I am broadly interested in algorithmic and applied aspects of data mining and computational biology. Specifically, for my masters degree I worked on algorithms for recommendation systems which predict user preferences by learning past user-item relationships. I am also interested in combinatorial problems that arises in computational biology and have worked on disk-based suffix tree algorithms for handling genome-scale strings. Besides these, I participated in research on some fundamental problems of data mining such as high dimensional spatial data clustering and high dimensional k-nn computation. Finally, my thesis topic is on indexing directed graphs for efficiently answering reachability queries.

In recent years, my research focus is on indexing directed graphs for efficiently answering reachability queries. These queries are basically asking whether given two nodes are connected. In many real graphs, testing reachability between two nodes corresponds to an important problem. For example, in protein-protein interaction networks one can use it to answer whether two proteins are related, whereas in ontological databases such queries might correspond to the question of whether a concept subsumes another one. Given the huge databases that are often tested with reachability queries, it is an important problem to come up with a scalable indexing scheme that has almost constant query time. We developed a highly scalable labeling scheme which outperforms all of the existing methods in very large real graph data such as UniProt RDF graph or CiteSeerX citation graph.

Grail Project Page

Vineet Chaoji, Geng Li, Hilmi Yildirim and Mohammad J. Zaki : "ABACUS: Mining Arbitrary Shaped Clusters from Large Datasets based on Backbone Identification", SIAM Data Mining (SDM 2011) (Mesa, Arizona USA, April 27-29, 2011)

Mohammad AlHasan, Hilmi Yildirim and Ahbirup Chakraborty : "SONNET: Efficient Approximate Nearest Neighbor using Multi-Core", 10th IEEE International Conference on Data Mining (ICDM 2010) (Sydney, Australia, December 14-17, 2010)

Hilmi Yildirim, Vineet Chaoji and Mohammad J. Zaki : "GRAIL: Scalable Reachability Index for Large Graphs", Proceedings of the VLDB Endowment (36th International Conference on Very Large Data Bases, Singapore, September 13-17, 2010), 3(1):-. 2010 [slides]

Hilmi Yildirim : "Graph Indexing for Reachability Queries", 26th IEEE International Conference on Data Engineering Phd Workshop, Long Beach, California, March 6, 2010

Hilmi Yildirim and Mukkai S. Krishnamoorthy : "A Random Walk Method for Alleviating the Sparsity Problem in Collaborative Filtering", 2nd ACM International Conference on Recommender Systems, Lausanne, Switzerland, October 23-25, 2008

Hilmi Yildirim, Mukkai S. Krishnamoorthy, and Narsingh Deo : "A Study of the Sudoku Graph Family", Thirty-Ninth Southeastern International Conference on Combinatorics, Graph Theory, and Computing, Boca Raton, USA, March 3-7, 2008 [slides]

MS Thesis: "A Random Walk Method For Handling Sparse Training Set In Collaborative Filtering" ,Department of Computer Science, Rensselaer Polytechnic Institute, December 2007