Sitaram Asur   

Department of Computer Science                                                                Phone : (614) 292 1151 

The Ohio State University                                                                             Mobile : (614) 218 3631 

674 Dreese Labs, 2015 Neil Ave                                                             Email : asur {at} cse.ohio-state.edu 

Columbus, OH 43210                                                                             Web: www.cse.ohio-state.edu/~asur

Education 

• The Ohio State University                                                         Columbus, OH              PhD in Computer Science and Engineering                                                Sep. 2003 - present

• Visveswaraiah Technological University                                              Bangalore, India          Bachelor of Engineering, Information Science Engineering                              1998 - 2002

Research Interests

   Data Mining, Machine Learning and their applications to Social Networks, Web and Bioinformatics. In
   particular, I am interested in developing algorithms for mining static and dynamic (evolving) interaction
   networks.

Professional and Academic Experience

The Ohio State University Columbus, OH

• Post : Graduate Research Associate                                                            June 2005 - present 

  Supervisor: Dr. Srinivasan Parthasarathy 

  Relevant Projects :

• Functional Clustering of Interaction Networks: The objective here is to extract       useful modules or clusters from real-world interaction networks. In Protein-protein interaction (PPI) networks, the discovery of key functional modules can help understand the functions of proteins and also aid in predicting the function of unknown (un-annotated) proteins. Traditional clustering/graph partitioning algorithms have not performed well in this task due to the presence of a) noisy false positive interactions b) scale-free topology, and c) multi-faceted hub nodes.
  I have developed efficient techniques focusing on the topological properties of these networks to eradicate noise and discover functionally relevant clusters. I have also examined the use of ensemble clustering for this purpose, with successful results. Parts of this ongoing work have been published in BIBE 2005, PKDD 2006, Link-KDD 2006 and ISMB 2007. Although in these papers, I have focused on PPI networks, these challenges and techniques are applicable to several other real-world interaction networks.
• Evolutionary Analysis of Dynamic Interaction Networks: The goal here is to study
  evolving real-world interaction networks, such as social networks, WWW networks and biological networks (gene-expression timeseries networks). Identifying the portions of the network that are changing, characterizing the type of change, predicting future events (link prediction), and developing generic models for evolving networks are critical challenges that I am looking to address. I have been working on developing a general framework for characterizing evolution, quantifying behavior and performing temporal reasoning on dynamic networks. An initial part of this work will be published in the proceedings of SIGKDD 2007 and has also secured the Best Paper Award in the Applications category.
• Mining Protein Crystallization Trials: The goal here is to predict novel crystallization
  conditions based on earlier crystallization results. The key challenges are a) The training     data consists of mostly negative samples (corresponding to unsuccessful crystallization trials) b) the conditions have been sampled from only a few regions in the crystallization space. To overcome these challenges, I have proposed a model-based approach using an ensemble of classifiers to handle the bias in the training data and an incremental stratified sampling approach to predict novel crystallization parameters. This work was published at ISMB 2006 and in the Journal of Bioinformatics.                                                                                                                                                                                                                                         
• Post : Graduate Teaching Associate                                                             Sep 2004 - May 2005
• Course Instructor : Introduction to Computer Science (CSE100).
• Teaching Associate :
• Introduction to Neural Networks (CSE 779)
• Introduction to Data Mining (CSE 694)

Oracle India Pvt Ltd Hyderabad, India

Post : Applications Development Engineer                                                                   Mar - July 2003

Developed Business Intelligence Software for Management Applications using the oracle 9i advanced concepts of materialized views

Indian Institute of Science Bangalore,India

Post : Student Intern                                                                                                Oct 2002 - Jan 2003

Developed an Expert System intended for Customer Relationship Management (CRM) Applications

Indian Space Research Organization (ISRO) Bangalore, India

Post : Student Intern                                                                                               Apr 2002 - July 2002

Was part of a group that developed a Real Time System to automate the process of temperature scheduling for satellite thrusters

Publications

Journal Articles

• S. Asur, D. Ucar and S. Parthasarathy. An Ensemble Framework for Clustering Protein-Protein Interaction Networks. (To appear) In Bioinformatics.
• S. Asur, P. Raman, M. Otey and S. Parthasarathy.A Model-based Approach for Mining Membrane Protein Crystallization Trials.Bioinformatics, Volume 22(14), e40-e48. July 2006.

Conference and Workshops

• S. Asur, S. Parthasarathy and D. Ucar. An Event-based Framework for Characterizing the Evolutionary Behavior of Interaction Graphs. In the Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (SIGKDD), 2007.
• S. Asur, D. Ucar and S. Parthasarathy. An Ensemble Framework for Clustering Protein-Protein Interaction Networks. In the Proceedings of the 15th Annual International Conference on Intelligent Systems (ISMB), 2007.
• D. Ucar, S. Parthasarathy and S. Asur, Novel Pre-processing Techniques to Improve Functional Modularity in Protein-Protein Interaction Graphs, 13th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2007 (Poster paper)
• D. Ucar, S. Asur, U. Catalyurek and S. Parthasarathy. Improving Functional Modularity in Protein-Protein Interactions Graphs Using Hub-induced Subgraphs. In the Proceedings of the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), 2006.
• S. Asur, S. Parthasarathy and D. Ucar, An Ensemble Approach for Clustering Scale-Free Graphs. In the Proceedings of the LinkKDD workshop at the ACM International Conference on Knowledge Discovery and Data Mining (LinkKDD), 2006.
• S. Asur, P. Raman, M. Otey and S. Parthasarathy. A Model-based Approach for Mining Membrane Protein Crystallization Trials. In the proceedings of the 14th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), 2006.

• D. Ucar, S. Parthasarathy, S. Asur and C. Wang, Effective Pre-processing Strategies for Functional Clustering of a Protein-Protein Interactions Network. In the Proceedings of the IEEE 5th Symposium on Bioinformatics and Bioengineering (BIBE), 2005.

Presentations

• An Event-based Framework for Characterizing the Evolutionary Behavior of Interaction Graphs. At the 13th ACM SIGKDD International Conference on Knowledge Discovery and DataMining (SIGKDD 2007), San Jose, USA, Aug 2007.
• An Ensemble Framework for Clustering Protein-Protein Interaction Networks. At the15th Annual International Conference on Intelligent Systems for Molecular Biology(ISMB 2006),Vienna, Austria, July 2007.
• Detecting Hepatotoxicity in Clinical Trials Data : An Anomaly Detection Approach. Atthe 30th Annual Midwest Biopharmaceutical Statistics Workshop (MBSW 2007), Muncie, Indiana,USA, May 2007.
• An Ensemble Approach for Clustering Scale-free Graphs. At the Workshop on Link Analysis: Dynamics and Static of Large Networks at the ACM International Conference on KnowledgeDiscovery and Data Mining (SIGKDD 2006), Philadelphia, USA, August 2006.
• A Model-based Approach for Mining Membrane Protein Crystallization Trials. At the14th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2006), Fortaleza, Brazil, August 2006.
  

School Projects

• Developed a spam detector for Pine using Decision Trees.
• Developed a Virtual Tour application using Hand Gesture Recognition.
• Developed a Search Engine using Face Recognition.
• Developed a LISP Interpreter using Java.
  
  

Skills

• Languages: C/C++, LATEX, Java, VB, Perl, Lisp, SQL, Parallel Programming (MPI, OpenMP),
  Assembly programming (x86).
• Operating Systems: Linux, Solaris, UNIX, Windows 95/98/NT/2000/XP
  Applications: MatLab, MS O.ce XP
• Academic Background: Data Mining, Machine Learning, Advanced Computer Architecture, Ad-
  vanced Operating Systems, Neural Networks, Algorithms, Databases, Parallel Computing, Dis-
  tributed Systems, Compilers/Programming Languages and Computer Networking                                        

Awards

• Best Application Paper Award - SIGKDD                                                                         2007
  
• Travel Fellowship to attend SIGKDD conference                                                             2007
• Travel Fellowship to attend ISMB conference                                                                 2007
• Travel Fellowship to attend ISMB conference                                                                 2006
• University Fellowship (Ohio State University)                                                           2003-2004
• Graduate Teaching Assistantship (Ohio State University)                                         2004-2005
• Graduate Research Assistantship (Ohio State University)                                         2005-present
• University Rank 7 in B.E. (Visveswaraiah Technological University)                              2002
  out of students from 110 a.liated engineering colleges
• Undergraduate Scholarship and Tuition Fee Waiver                                                  1998-2002
  (Visveswaraiah Technological University)
  

Professional Activities

Reviewer for:

• IEEE Symposium on Bioinformatics and Bioengineering (BIBE) - 2005. 
• ICDM Temporal Data Mining (TDM) Workshop - 2005.
• ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD) - 2006, 2007.
• 2nd International Symposium on Computational Life Science (CompLife) - 2006.
• IEEE International Conference on Data Mining (ICDM) - 2005, 2006. 
• ACM SIGMOD International Conference on Management of Data (SIGMOD) - 2007. 
• Conference on Information and Knowledge Management (CIKM) - 2007.
  

References

• Dr. Srinivasan Parthasarathy, Associate Professor.
  Dept. of Computer Science and Engineering, The Ohio State University.
  2015 Neil Avenue, 395 DL, Columbus OH 43210.
  srini@cse.ohio-state.edu, 614-292-2568.
• Dr. Hakan Ferhatosmanoglu, Assistant Professor.                                                                           Dept. of Computer Science and Engineering, The Ohio State University.                                              2015 Neil Avenue, 395 DL, Columbus OH 43210.                                                hakan@cse.ohio-state.edu, 614-292-6377.