivas Mukkamala},
  booktitle={IJCNN},
  pages={1068--1074},
  year={2008}
}
John Stamey, Jean-Louis Lassez, Ryan Rossi, Daniel Boorn: Client-Side Dynamic Metadata in Web 2.0, Proceedings of the 25th ACM International Conference on Design of Communication, 155-161, 2007.   [ ] 

@inproceedings{stamey2007dynamic,
  title={Client-side Dynamic Metadata in Web 2.0},
  author={John Stamey and Jean-Louis Lassez and Daniel Boorn and Ryan Rossi},
  booktitle={Proceedings of the 25th annual ACM International Conference on 
    Design of Communication},
  pages={155--161},
  year={2007}
}
Ryan Rossi: Latent Semantic Analysis of the Languages of Life, ISICA, CCIS 51:128-137, 2009.   [ ] 

@article{rossi2009latent,
  title={Latent Semantic Analysis of the Languages of Life},
  author={Ryan A. Rossi},
  journal={Computational Intelligence and Intelligent Systems},
  pages={128--137},
  year={2009},
  publisher={Springer}
}
Mark W. Powell, Ryan A. Rossi, and Khawaja S. Shams: A Scalable Image Processing Framework for Gigapixel Mars and Other Celestial Body Images, IEEE Aerospace, 1-11, 2009.   [ ] 

@inproceedings{powell2010scalable,
  title={A Scalable Image Processing Framework for Gigapixel Mars and 
    Other Celestial Body Images},
  author={Mark W. Powell and Ryan A. Rossi and Khawaja S. Shams},
  booktitle={IEEE Aerospace},
  pages={1--11},
  year={2010}
}
Khawaja S. Shams, Mark W. Powell, Tom M. Crockett, Jeffrey S. Norris, Ryan Rossi, Tom Soderstrom: Polyphony: A Workflow Orchestration Framework for Cloud Computing, 10th IEEE/ACM Inter. Conf. on Cluster, Cloud and Grid Computing, CCGrid, 606-611, 2010. Also (Amazon AWS Case Study: NASA JPL’s Desert Research and Training [txt])   [ ] 

@inproceedings{shams2010polyphony,
  title={Polyphony: A Workflow Orchestration Framework for Cloud Computing},
  author={Khawaja S. Shams and Mark W. Powell and Tom M. Crockett and 
    Jeffrey S. Norris and Ryan Rossi and Tom Soderstrom},
  booktitle={10th IEEE/ACM International Conference on Cluster, Cloud and 
    Grid Computing (CCGrid)},
  pages={606--611},
  year={2010}
}
John Stamey, Ryan Rossi: Automatically Identifying Relations in Privacy Policies, Proceedings of the 27th ACM International Conference on Design of Communication, 233-238, 2009.   [ ] 

@inproceedings{stamey2009automatically,
  title={Automatically Identifying Relations in Privacy Policies},
  author={John W. Stamey and Ryan A. Rossi},
  booktitle={Proceedings of the 27th ACM International Conference on Design 
    of Communication},
  pages={233--238},
  year={2009}
}

Technical Reports

Ryan A. Rossi, David F. Gleich, Assefaw H. Gebremedhin, Md. Mostofa Ali Patwary, What if CLIQUE were fast? Maximum Cliques in Information Networks and Strong Components in Temporal Networks, (In Submission).   [ ] 

@article{rossi2012fastclique,
  title={What if CLIQUE were fast? Maximum Cliques in Information Networks 
    and Strong Components in Temporal Networks},
  author={Ryan A. Rossi and David F. Gleich and Assefaw H. Gebremedhin and 
    Mostofa A. Patwary},
  journal={arXiv preprint arXiv:1210.5802},
  pages={1--11},
  year={2012}
}
Ryan Rossi, Brian Gallagher, Jennifer Neville, and Keith Henderson: Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model, DOE Scientific and Technical Information, LLNL-TR-514271, 2011.   [ ] 

@inproceedings{rossi2011modeling,
  title={Modeling Temporal Behavior in Large Networks: A Dynamic 
    Mixed-Membership Model},
  author={Ryan Rossi and Brian Gallagher and Jennifer Neville and 
    Keith Henderson},
  booktitle={LLNL-TR-514271},
  year={2011},
  pages={1--10}
}
Ryan Rossi and Jennifer Neville: Representations and Ensemble Methods for Dynamic Relational Classification, CoRR abs/1111.5312, 2011.   [ ] 

@article{rossi2011representations,
  title={Representations and Ensemble Methods for Dynamic Relational 
    Classification},
  author={Ryan A. Rossi and Jennifer Neville},
  journal={arXiv preprint arXiv:1111.5312},
  pages={1--11},
  year={2011}
}
Ryan Rossi: Discovering Latent Graphs with Positive and Negative Links to Eliminate Spam in Adversarial Information Retrieval, NASA JPL 2009.
[ ] 

@inproceedings{rossi2009discovering,
  title={Discovering Latent Graphs with Positive and Negative Links 
    to Eliminate Spam},
  author={Ryan A. Rossi},
  booktitle={JPL Tech Report},
  year={2009},
  pages={1--9}
}

Posters

Ryan Rossi, Brian Gallagher, Jennifer Neville, and Keith Henderson, Modeling Dynamic Behavior in Large Evolving Graphs, WSDM, 2013.

Ryan Rossi, Brian Gallagher, Jennifer Neville, and Keith Henderson, Modeling Temporal Behavior in Large Networks: From Predictive Modeling to Anomaly Detection, ISCR Annual Research Symposium at LLNL, 2011.

Ryan Rossi and Jennifer Neville, Temporally-Evolving Network Classification, SIGKDD SOMA, 2010.


Past Research Activities

In the summer of 2011 I was at Lawrence Livermore National Laboratory (LLNL) working with Brian Gallagher on problems related to detecting anomalies and mining large temporal networks. I was supported through the LLNL Scholar (Cyber Defenders Program) part of the Computation Directorate. I presented a version of our Temporal Behavioral Model at LLNL and Purdue. [Poster][Presentation]

I previously visited the Naval Research Laboratory in Washington DC and worked with Dr. David Aha in the Navy Center for Applied Research in Artificial Intelligence and Dr. Luke McDowell of the United States Naval Academy. We focused on surveying approaches and opportunities for relational representation discovery. This lead us to introduce an intuitive taxonomy for relational representation discovery that formulates link discovery and node discovery as symmetric representation tasks (predicting their existence, predicting their label or type, estimating their weight or importance, and systematically discovering their relevant features). During my visit, I was supported by the NREIP Fellowship awarded by the Office of Naval Research (ONR).

The majority of my undergraduate studies were spent working with Dr. Jean-Louis Lassez (Retired IBM T.J. Watson Researcher) on many problems from machine learning, information retrieval, bioinformatics, security, and search engines.

Before attending Purdue, I was a research fellow (USRP, SURF, and Space Grant) at NASA Jet Propulsion Laboratory and California Institute of Technology working with Dr. Mark W. Powell on a Scalable Image Processing Framework for Gigapixel Mars Images. I also had the opportunity to work on extending this framework for Cloud Computing with Khawaja Shams (Amazon AWS Case Study: NASA JPL Desert Research and Training [txt]) and other members of the Planning Software Systems Group (within the Planning and Exploration Systems Mission Directorate).

During the summer of 2008, I worked with Dr. David Jensen and Brian Taylor at the University of Massachusetts Amherst in the Knowledge Discovery Laboratory (supported by the NSF REU Fellowship). The research investigated peer production and collaborative sensing systems in order to discover causal knowledge from these systems through sophisticated simulation techniques.

I also had the chance to work with Dr. Srinivas Mukkamala and jointly with Dr. Jean-Louis Lassez on problems of dimensionality reduction and real-time intrusion detection systems using a technique we designed based on Singular Value Decomposition and a simpler more robust version of Support Vector Machines (Summer 2007).



Research Experience

Research Assistant, Purdue University (2009-Present)
Advisor: Jennifer Neville, Research: Machine Learning, Statistical Relational Learning

Research Assistant, Lawrence Livermore National Laboratory (ISCR)
Advisor: Brian Gallagher, LLNL Scholar: Cyber Defenders Program (Summer 2011)

Research Assistant, Naval Research Laboratory, AI Research Center
Advisor: David Aha, Co-advisor: Luke McDowell, ONR NREIP Fellowship
Relational Representation Discovery in Statistical Relational Learning, (Summer 2010)

Research Assistant, Coastal Carolina University (2005-2009)
Advisor: Jean-Louis Lassez, Retired IBM T.J. Watson Research Center

Research Assistant, NASA Jet Propulsion Laboratory, (Summer 2009)
California Institute of Technology, Space Grant/USRP Fellowship
(Returned to continue my research).

Research Assistant, NASA Jet Propulsion Laboratory, (Spring 2009)
California Institute of Technology, USRP NASA Fellowship
Advisor: Mark Powell (Scalable Image Processing) and Khawaja Shams (Cloud Computing)

Research Assistant, University of Massachusetts at Amherst, KDL, (Summer 2008)
Advisor: David Jensen, Graduate Advisor: Brian Taylor, REU NSF Fellowship

Research Assistant, New Mexico Tech, Institute for Complex Additive Systems
Advisor: Srinivas Mukkamala, Senior Research Scientist, ICASA (Summer 2007)


Teaching Experience

Search Engine Theory, Instructor, Spring 2008
This course was taught from a machine learning perspective using a variety of resources and recent papers along with a series of homeworks and projects implementing the significant parts of a search engine.

Algorithms in Bioinformatics, Teaching Assistant, Fall 2007
Numerical Methods, Teaching Assistant, Spring 2007
Introduction to Bioinformatics, Teaching Assistant, Fa 2008, Fa/Spr 2007, Spr 2006
Introduction to Algorithm Design II, Teaching Assistant, Spring 2006
Introduction to Algorithm Design I, Teaching Assistant, Spring 2006

As a teaching assistant I gave lectures and review sessions; developed homeworks, labs, and programs, held office hours, and maintained course website.


Books / Lecture Notes

Bioinformatics is the application of computational techniques and tools to analyze and manage biological data. This book provides an Introduction to Bioinformatics through the use of Action Labs. These labs allow students to get experience using real data and tools to solve difficult problems. The book comes with supplementary powerpoints, papers, and tools. The labs use data from Breast Cancer, Liver Disease, Diabetes, SARS, HIV, Extinct Organisms, and many others. The book has been written for first or second year computer science, mathematics, and biology students. The book is published by the Digital University Press. [pdf version] (6.2 MB)