Hassan H. Malik
I was a PhD student in the Department of Computer Science at Columbia University in New York City, advised by Professor Professor John Kender. He is a great teacher!
My PhD research focused on investigating novel techniques to mine, cluster, and classify high-dimensional data, with a focus on document and image collections. I now work as Senior Technical Specialist - Text Processing Systems at Thomson Reuters in NYC, where I conduct data mining and machine learning research for various text processing applications. Prior to joining Thomson Reuters, I was a Research Scientist in the Integrated Data Systems department at Siemens Corporate Research in Priceton, NJ. In the past, I managed a large engineering team at Liberty Travel (now Flight Center) in Mahwah NJ, and also worked as a senior member of enginering team at Tibco Software in Palo Alto, CA.
Publications:
- Dejori, M., Malik, H.H., Morchen, F., Tas, N.C., and Neubauer, C.,
"Development of Data Infrastructure for the Long Term Bridge Performance Program",
To Appear In Proceedings of Structures Congress '09, Austin, Texas, USA. - Malik, H.H., and Kender,
J.R.,
"Classifying High-Dimensional Text and Web Data using Very Short Patterns",
In Proceedings of the IEEE International Conference on Data Mining (ICDM 2008), Pisa, Italy. (Full paper as TR-046-08) - Malik, H.H., and Kender,
J.R.,
"Instance Driven Hierarchical Clustering of Document Collections",
In From Local Patterns to Global Models Workshop (ECML/PKDD 2008), Antwerp, Belgium. (pdf) - Malik, H.H., and Kender,
J.R.,
"Classification by Pattern-Based Hierarchical Clustering",
In From Local Patterns to Global Models Workshop (ECML/PKDD 2008), Antwerp, Belgium. (pdf) - Malik, H.H., and Kender,
J.R.,
"Optimizing Frequency Queries for Data Mining Applications",
In Proceedings of the IEEE International Conference on Data Mining (ICDM 2007), Omaha, Nebraska, USA. (Full paper as TR-026-07) - Malik, H.H., and Kender,
J.R.,
"High Quality, Efficient Hierarchical Document Clustering using Closed Interesting Itemsets",
In Proceedings of the IEEE International Conference on Data Mining (ICDM 2006), Hong Kong. (Full paper as TR-046-06) - Malik, H.H., and Kender,
J.R.,
"Clustering web images using association rules, interestingness measures, and hypergraph partitions",
In Proceedings of the 6th international conference on Web engineering (ICWE 2006), Palo Alto, California, USA. (pdf) (Dataset1) (Dataset2)
Thesis:
- Malik, H.H.,
"Efficient Algorithms for Clustering and Classifying High Dimensional Text and Discretized Data using Interesting Patterns",
PhD Thesis. (pdf)
Phone: (650-283-5054)