Assistant Professor Office: MCS264/(330)672-9063 Computer Science Department, Kent State University

Email: jin@cs.kent.edu http://www.cs.kent.edu/˜jin

Ruoming Jin

Research Interests

Data Mining, Complex Network Analysis, BioMedical Informatics, Databases, and High Performance Computing.

Education

Ph.D. (2005) in Computer Science CSE Dept., Ohio State University Dissertation: New Techniques for Efficiently Discovering Frequent Patterns

M.S. (2001) in Computer Science CIS Dept., University of Delaware

M.E. (1999), B.E. (1996) in Computer Engineering CSE Dept., Beihang University, China

Research and Work Experience

  • Assistant Professor, Aug. 2005 -Present Computer Science Department (CS) , Kent State University

  • Research Assistant, Sep. 2002 -Aug. 2005 Department of Computer Science and Engineering (CSE), The Ohio State University

  • Research Scientist, Aug. 2001 -Sep. 2002 Department of Computer Science and Engineering (CSE), The Ohio State University

  • Research Assistant, Aug. 1999 -July 2001 Computer Information Science Department (CIS), University of Delaware

Representative Publications

  1. Identify Dynamic Network Modules with Temporal and Spatial Constraints, Ruoming Jin, Scott McCallen, Chun-Chi Liu, Yang Xiang, Eivind Almaas, and Xianghong Jasmine Zhou, in the Proceedings of Pacific Symposium on Biocomputing (PSB’09).

  2. Overlapping Matrix Pattern Visualization: a Hypergraph Approach, Ruoming Jin, Yang Xiang, Dave Fuhry, and Feodor Dragan, in Prof. of IEEE International Conference on Data Mining (ICDM’08).

  3. Effective and Efficient Itemset Pattern Summarization: Regression-based Approaches, Ruoming Jin,Muad Abu-Ata, Yang Xiang, and Ning Ruan, in Proc. of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’08), August, 2008.

  4. Succinct Summarization of Transactional Databases: an Overlapped Hyperrectangle Scheme,Yang Xiang, Ruoming Jin, Dave Fuhry, and Feodor Dragan, in the Proc. of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’08), August, 2008.

  5. Efficiently Answering Reachability Query on Very Large Directed Graphs, Ruoming Jin,Yang Xiang,Ning Ruan, and Haixun Wang, in the Proc. of ACM SIGMOD conference (SIGMOD’08), June, 2008.

  6. Data Discretization Unification, Ruoming Jin, Yuri Breitbart, and Chibuike Muoh, in the Proc. of the IEEE International Conference on Data Mining (ICDM’07), Oct. 2007.

  7. Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks, Ruoming Jin,Scott McCallen, and Eivind Almaas, in the Proc. of the Seventh IEEE International Conference on Data Mining (ICDM’07), Oct. 2007.

  8. A Systematic Approach for Optimizing Complex Mining Tasks on Multiple Databases, Ruoming Jin and Gagan Agrawal, in the Proc. of 22nd International Conference on Data Engineering (ICDE’06), April 2006.

  9. Shared Memory Parallelization of Data Mining Algorithms: Techniques, Programming Interface, and Performance, Ruoming Jin, Ge Yang, and Gagan Agrawal, in the IEEE Transactions on Knowledge & Data Engineering (TKDE), Vol. 17, No. 1, January, 2005
  10. Performance Prediction for Random Write Reduction: A Case Study in Modeling Shared Memory Programs, Ruoming Jin and Gagan Agrawal, in ACM Sigmetrics (SIGMETRICS’02), 2002.

Complete Publication List

Book Chapters and Journal Papers

  1. Data Discretization Unification, Ruoming Jin, Yuri Breitbart, and Chibuike Muoh, accepted in Knowledge and Information System (KAIS journal).

  2. Middleware for Data Mining Applications on Clusters and Grids, Leonid Glimcher, Ruoming Jin, Gagan Agrawal, Journal of Parallel and Distributed Computing (JPDC), 68(1): 37-53 (2008).

  3. Frequent Pattern Mining in Data Streams, Ruoming Jin, Gagan Agrawal, book chapter in Data Streams: Models and Algorithms, Ed. Charu Aggrawal, Spinger, 2007.

  4. Fast and Exact Out-of-Core and Distributed K-Means Clustering, Ruoming Jin, Anjan Goswami, and Gagan Agrawal, in Knowledge and Information System (KAIS journal), 10(1): 17-40 (2006) .

  5. Communication and Memory Optimal Parallel Data Cube Construction, Ruoming Jin, Karthik Vaidyanathan, Ge Yang, and Gagan Agrawal, in the IEEE transactions on Parallel and Distributed Systems (TPDS), 16(12): 1105-1119 (2005).

  6. A Methodology for Detailed Performance Modeling of Reduction Computations on SMP Machines, Ruoming Jin and Gagan Agrawal, in Performance Evaluation, Vol. 60(1-4), p. 73-105, 2005.

  7. Shared Memory Parallelization of Data Mining Algorithms: Techniques, Programming Interface, and Performance, Ruoming Jin, Ge Yang, and Gagan Agrawal, in the IEEE Transactions on Knowledge & Data Engineering (TKDE), Vol. 17, No. 1, January, 2005

  8. Implementing Data Cube Construction Using a Cluster Middleware: Algorithms, Implementation Experience, and Performance Evaluation, Ge Yang, Ruoming Jin, and Gagan Agrawal, in Future Generation Computer Systems (FGCS), v. 19, i. 4, p. 533 -550, 2003 .

  9. Research on Static Prediction and Visual Analysis of Program Execution Time, Changai Sun, Maozhong Jin, Chao Liu, and Ruoming Jin, Journal of Software (Chinese), Vol. 14, No. 1, 2003, p: 68-75.

  10. Testing Technology of Real-time and Embedded Software, Changai Sun, Ruoming Jin, Chao Liu, and Maozhong Jin, Journal of Mini Micro Systems (Chinese), Vol. 21, No. 9, 2000, p: 920-924.

Conference and Referred Workshop Papers

  1. Identify Dynamic Network Modules with Temporal and Spatial Constraints, Ruoming Jin, Scott McCallen, Chun-Chi Liu, Yang Xiang, Eivind Almaas, and Xianghong Jasmine Zhou, in the Proceedings of Pacific Symposium on Biocomputing (PSB’09).

  2. A Study on Frequent Co-Expression Networks in Cancers, Yang Xiang, Jie Zhang, Ruoming Jin,and Kun Huang, accepted for oral presentation in the AMIA Summit on Translational Bioinformatics, 2009.

  3. Estimating the Number of Frequent Itemsets in a Large Database, Ruoming Jin, Scott Mccallen, and Yuri Breitbart, to appear in the Proceedings of 12th International Conference on Extending Database Technology (EDBT’09).

  4. Efficient Skyline Computation in Metric Space, Dave Fuhry, Ruoming Jin, and Donghui Zhang, to appear in the Proceedings of 12th International Conference on Extending Database Technology (EDBT’09).

  5. Overlapping Matrix Pattern Visualization: a Hypergraph Approach, Ruoming Jin, Yang Xiang, Dave Fuhry, and Feodor Dragan, to appear in International Conference on Data Mining (ICDM’08), (Full Paper, Acceptance rate: 9.7%).

  6. A Topic Modeling Approach and its Integration into the Random Walk Framework for Academic Search,Jie Tang, Ruoming Jin, Jing Zhang, to appear in International Conference on Data Mining (ICDM’08) (Short Paper, Acceptance rate: 19.9%).

  7. Effective and efficient itemset pattern summarization: regression-based approaches, Ruoming Jin, Muad Abu-Ata, Yang Xiang, and Ning Ruan, in the Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’08), August, 2008, Pages 399-407 (Full Paper, Acceptance rate: 18.5%).

  8. Succinct summarization of transactional databases: an overlapped hyperrectangle scheme,Yang Xiang, Ruoming Jin, Dave Fuhry, and Feodor Dragan, in the Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’08), August, 2008, Pages 758-766 (Full Paper, Acceptance rate: 18.5%).

  9. Efficiently Answering Reachability Query on Very Large Directed Graphs, Ruoming Jin,Yang Xiang,Ning Ruan, and Haixun Wang, in the Proceedings of ACM SIGMOD conference (SIGMOD’08), June, 2008, Pages 595-608 (Full Paper, Acceptance rate: 18%).

  10. Query Planning for Searching Inter-dependent Deep-Web Databases, Fan Wang, Gagan Agrawal, and Ruoming Jin, in the Proceedings of 20th International Conference on Scientific and Statistical Database Management (SSDBM’08), July, 2008, pages 24-41 (Full Paper, Acceptance rate: 34.5%).

  11. Cost-Based Query Optimization for Complex Pattern Mining on Multiple Databases, Ruoming Jin, Dave Fuhry, and Abdulkareem Alali, in the Proceedings of 11th International Conference on Extending Database Technology (EDBT’08), March, 2008, pages 380-391 (Full Paper, Acceptance rate: 17.5%).

  12. Data Discretization Unification, Ruoming Jin, Yuri Breitbart, and Chibuike Muoh, in the Proc. of the Seventh IEEE International Conference on Data Mining (ICDM’07), Oct. 2007 (Full Paper, Acceptance rate: 7%, received two best paper nomination).

  13. Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks, Ruoming Jin,Scott McCallen, and Eivind Almaas, in the Proc. of the Seventh IEEE International Conference on Data Mining (ICDM’07), Oct. 2007 (Short Paper, Acceptance rate: 19%).

  14. SNPMiner: A Domain-Specific Deep Web Mining Tool, Fan Wang, Gagan Agrawal, Ruoming Jin,and Helen Piontkivska. in IEEE 7th Symposium in Bioinformatics and Bioengineering (BIBE), Oct. 2007 (Acceptance rate: 13%).

  15. Graph and Topological Structure Mining on Scientific Articles,Fan Wang, Ruoming Jin, Gagan Agrawal, and Helen Piontkivska. in IEEE 7th Symposium in Bioinformatics and Bioengineering (BIBE), Oct. 2007 (Acceptance rate: 13%).

  16. Assigning Schema Labels Using Ontology and Heuristics, Xuan Zhang, Ruoming Jin, and Gagan Agrawal, in IEEE 6th Symposium in Bioinformatics and Bioengineering (BIBE), Oct. 2006.

  17. Exploratory Tools for Follow-Up Studies to Microarray Experiments, Kaushik Sinha, Ruoming Jin, Gagan Agrawal, and Helen Piontkivska, in IEEE 6th Symposium in Bioinformatics and Bioengineering (BIBE), Oct. 2006.

  18. FREERIDE-G: Supporting Applications that Mine Remote FREERIDE-G: Supporting Applications that Mine Remote, Leo Glimcher, Ruoming Jin, and Gagan Agrawal, in the Proc. of International Conference on Parallel Processing (ICPP), August 2006.

  19. A New Robust Estimation Technique for Approximate Processing of OLAP Queries, Ruoming Jin, Leo Glimcher, Chris Jermaine, and Gagan Agrawal, in the Proc. of 22nd International Conference on Data Engineering (ICDE), April 2006.

  20. A Systematic Approach for Optimizing Complex Mining Tasks on Multiple Databases, Ruoming Jin and Gagan Agrawal, in the Proc. of 22nd International Conference on Data Engineering (ICDE), April 2006.

  21. A Decomposition-Based Probabilistic Framework for Estimating the Selectivity of XML Twig Queries,Chao Wang, Srinivasan Parthasarath, and Ruoming Jin, in the Proc. of 10th International Conference on Extending Database Technology (EDBT), March 2006.

  22. An Algorithm for In-Core Frequent Itemset Mining on Streaming Data, Ruoming Jin and Gagan Agrawal, in the Proc. of the Fifth IEEE International Conference on Data Mining (ICDM), Nov. 2005.

  23. Using Data Mining Techniques to Learn Layouts of Flat-File Biological Datasets, Kaushik Sinha, Xuan Zhang, Ruoming Jin, and Gagan Agrawal, in the IEEE 5th Symposium on Bioinformatics & Bioengineering (BIBE), Oct. 2005.

  24. Simultaneous Optimization of Complex Mining Tasks with a Knowledgeable Cache, Ruoming Jin,Kaushik Sinhak, and Gagan Agrawal, in the Proc. of 11th International Conference on Knowledge Discovery and Data Mining (SIGKDD), Aug. 2005.

  25. Discovering Frequent Topological Patterns from Graph Datasets, Ruoming Jin, Chao Wang, Dmitrii Polshako, Srinivasan Parthasarathy, Gagan Agrawal, in the Proc. of 11th International Conference on Knowledge Discovery and Data Mining (SIGKDD), Aug. 2005.

  26. A Framework to Support Multiple Query Optimization for Complex Mining Tasks, Ruoming Jin,Kaushik Sinhak, and Gagan Agrawal, in the Sixth International Workshop on Multimedia Data Mining in conjunction with KDD (MDM/KDD2005), Aug. 2005.

  27. Learning Layouts of Biological Datasets Semi-Automatically, Kaushik Sinha, Xuan Zhang, Ruoming Jin,and Gagan Agrawal, in the Proc. of 2nd International Workshop on Data Integration in the Life Sciences (DILS), Jul. 2005.

  28. Parallelizing a Defect Detection and Categorization Application, Leo Glimcher, Gagan Agrawal, Sameep Mehta, Ruoming Jin, and Raghu Machiraju, in the Proc. of International Parallel and Distributed Processing Symposium (IPDPS), April 2005

  29. Fast and Exact Out-of-Core K-Means Clustering, Anjan Goswami, Ruoming Jin, and Gagan Agrawal, in the Proc. of International Conference on Data Mining (ICDM), Nov. 2004.

  30. Using Tiling to Scale Parallel Data Cube Construction, Ruoming Jin, Karthik Vaidyanathan, Ge Yang, and Gagan Agrawal, in the Proc. of International Conference on Parallel Processing (ICPP), August 2004.

  31. Parallel Data Cube Construction: Algorithms, Theoretical Analysis, and Experimental Evaluation, Ruoming Jin, Ge Yang, and Gagan Agrawal, in the Prof. of 10th International Conference on High Performance Computing (HiPC), Dec. 2003.

  32. Efficient Decision Tree Construction on Streaming Data, Ruoming Jin and Gagan Agrawal, in the Proc. of 9th International Conference on Knowledge Discovery and Data Mining (SIGKDD), Aug. 2003.

  33. Communication and Memory Optimal Parallel Data Cube Construction, Ruoming Jin, Ge Yang, Gagan Agrawal, and Karthik Vaidyanathan, in the Proc. of International Conference on Parallel Processing (ICPP), Aug. 2003.

  34. Communication and Memory Efficient Parallel Decision Decision Tree Construction, Ruoming Jin and Gagan Agrawal, in the Third SIAM International Conference on Data Mining (SDM), May 2003.

  35. Combining Distributed Memory and Shared Memory Parallelization for Data Mining Algorithms, Ruoming Jin and Gagan Agrawal, in the 6th International Workshop on High Performance Data Mining: Pervasive and Data Stream Mining (HPDM:PDS’03) in conjunction with SDM, April 2003.

  36. A Compilation Framework for Distributed Memory Parallelization of Data Mining Algorithms, Xiaogang Li, Ruoming Jin, and Gagan Agrawal, in the Proc. of International Parallel and Distributed Processing Symposium (IPDPS), May, 2003.

  37. Impact of Data Distribution, Level of Parallelism and Communication Frequency on Parallel Data Cube Construction, Ge Yang, Ruoming Jin, and Gagan Agrawal, in the Proc. of International Parallel and Distributed Processing Symposium (IPDPS), May, 2003.

  38. Compiler and Runtime Support for Shared Memory Parallelization of Data Mining Algorithms, Xiaogang Li, Ruoming Jin, and Gagan Agrawal, in the Proc. of Languages and Compilers for Parallel Computing (LCPC), 2002.
  39. Shared Memory Parallelization of Decision Tree Construction Using a General Data Mining Middleware, Ruoming Jin and Gagan Agrawal, in the Proc. of EuroPar (EuroPar), 2002.
  40. Performance Prediction for Random Write Reduction: A Case Study in Modeling Shared Memory Programs, Ruoming Jin and Gagan Agrawal, in ACM Sigmetrics (SIGMETRICS), 2002.
  41. Implementing Data Cube Construction Using a Cluster Middleware: Algorithms, Implementation Experience, and Performance Evaluation, Ge Yang, Ruoming Jin, and Gagan Agrawal, in 2nd IEEE International Symposium on Cluster Computing and the Grid (CCGrid), 2002.
  42. Shared Memory Parallelization of Data Mining Algorithms: Techniques, Programming Interface, and Performance, Ruoming Jin and Gagan Agrawal, in Second SIAM International Conference on Data Mining (SDM), 2002.
  43. Compiler and Middleware Support for Scalable Data Mining, Gagan Agrawal, Ruoming Jin, and Xiaogang Li, in 9th Workshop on Compilers for Parallel Computers, June 2001.
  44. An Efficient Association Mining Implementation on Cluster of SMPs, Ruoming Jin and Gagan Agrawal, in 4th International Workshop on Parallel and Distributed Data Mining, April 2001.

  45. A Middleware for Developing Parallel Data Mining Applications, Ruoming Jin and Gagan Agrawal, in First SIAM International Conference on Data Mining (SDM), April 2001.

  46. Compiling Data Intensive Applications with Spatial Coordinates, Renato Ferreira, Gagan Agrawal, Ruoming Jin, and Joel Saltz, in Proc. of Languages and Compilers for Parallel Computing (LCPC), 2000.

  47. High-level Programming Methodologies for Data Intensive Computing, Gagan Agrawal, Renato Ferreira, Joel Saltz, and Ruoming Jin, in Proc. of Languages, Compilers and Runtime Systems for Scalable Machines, 2000.

Papers Under Review or In-Preparation

  1. Dynamic Module Discovery in Temporal Complex Networks, Ruoming Jin, Ning Ruan, Scott McCallen, and Victor Lee, in submission.

  2. Multi-Source Omni-View Cooperative Learning,Xingquan Zhu, Ruoming Jin, in submission.

  3. Supervised Multivariate Data Discretization: A Tale of Two Classifiers, Ning Ruan, Ruoming Jin,and Yuri Breitbart, in preparation.

Invited Talks and Colloquium

  1. Efficiently Answering Reachability Query on Very Large Directed Graphs, presentation at SIGMOD’08 (June 2008), invited talk at College of Information Sciences and Technology, Penn State (Oct. 2008), Department of Computer Science, Oakland University (Sep. 2008), Beihang University, IBM China Research Lab, AOL Beijing Research Lab (July, 2008).

  2. Database Supports for Efficient Frequent Pattern Mining, invited talk at IBM T.J. Watson Research Center (May, 2008), Colloquium at Department of Computer Science, Wayne State University (March, 2008), invited talk at Max-Planck-Institut fcken, Germany, (August, 2007).

  3. Scalable Data Mining: System Support and Algorithms, invited talk at Beihang University and Mathematics and Systems Institute of Chinese Academy of Sciences, June, 2007.

  4. Towards a Systematic Approach for Genome-Wide Rice Gene Annotation, invited talk on the 3rd Rice Annotation Project Meeting (RAP3), Tsukuba, Japan, Dec. 9-10, 2006.

  5. Frequent Pattern Mining: Algorithms, Research Issues, and Applications, talk at Department of Computer Science, Kent State University, Nov. 2005.

  6. Scalable Data Mining: System Support and Algorithms, talk at IBM T.J. Watson, Dec. 2004.

  7. Efficiently and Accurately Mining Out-of-Core Datasets by Sampling, talk at CMU AutonLab, Aug. 2004

  8. A Systematic Approach to Mine Multiple Datasets, Ruoming Jin, System Group Seminar, OSU, April. 2004

  9. Developing Data Intensive Applications on SMP Clusters, talk in First SIAM Conference on Computational Science and Engineering, September 2000.

Honors

Memberships

Professional Service

  1. Workshop Co-Chair for International Workshop on Mining Multiple Information Sources, in conjunction with KDD’07 and KDD’08.

  2. Program Committee Member for ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2009.

  3. Program Committee Member for International Conference on Extending Database Technology (EDBT), 2009.

  4. Program Committee Member for the European Conference on Machine Learning / Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2008.

  5. Program Committee Member for Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2007, 2008, 2009.

  6. Program Committee Member for SIAM Conference on Data Mining (SDM), 2007, 2009.

  7. Program Committee Member for European First International Conference on Data Mining (ECDM), 2007.

  8. Program Committee Member for IEEE International Conference on Granular Computing, 2006, 2007, 2008.

  9. Program Committee Member for International Conference on Information Systems, Technology, and Management (ICISTM), 2007, 2009.

  10. Program Committee Member for 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD), 2007.

  11. Program Committee Member for 2nd CIKM workshop of Data and Text Mining Methods in Bioinformatics (DTMbio), 2007.

  12. Program Committee Member for International Workshop on High Performance Data Mining and Application (HPDMA), 2007, in Conjuction with PAKDD 2007.

  13. Program Committee Member for 2006 ECML PKDD Workshop on Parallel Data Mining.

  14. Program Committee Member for 9th International Workshop on High Performance and Distributed Mining, 2006.

  15. Reviewer for International Conferences: VLDB’06, PODS’07, ICDCS’07.

  16. Journal Reviewer for BMC Bioinformatics, IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Parallel and Distributed Systems (TPDS), and IEEE Transactions on Computers (TC), ournal of Machine Learning Research (JMR).

Grants

  1. Ohio Board of Regents (OBR) Research Challenge Award (2007-2008), $50,000, Principle Investigator, (Co-PI: Helen Piontkivska, B.S., KSU).

  2. KSU Research Activity Award, 2007, Two-course release.

  3. Wright Center for Sensor Systems Engineering, August, 2007, co-PI, (PI Robert Walker, other Co-PIs Mikhail Nesterenko, Yuri Brietbart, and Hassan Peyravi, received 2-year funding of $444,959 from Cleveland State University. This grant is a subaward under a larger award from the Ohio Third Frontier Commission to fund a $73 million Wright Center for Sensor Systems Engineering)

Teaching & Course Development

  1. Database System Design, CS 4/50005 (Spring, 2009)

  2. Graph Mining, CS 6/79995 (Spring, 2009)

  3. Data Mining Techniques, CS 6/73015 (Fall, 2008)

  4. Data Mining Techniques, CS 6/73015 (Fall, 2007)

  5. Graph Mining, CS 6/79995 (Spring, 2007, New Course)

  6. Data Mining Techniques, CS 6/73015 (Fall, 2006)

  7. Advanced Database System Design, CS 6/73005 (Spring, 2006)

  8. Computer Architecture, CS 35101 (Fall, 2005)

Current Advisees

  1. Victor Lee (Ph.D. Student)

  2. Ning Ruan (Ph.D. Student)

  3. Xiaoxi Du (Ph.D. Student)

  4. Muad Abuata (Ph.D. Student)

  5. Lin Liu (Ph.D. Student)

  6. Hui Hong (Ph.D. Student)

  7. Chibuike Muoh (Masters Student)

Graduated Advisees

  1. Dong Wang (M.S. Nov. 2008)

  2. Dave Furhy (M.S., April 2008)

  3. Dave Stanfill, (B.S., Honors thesis, April 2008)

  4. Scott McCallen (M.S., Dec. 2007)