Yumei Huo

Professor

Dr. Yumei Huo is a professor in Computer Science Department at CSI. Dr. Huo’s research has been in Sequencing and Scheduling, Combinatorial Optimization, Computational Complexity, Operations Research, High Performance Computing (HPC) and recently Medical Imaging and Big Data. Her complete list of published work can be found in Google Scholar and DBLP (https://scholar.google.com/citations?user=zpwr3EEAAAAJ and http://dblp.uni-trier.de/pers/hd/h/ Huo:Yumei). She has reviewed more than 50 proposals for PSC-CUNY research grants and Chancellor’s research fellowship program and has reviewed numerous manuscripts for more than 40 journals and conference proceedings. Dr. Huo has been supervising undergraduate/graduate students on a variety of research projects and published research papers with students.

Dr. Huo has taught various courses ranging from 100-level courses such as CSC126 (Introduction to Computer Science) to master-level courses such as CSC716 (Advanced Operating System) and CSC770 (Parallel Computing) and Ph.D.-level course such as CSC70010 (Algorithms) and CSC80030 (Sequencing and Scheduling). She has initiated and developed four High Performance Computing (HPC) courses for improving Computer Science program, including CSC229 Introduction to High Performance Computing, CSC429 Advanced High Performance Computing, CSC770 Parallel Computing, and CSC425 Shared Memory Parallel Computing.

Degrees

BS, University of Science and Technology (China)

MS, University of Science and Technology (China)

PhD, New Jersey Institute of Technology

Scholarship and Publications

REFEREED ARTICLES

  1. Tan J., L Jing, Y Huo, L Li, O Akin, Y Tian, “Lgan: Lung segmentation in ct scans using generative adversarial network”, Computerized Medical Imaging and Graphics, 87, 101817, 2021.
  2. Tan J., Y Gao, Z Liang, W Cao, MJ Pomeroy, Y Huo, L Li, MA Barish, A. F. abbasi, P. J. Pickhardt, “3D-GLCM CNN: A 3-dimensional gray-level co-occurrence matrix based CNN model for polyp classification via CT colonography”, IEEE Transactions on Medical Imaging, 39 (6), 2013-2024, 2019.
  3. Huo. Y, “Parallel Machine Makespan Minimization Subject to Machine Availability and Total Completion Time Constraints”, Journal of Scheduling, 22(4), 433-447, 2019.
  4. Gao Y., J. Tan, Z. Liang, L. Li, Y. Huo, “Improved computer-aided detection of pulmonary nodules via deep learning in the sinogram domain”, Visual Computing for Industry, Biomedicine, and Art, 2: 1-9, 2019.
  5. Tan J., Y. Huo, Z Liang, L Li, “Expert knowledge-infused deep learning for automatic lung nodule detection”, Journal of X-ray science and technology, 27(1), 17-35, 2019.
  6. Hall N.G., Y. Huo, B. Li, M. Pinedo, H. Zhao, "In memoriam: Dr. Joseph Leung", J. Scheduling 21(6): 579-580, 2018.
  7. Huo, Y. and H. Zhao, “Two Machine Scheduling Subject to Arbitrary Machine Availability Constraints,” Omega, 76: 128-136, 2018.
  8. Huo, Y. and H. Zhao, "Total Completion Time Minimization on Multiple Machines Subject to Machine Availability and Makespan Constraints," European Journal of Operational Research, 243(2):547-554, 2015.
  9. Huo, Y., Reznichenko B. and H. Zhao, "Minimizing Total Weighted Completion Time with Unexpected Machine Unavailability," Journal of Scheduling, 17(2): 161-172, 2014.
  10. Fu, B, Huo, Y. and H. Zhao, “Coordinated Scheduling of Production and Delivery with Production Window and Delivery Capacity Constraints”, Theoretical Computer Science, 422: 39-51, 2012.
  11. Fu, B, Huo, Y. and H. Zhao, "Approximation Schemes for Parallel Machine Scheduling with Availability Constraints," Discrete Applied Math, 159: 1555-1565, 2011.
  12. Huo, Y. and H. Zhao, “Bicriteria Scheduling Concerned with Makespan and Total Completion Time Subject to Machine Availability Constraints”, Theoretical Computer Science, 412:1081-1091, 2011.
  13. Huo, Y., J. Y-T. Leung and X. Wang, "Integrated Production and Delivery Scheduling with Disjoint Windows," Discrete Applied Math, 158:921-931, 2010.
  14. Huo, Y. and J. Y-T. Leung, “Fast Approximation Algorithms for Job Scheduling with Processing Sets Restrictions”, Theoretical Computer Science, 411: 3947-3955, 2010.
  15. Huo, Y. and J. Y-T. Leung, "Parallel Machine Scheduling with Nested Processing Set Restrictions," European Journal of Operational Research, 204:229-236, 2010.
  16. Fu, B, Huo, Y. and H. Zhao, “Exponential Inapproximability and FPTAS for Scheduling with Availability Constraints”, Theoretical Computer Science, 410:2663-2674, 2009.
  17. Huo, Y., J. Y-T. Leung and X. Wang,"Preemptive Scheduling Algorithms with Nested Processing Set Restriction," International Journal of Foundations of Computer Science, 20(6): 1147-1160, 2009.
  18. Fu, B, Y. Huo and H. Zhao, "Makespan Minimization with Machine Availability Constraints," Discrete Mathematics, Algorithms and Applications, 1(2): 141-151, 2009.
  19. Huo, Y., J. Y-T. Leung and X. Wang, "A Fast Preemptive Scheduling Algorithm with Release Times and Inclusive Processing Set Restrictions," Discrete Optimization, 6(3): 292-298, 2009.
  20. Huo, Y., H. Li, and H. Zhao, "Minimizing Total Completion Time in Two-Machine Flow Shops with Exact Delays," Computers & Operations Research, 36(6): 2018-2030, 2009.
  21. Huo, Y., J. Y-T. Leung and X. Wang, "Online Scheduling of Equal-Processing-Time Task Systems," Theoretical Computer Science, 401: 85-95, 2008.
  22. Huo, Y., J. Y-T. Leung and H. Zhao, "Complexity of Two Dual Criteria Scheduling Problems," Operations Research Letters, 35:211-220, 2007.
  23. Huo, Y., J. Y-T. Leung and H. Zhao, "Bi-criteria Scheduling Problems: Number of Tardy Jobs and Maximum Weighted Tardiness," European Journal of Operational Research, 177:116-134, 2007.
  24. Huo, Y. and J. Y-T. Leung, "Minimizing Mean Flow Time for UET Tasks," ACM Transactions on Algorithms, Vol. 2, No. 2, pp. 244-262. April 2006.
  25. Huo, Y.  and J. Y-T. Leung, "Online Scheduling of Precedence Constrained Tasks," SIAM J. on Computing, Volume 34, Number 3, pp. 743-762. 2005.
  26. Huo, Y.  and J. Y-T. Leung, "Minimizing Total Completion Time for UET Tasks with Release Time and Outtree Precedence Constraints," Mathematical Methods of Operations Research, Vol. 62, No. 2, pp. 275-278, 2005.
  27. Huo Y. and Q. Wang, "Control Flow Analysis and Simulator Design for VLIW Architecture Microprocessor", MINI-MICRO SYSTEMS, Vol. 22, No. 5, 2001.
  28. Tu, X. and Y. Huo, "Knowledge Economics-oriented Intelligence Simulation Technology", Computer Simulation, 1999(7).

REFEREED PROCEEDINGS

  1. Tan J., S. Zhang, W. Cao, Y. Gao, L.C. Li, Y. Huo, Z. Liang, "A multi-stage fusion strategy for multi-scale GLCM-CNN model in differentiating malignant from benign polyps," Medical Imaging 2020: Computer-Aided Diagnosis, 11314, 113141S, 2020.
  2. Huo Y. and H. Zhao, “Revisit Heuristics for Flowshop Scheduling with Availability Constraint,” The 9th Multidisciplinary International Conference on Scheduling: Theory and Applications (MISTA 2019), 609-611, 2019.
  3. Tan J., Y. Gao, W. Cao, M.J. Pomeroy, S. Zhang, Y. Huo, L. Li, Z. Liang, "GLCM-CNN: Gray Level Co-occurrence Matrix based CNN Model for Polyp Diagnosis," IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 1-4, 2019.
  4. Tan J., Y. Gao, Y. Huo, L. Li, Z. Liang, "Sharpness preserved sonogram synthesis using convolutional neural network for sparse-view CT imaging," SPIE Medical Imaging: Image Processing, 109490E, 2019.
  5. Tan J., Y. Huo, Z. Liang, L. Li, "A Fast Automatic Juxta-pleural Lung Nodule Detection Framework Using Convolutional Neural Networks and Vote Algorithm," The International Workshop on Patch-Based Techniques in Medical Imaging, (Patch-MI@MICCAI 2018), Lecture Notes in Computer Science Vol. 11075, page 85-92, 2018.
  6. Tan J., Y. Huo, Z. Liang, L. Li, “Apply Convolutional Neural Network to Lung Nodule Detection: Recent Progress and Challenges,” The International Conference for Smart Health 2017 (ICSH 2017).
  7. Tan J., A. Kotov, R.P. Mohammadiani, Y. Huo, “Sentence Retrieval with Sentiment-specific Topical Anchoring for Review Summarization”, The 26th 2017 ACM Conference on Information and Knowledge Management (CIKM’17). ).
  8. Tan J., Huo Y., Z. Liang and L. Li, “A Comparison Study On The Effect Of False Positive Reduction In Deep Learning Based Detection For Juxtapleural Lung Nodules: CNN VS DNN,” Modeling and Simulation in Medicine Symposium 2017 (MSM 2017).
  9. Tan J., Huo Y., and L. Li, "Using ConvNet to recognize lung nodule from CT user data: A feasibility study," Computational Approaches for Cancer Workshop 2016 (CAFCW-2016).
  10. Huo, Y. and H. Zhao, “Minimizing Total Completion Time in Flow shop with Availability Constraints,” 9th International Workshop on Computational Optimization (WCO'16), Proceedings of the Federated Conference on Computer Science and Information Systems, 637-645, 2016.
  11. Huo, Y. and Huang J.X., “Parallel ant colony optimization for flow shop scheduling subject to limited machine availability,” The sixth IEEE Workshop on Parallel Computing and Optimization, IEEE International Parallel and Distributed Processing Symposium Workshops, 756-765, 2016.
  12. Huo, Y., “Makespan Minimization on Multiple Machines Subject to Machine Unavailability and Total Completion Time Constraints,” The tenth International Conference on Algorithmic Aspects of Information and Management (AAIM 2014), Lecture Notes In Computer Science, Vol. 8546: 56-65, 2014.
  13. Huo, Y. and H. Zhao, "Bi-criteria Scheduling on Multiple Machines Subject to Machine Availability Constraints," The Seventh International Frontiers of Algorithmics Workshop and The Ninth International Conference on Algorithmic Aspects of Information and Management (FAW-AAIM 2013), Lecture Notes In Computer Science, Vol. 7924: 325-338, 2013.
  14. Huo, Y., B. Reznichenko and H. Zhao, "Minimizing Total Weighted Completion Time with Unexpected Machine Unavailability," The 6rd Annual International Conference on Combinatorial Optimization and Applications (COCOA'12), Lecture Notes In Computer Science, Vol. 7402: 291-300, 2012.
  15. Fu, B., Y. Huo and H. Zhao, "Approximation Schemes for Scheduling with Availability Constraints," In the Proceedings of the Fourth International Frontiers of Algorithmics Workshop (FAW 2010), Lecture Notes in Computer Science, Lecture Notes In Computer Science, Vol. 6213: 77-88, 2010.
  16. Fu, B, Huo, Y. and H. Zhao, “Coordinated Scheduling of Production and Delivery with Production Window and Delivery Capacity Constraints”, The Sixth International Conference on Algorithmic Aspects in Information and Management (AAIM’10), Lecture Notes In Computer Science, Vol. 6124: 141-149, 2010.
  17. Huo, Y., J. Y-T. Leung and X. Wang, "Integrated production and delivery scheduling with disjoint windows," The 3rd Annual International Conference on Combinatorial Optimization and Applications (COCOA'09), Lecture Notes In Computer Science, Vol. 5573: 471-482, 2009.
  18. Fu, B., Y. Huo and H. Zhao, "Makespan minimization with machine availability constraints", The 3rd Annual International Conference on Combinatorial Optimization and Applications (COCOA'09), Lecture Notes In Computer Science, Vol. 5573: 430-437, 2009.
  19. Huo, Y., H. Li, and H. Zhao, "Minimizing Total Completion Time in Two-Machine Flow Shops With Exact Delays," The 2nd Annual International Conference on Combinatorial Optimization and Applications (COCOA'08), Lecture Notes In Computer Science: Vol. 5165: 427-437, 2008.
  20. Huo, Y. and J. Y-T. Leung, "Online Scheduling of Precedence Constrained Tasks," Proceedings of the 2nd Multidisciplinary International Conference on Scheduling: Theory & Applications (MISTA 2005), pages 573-584, 2005.

REFEREED POSTERS

  1. Huo, Y. and Gu, F. Adoptions and Outcomes of NSF/IEEE TCPP PDC Curriculum at College of Staten Island, NSF/TCPP Workshop on Parallel and Distributed Computing Education (EduPar-16), Chicago, IL, May 23, 2016.
  2. Huo, Y. and Gu, F. EA Poster: Experience of Applying NSF/IEEE TCPP Curriculum Initiative on Parallel and Distributed Computing at College of Staten Island, EduHPC-15: Workshop on Education for High-Performance Computing, Austin, TX, November 16, 2015.
  3. Huo, Y. and Gu, F. EA Poster - Parallel and Distributed Computing Curriculum at College of Staten Island,  29th IEEE International Parallel & Distributed Processing Symposium, May 23-27, 2015, Hyderabad, India.

NON-REFEREED BOOKS, ARTICLES, AND PROCEEDINGS

  1. Cardozo, A. and Y. Huo (2017), “Parallel Ant Colony Optimization for Flow Shop Scheduling under Shared Memory Platform,” Undergraduate Research conference 2017, College of Staten Island, CUNY.
  2. Park, S. and Y. Huo (2017), “Parallel Tabu Search Algorithms for Two Machine Flow Shop with Limited Machine Availability,” Undergraduate Research conference 2017, College of Staten Island, CUNY.
  3. Ariaudo, D. and Y. Huo (2015), “Minimizing Total Completion Time in Flow Shop with Unavailable Interval on the First Machine,” Undergraduate Research conference 2015, College of Staten Island, CUNY.
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Contact Information

Office: Building 1N Room 214
Phone: 718.982.2841
Fax: 718.982.2856
Email Yumei Huo