Yanqing Ji, Ph.D.

Professor, Electrical and Computer Engineering

Dr. Ji is an editor of Journal of Digital Signal Processing, an editorial board member of Biomedical Engineering Research (BER), and a reviewer for 23 international journals. He is also a member of the Program Committees of various international conferences...

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Yanqing Ji

Contact Information

  • FALL 2021
    On Sabbatical

Education & Curriculum Vitae

Ph.D. Computer Engineering, Wayne State University

M.Sc. Physical Electronics, University of Science & Technology of China

B.E. Industrial Automation, Qingdao University

Courses Taught

FALL 2021
On Sabbatical

Other semesters
CPEN 231 Microcomputer Architecture & Assembly Programming
CPEN 231L Microcomputer Architecture & Assembly Programming Lab
CPEN 436 Biomedical Informatics & Comp

Dr. Ji is an editor of Journal of Digital Signal Processing, an editorial board member of Biomedical Engineering Research (BER), and a reviewer for 23 international journals. He is also a member of the Program Committees of various international conferences and workshops including the 2017 IEEE International Conference on Bioinformatics and Biomedicine, the 15th International Conference on Information Technology: New Generations, the 13th IEEE International Conference on Ubiquitous Computing and Communications, and so on.

Peer-reviewed Book Chapters

  1. Hai Jiang, Yanqing Ji, “State-Carrying Code for Computation Mobility”, Handbook of Research on Scalable Computing Technologies, IGI Global, pp.874-894, 2009.

Peer-reviewed Journal Publications

  1. Yanqing Ji, Yun Tian, Fangyang Shen, John Tran “Leveraging MapReduce to Efficiently Extract Associations between Biomedical Concepts from Large Text Data,” Journal of Microprocessors and Microsystems, vol.46 (Part B), pp. 202-210, October 2016. DOI: 10.1016/j.micpro.2016.03.003
  2. Yanqing Ji, Hao Ying, John Tran, Peter Dews, R. Michael Massanari, “Integrating Unified Medical Language System and Association Mining Techniques into Relevance Feedback for Biomedical Literature Search,” BMC Bioinformatics, vol.17 (Suppl 9):264, 12 pages, July 2016. DOI: 10.1186/s12859-016-1129-z
  3. Yanqing Ji, Hao Ying, John Tran, Peter Dews, See-Yan Lau, Richard E. Miller, R. Michael Massanari, “A Functional Temporal Association Mining Approach for Screening Potential Drug-Drug Interactions from Electronic Patient Databases,” Informatics for Health & Social Care, vol.41 (4), pp. 387-404, 2016. DOI: 10.3109/17538157.2015.1064427
  4. Yanqing Ji, Fangyang Shen, See Yan Lau, John Tran “A Multi-Agent System for Reporting Suspected Adverse Drug Reactions,” Online Journal of Public Health Informatics, vol.6 (3), 19 pages, 2014. DOI: 10.5210/ojphi.v6i3.5579
  5. Yanqing Ji, Hao Ying, Peter Dews, John Tran, Ayman Mansour, Richard E. Miller, R. Michael Massanari, “A Method for Mining Infrequent Causal Associations and Its Application in Finding Adverse Drug Reaction Signal Pairs,” IEEE Transactions on Knowledge and Data Engineering, vol.25(4), pp.721-733, 2013. DOI: 10.1109/TKDE.2012.28
  6. Xiandong Meng, Yanqing Ji, "Modern Computational Techniques for the HMMER Sequence Analysis," ISRN Bioinformatics, vol. 2013, Article ID 252183, 13 pages, 2013. DOI: 10.1155/2013/252183
  7. Yanqing Ji, Hai Jiang, Vipin Chaudhary, “A Heuristic Checkpoint Placement Algorithm for Adaptive Application-Level Checkpointing,” International Journal of Applied Science and Technology, vol. 1(6), pp. 50-61, 2011.
  8. Yanqing Ji, Hao Ying, Peter Dews, Ayman Mansour, Margo S. Farber, John Tran, Richard E. Miller, R. Michael Massanari, “A Potential Causal Association Mining Algorithm for Screening Adverse Drug Reactions in Postmarketing Surveillance,” IEEE Transactions on Information Technology in Biomedicine, vol. 15(3), pp. 428-437, 2011. DOI: 10.1109/TITB.2011.2131669
  9. Yanqing Ji, Hao Ying, Margo S. Farber, John Yen, Peter Dews, Richard E. Miller, R. Michael Massanari, “A Distributed, Collaborative Intelligent Agent System Approach for Proactive Postmarketing Drug Safety Surveillance,” IEEE Transactions on Information Technology in Biomedicine, vol. 14 (3), pp. 826-837, 2010. DOI: 10.1109/TITB.2009.2037007
  10. Xiandong Meng, Yanqing Ji, Hai Jiang, “Advanced Acceleration Technologies for Biological Sequence Analysis,” Journal of Current Bioinformatics, vol. 5 (3), pp. 176-194, 2010. DOI: 10.2174/157489310792006738
  11. Yanqing Ji, R. Michael Massanari, Joel Ager, John Yen, Richard E. Miller, and Hao Ying "A Fuzzy Logic-Based Computational Recognition-Primed Decision Model," Information Sciences, vol. 177(20), pp. 4338-4353, 2007. DOI: 10.1016/j.ins.2007.02.026
  12. Yanqing Ji, Hao Ying, John Yen, Shizhuo Zhu, Daniel C. Barth-Jones, Richard E. Miller, R. Michael Massanari, “A Distributed Adverse Drug Reaction Detection System Using Intelligent Agents with Fuzzy Recognition-Primed Decision Model,” International Journal of Intelligent Systems, vol. 22(8), pp. 827-845, 2007. DOI: 10.1002/int.20230
  13. Yanqing Ji, Yongming Zhang, Xianbin Du, Ruishen Wu, Shixing Liu “Software Design of New-style Nuclear Gauge System,” Nuclear Electronics & Detection Technology (in Chinese), Vol. 22 (6), pp. 541-544, 2002.
  14. Shixing Liu, Yongming Zhang, Ying Yang, Ruisheng Wu, Xianbin Du, Yanqing Ji “A Microcomputerized Nuclear Gauge System with High Sensitivity and Low Radiation,” Nuclear Electronics & Detection Technology (in Chinese), Vol. 22 (3), pp. 265-267, 2002.
  15. Yanqing Ji, Yongming Zhang, Ruisheng Wu, Shixing Liu, Ying Yang “Multichannel Data Acquisition and Control Interface in Microcomputer Nuclear Gauge System,” Nuclear Electronics & Detection Technology (in Chinese), Vol. 21 (3), pp. 239-244, 2001.

Peer-reviewed Conference Proceedings Publications

  1. Yun Tian, Carol Taylor, Yanqing Ji, “Improving the CamShift Algorithm in Object Tracking Using Dynamic Parallelism on GPU”, 14th International Conference on Information Technology: New Generations (ITNG 2017), Las Vegas, Nevada, April 10-12, 2017.
  2. Fangyang Shen, Janine Roccosalvo, Jun Zhang, Yang Yi, Yanqing Ji, “A New Approach for STEM Teacher Scholarship Implementation”, 14th International Conference on Information Technology: New Generations (ITNG 2017), Las Vegas, Nevada, April 10-12, 2017.
  3. Yanqing Ji, Yun Tian, Fangyang Shen, John Tran, “Experimental Evaluations of MapReduce in Biomedical Text Mining,” 13th International Conference on Information Technology: New Generations (ITNG 2016), pp. 665-675, Las Vegas, Nevada, April 11-13, 2016.
  4. Yanqing Ji, Hao Ying, John Tran, Peter Dews, R. Michael Massanari, “Integrating Association Mining into Relevance Feedback for Biomedical Literature Search,” 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2015), pp. 531-536, Washington D.C., November 9-12, 2015.
  5. Yun Tian, Bojian Xu, Yanqing Ji, Jesse Scholer, “CloudTree: A Library to Extend Cloud Services for Trees,” 2015 IEEE BigData Congress, pp. 689-693, New York, June 27-July 2, 2015.
  6. Yanqing Ji, Yun Tian, Fangyang Shen, John Tran, “High-Performance Biomedical Association Mining with MapReduce,” 12th International Conference on Information Technology: New Generations (ITNG 2015), pp. 465-470, Las Vegas, Nevada, April 13-15, 2015.
  7. Yun Tian, Yanqing Ji “A Prototype Spatio-temporal Database Built on Top of Relational Database,” 12th International Conference on Information Technology: New Generations (ITNG 2015), pp. 14-19, Las Vegas, Nevada, April 13-15, 2015.
  8. Yanqing Ji, Hao Ying, John Tran, Peter Dews, Ayman Mansour, R. Michael Massanari, “A Temporal Interestingness Measure for Drug Interaction Signal Detection in Post-marketing Surveillance,” 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2722 - 2725, Chicago, Illinois, August 26-30, 2014.
  9. Yanqing Ji, Fangyang Shen, John Tran, “A Multi-Relational Association Mining Algorithm for Screening Suspected Adverse Drug Reactions,” 11th International Conference on Information Technology: New Generations (ITNG 2014), pp. 407 – 412, Las Vegas, Nevada, April 7-9, 2014.
  10. Yanqing Ji, Hao Ying, John Tran, Peter Dews, Ayman Mansour, See Yan Lau, R. Michael Massanari, “A Temporal Association Mining Method for Signaling Drug-Drug Interactions,” 2nd Workshop on Data Mining for Medicine and Healthcare in 2013 SIAM International Conference on Data Mining, 9 pages, Austin, Texas, May 2-4, 2013.
  11. Ayman Mansour, Hao Ying, Peter Dews, Yanqing Ji, R. Michael Massanari, "Identifying Adverse Drug Reaction Signal Pairs by a Multi-Agent Intelligent System with Fuzzy Decision Model," Proceedings of the 31st North American Fuzzy Information Processing Society Conference, pp. 1-6, Berkeley, CA, August 6-8, 2012.
  12. Yanqing Ji, Fangyang Shen, John Tran," A High Performance Agent-Based System for Reporting Suspected Adverse Drug Reactions," 9th International Conference on Information Technology: New Generations (ITNG 2012), pp. 490-495, Las Vegas, Nevada, April 16-18, 2012.
  13. Yanqing Ji, Hao Ying, John Tran, Peter Dews, Ayman Mansour, R. Michael Massanari, "Mining Infrequent Causal Associations in Electronic Health Databases," 2011 IEEE 11th International Conference on Data Mining Workshops, pp. 421-428, Vancouver, Canada, December 11-14, 2011.
  14. Yanqing Ji, Hao Ying, Peter Dews, John Tran, Ayman Mansour, Richard E. Miller, R. Michael Massanari, "An Exclusive Causal-Leverage Measure for Detecting Adverse Drug Reactions from Electronic Medical Records," Proceedings of the 30th North American Fuzzy Information Processing Society Conference, pp. 1-6, El Paso, TX, March 18-20, 2011.
  15. Ayman Mansour, Hao Ying, Peter Dews, Yanqing Ji, John Yen, Richard E. Miller, R. Michael Massanari, "Finding Similar Patients in a Multi-Agent Environment," Proceedings of the 30th North American Fuzzy Information Processing Society Conference, pp. 1-6, El Paso, TX, March 18-20, 2011.
  16. Yanqing Ji, Hao Ying, Margo S. Farber, Peter Dews, Ayman Mansour, John Tran, Richard E. Miller, R. Michael Massanari, “A Fuzzy Recognition-Primed Decision Model-Based Causal Association Mining Algorithm for Detecting Adverse Drug Reactions in Postmarketing Surveillance,” 2010 IEEE World Congress on Computational Intelligence (WCCI 2010), pp.1- 8, Barcelona, Spain, July 18-23, 2010.
  17. Ayman Mansour, Hao Ying, Peter Dews, Yanqing Ji, Margo S. Farber, John Yen, Richard E. Miller, R. Michael Massanari, “A Multi-Agent System for Detecting Adverse Drug Reactions,” 29th North American Fuzzy Information Processing Society Annual Conference (NAFIPS10), pp. 1-6 Toronto, Canada, July 12-14, 2010.
  18. Kiatisak Wongsopanakul, Yanqing Ji, Xinyu Du, Feng Lin, Hao Ying, “Application of the Extended Fuzzy Discrete Systems Theory to HIV/AIDS Treatment Regimen Selection,” 28th North American Fuzzy Information Processing Society Annual Conference (NAFIPS09), pp. 1- 6, Cincinnati, Ohio, June 14-17, 2009.
  19. Yanqing Ji, Hao Ying, Margo S. Farber, John Yen, Peter Dews, Richard E. Miller, and R. Michael Massanari, “Identifying Unknown Adverse Drug Reaction Signal Pairs in Postmarketing Surveillance Using an Active Multi-Agent System Approach,” IEEE 8th International Conference on Computer and Information Technology (CIT’08), pp. 444-449, Sydney, Australia, July 8-11, 2008.
  20. Yanqing Ji, Hao Ying, Margo S. Farber, John Yen, Peter Dews, Richard E. Miller, R. Michael Massanari, “Distributed, Collaborative Intelligent Agents for Proactive Post-Marketing Drug Safety Surveillance,” 26th North American Fuzzy Information Processing Society Annual Conference (NAFIPS07), pp.158-163, San Diego, California, June 24-27, 2007.
  21. Yanqing Ji, Hao Ying, Richard E. Miller, and R. Michael Massanari, "A Distributed Adverse Drug Reaction Detection System Using Intelligent Agents with Fuzzy Recognition-Primed Decision Model," Proceedings of VA Research - Real World Research to Improve Veterans Lives, pp. 14, Detroit, MI, May 18, 2007.
  22. Yanqing Ji, Hao Ying, Richard M. Massanari, and John Yen, "A Fuzzy Logic-Based Computational Recognition-Primed Decision Model," 11th Information Processing and Management of Uncertainty (IPMU) in Knowledge-Based Systems International Conference, pp. 1660-1667, Paris, France, July 2-7, 2006.
  23. Yanqing Ji, Hao Ying, Daniel C. Barth-Jones, John Yen, Shizhuo Zhu, Richard E. Miller, R. Michael Massanari, “A Team Agent Approach to Postmarketing Surveillance of Adverse Drug Reactions,” 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 6969 – 6972, Shanghai, China, September 1-4, 2005.
  24. Yanqing Ji, Hao Ying, John Yen, Shizhuo Zhu, R. Michael Massanari, Daniel C. Barth-Jones, “Team-based Multi-agent System for Early Detection of Adverse Drug Reactions in Postmarketing Surveillance,” 24th North American Fuzzy Information Processing Society Annual Conference (NAFIPS05), pp. 644-649, Ann Arbor, Michigan, June 22-25, 2005
  25. Yanqng Ji, H. Jiang, and V. Chaudhary, "Adaptation Strategies for Application-Level Computation Migration/Checkpointing," 2005 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’05), pp. 1156-1169, Las Vegas, Nevada, June 27-30, 2005.
  26. Yanqing Ji, H. Jiang, and V. Chaudhary, "Adaptation Point Analysis for Computation Migration/Checkpointing," 20th ACM Symposium on Applied Computing, Santa Fe, New Mexico, March 13-17, 2005.

Notes on Publications

  • Conference publications are highly regarded in computer engineering and science since they provide a fast way to transmit ideas in this relatively young and fast evolving discipline. The conference papers listed above were published in prestigious international conferences sponsored by Institute of Electrical and Electronics Engineers (IEEE) and/or Association of Computing Machinery (ACM), two most famous organizations in the field. They were all subject to strict anonymous peer review prior to publication.
  • For these publications, the first author has generally conducted the major work. Personally, I allow my name to be included as a co-author only when I have made significant work in the related research.

09/2015 – present Department of Electrical and Computer Engineering, Gonzaga University, Biomedical Literature Search and Knowledge Discovery

  • Developed a novel relevance feedback system, called BiomedSearch, for effective biomedical literature search.

06/2014 – present Department of Electrical and Computer Engineering, Gonzaga University, High-Performance Biomedical Association Mining

  • Developed a new high-performance association mining algorithm using MapReduce

08/2009-08/2015 – Department of Electrical and Computer Engineering, Gonzaga University, Mining Infrequent Casual Associations

  • Developed a new interestingness measure that can be used to assess the degree of causal association between two events
  • Developed an efficient mining algorithm based on the above measure
  • Tested the above algorithm using real electronic health database

12/2003-06/2010 – Department of Electrical and Computer Engineering at Gonzaga University and Biomedical Intelligent Systems Laboratory at Wayne State University, A Collaborative Multi-Agent System Approach to Postmarketing Surveillance of Unknown Adverse Drug Reactions (This multidisciplinary work is supported by NIH R21grant)

  • Led system analysis and design of a multi-agent system for distributed healthcare
  • Developed a fuzzy logic-based computational recognition-primed decision model
  • Optimized the decision model using genetic algorithms and physicians’ expertise
  • Implemented the multi-agent system using Java, SQL, database, fuzzy inference tools
  • Participated in writing two grant proposals – NIH R21 and AHRQ R18

01/2002-12/2003 – Parallel and Distributed Computing Laboratory, Wayne State University, MigThread: Heterogeneous Process/Thread Migration and Checkpointing (This research was supported in part by NSF grants IGERT 9987598, NSF MRI 9977815, and NSF ITR 0081696)

  • Assisted in system analysis and design of MigThread
  • Developed adaptation strategies for application-level computation migration
  • Designed and did experiments to test these strategies under UNIX environment

12/2000-07/2001 Microcomputer Application Laboratory, University of Science & Technology of China, “Full TOF System” for RHIC – STAR

  • Assisted in developing a high frequency “Signal Amplifying Card” for its subsystem “High Precision MRPC Electronics System”

09/1999-04/2001 – Microcomputer Application Laboratory, University of Science & Technology of China, Microcomputer-Based Real-Time Gauge System (M.S. Thesis)

  • Designed a multi-channel data acquisition and control card
  • Developed the data acquisition and control software of the system

09/1998-07/1999 – Microcomputer Application Laboratory, University of Science & Technology of China, Cable Television Charging System