General

Ge Yang, Ph.D.

Professor, School of Artificial Intelligence, University of Chinese Academy of Sciences

Investigator, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences

Email: yangge@ucas.edu.cn   ge.yang@ia.ac.cn

Mailing address:

95 Zhongguancun East Road

Zidonghua Building 510

Beijing 100190

China


Research Areas

biological image analysis and informatics, computer vision, artificial intelligence, computational biology, computational neuroscience


Education

01/2004~12/2008 Postdoctoral Training, Computational Cell Biology, Scripps Research Institute, La Jolla
Advisor: Gaudenz Danuser

10/2001~02/2004 Ph.D., Mechanical Engineering; Minor, Applied Mathematics, University of Minnesota, Twin Cities
Advisor: Bradley Nelson

12/1998~10/2001 M.S., Mechanical Engineering, University of Minnesota, Twin Cities
Advisor: Bradley Nelson

09/1998~12/1998 Ph.D. Program in Mechanical Engineering, University of Illinois Chicago
Advisor: Bradley Nelson

09/1995~07/1998 M.S., Electrical Engineering, Institute of Automation, Chinese Academy of Sciences, Beijing
Advisor: Yaotong Li, Qiu Ouyang, Min Tan

09/1986~07/1991 B.S., Mechanical Engineering; B.S., Electrical Engineering, Tsinghua University, Beijing, China


Experience

   
Work Experience

01/2019~present Professor, School of Artificial Intelligence, 

University of Chinese Academy of Sciences

01/2019~present Investigator, National Laboratory of Pattern Recognition, Institute of Automation, 

Chinese Academy of Sciences

07/2014~12/2018 Associate Professor, Department of Biomedical Engineering & Department of Computational Biology,

Carnegie Mellon University

10/2011~12/2018 Faculty, Center for Mechanics & Engineering of Cellular Systems, Carnegie Mellon University

01/2009~present Faculty, Molecular Biosensor and Imaging Center, Carnegie Mellon University

01/2009~present Faculty, Carnegie Mellon University-University of Pittsburgh Joint Ph.D. Program in Computational Biology

01/2009~06/2014 Assistant Professor, Department of Biomedical Engineering & Department of Computational Biology,

Carnegie Mellon University

04/1994~07/1995 Engineer, Wuhan Electronics Group Company Software Development Center

07/1991~04/1994 Engineer, Dongfeng-Citroen Automobile Company


Teaching Experience

At University of Chinese Academy of Sciences

Spring 2020 Research Integrity and Norms of Professional Technical Writing

Spring 2020 Biological Image Analysis and Informatics

Fall 2019  Digitial Image Processing and Analysis

Summer 2019 Biological Image Analysis and Informatics


At Carnegie Mellon University

Spring 2017~2018 BME42-672/ECE18-795/CB02-740 Fundamentals of Biomedical Imaging and Image Analysis

Spring 2010~2016 BME42-731/ECE18-795/CB02-740 Bioimage Informatics

Fall 2009~2017 BME42-620 Engineering Molecular Cell Biology

Spring 2011, 2012, 2014 BSC03-741 Advanced Cell Biology (co-instructor, 3 weeks per semester)

Spring 2009 CB02-701 Current Topics in Computational Biology 


Publications

   
Papers

60. Ba Q.*, Andrzejczuk L.*, Chai X., Kiselyov K.^, and Yang G.^ Image biomarkers of lysosomal storage diseases identified using machine learning, in preparation.

59. Li A., Chai X., Zhang Y. J.^ and Yang G.^ Isogeometric analysis based simulation and analysis of material transport in complex geometry of neurons, submitted to Scientific Reports.

58. Yu Y.*, Ba Q.*, Qiu M. and Yang G. High-resolution imaging and computational analysis of mitochondrial dynamics in Drosophila larval segmental axons, submitted to Journal of Visualized Experiments (invited paper).

57. Yu Y.*, Ba Q.*, Lee H.-C., and Yang G. A computational model of dynamic spatial organization of mitochondria in the axon, submitted to Quantitative Biology (invited paper).

56. Chai X. and Yang G. Quantifying robustness and sensitivity of convolutional neural networks for quantitative characterization of mitochondrial morphology, Quantitative Biology, accepted.

55. Chai X. and Yang G. Characterizing robustness and sensitivity of deep convolutional neural networks for segmentation of fluorescence microscopy images, accepted to 2018 IEEE International Symposium on Image Processing (ICIP).

54. Ba Q., Raghavan G., Kiselyov K., and Yang G. (2018), Whole-cell scale dynamic organization of lysosomes revealed by spatial statistical analysis,  Cell Reports, vol. 23, pp. 3591-3606.

53. Rastogi S.K., Raghavan G., Yang G.^, and Cohen-Karni T.^ (2017), Effects of graphene on nonneuronal and neuronal cell viability and stress, Nano Letters, vol. 17, pp. 3297-3301. (^corresponding authors)

52. Ba Q., & Yang G. (2017), Intracellular organelle networks: understanding their organization and communication through systems-level modeling and analysis (invited review), Frontiers in Biology, vol. 12, pp. 7-18, doi:10.1007/s11515-016-1436-9.

51. Chai X., Qian D., Ba Q., Li A., Zhang Y.J., and Yang G. (2017), Image-base measurement of cargo traffic flow in complex neurite networks, Proc. 2017 IEEE International Conference on Image Processing (ICIP), pp. 3290-3294.

50. Ming X., Chai X., Muthakana H., Liang X., Yang G., Zeev-Ben-Mordehai T. and Xing E. (2017) Deep learning based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms, Bioinformatics, vol. 33, pp. i13-i22.

49. Yang H., Wang J., Tang H., Ba Q., Yang G., and Tang X. (2017), Mitochondrial shape analysis using large deformation diffeomorphic metric curve matching, Proc. 2017 IEEE Engineering in Medicine and Biology Conference (EMBS), pp. 4062-4065.

48. Yu Y., Lee H.-C., Chen K.-C., Suhan J., Qiu M., Ba Q., Yang G. (2016), Inner membrane fusion mediates spatial distribution of axonal mitochondria, Scientific Reports, doi:10.1038/srep18981.

47. Liao T., Lee H.-C., Yang G., Zhang Y. J. (2016), Shape correspondence analysis for biomolecules based on volumetric eigenfunctions, Molecular Based Mathematical Biology, vol. 3, pp. 112-127.

46. Weaver L. N., Ems-McClung S. C., Chen S.-H., Yang G., Shaw S.L., Walczak C. E. (2015), Ran-GTP gradient spatially regulates XCTK2 within the spindle, Current Biology, vol. 25, pp. 1509-1514.

45. Lee H.-C., Tao L., Zhang J., and Yang G. (2015), Shape component analysis: structure-preserving dimension reduction on biological shape spaces, Bioinformatics, doi:10.1093/bioinformatics/btv648.

44. Yang G. and Lee H.-C. (2015), Computational image analysis techniques for cell mechanobiology, in Micro and Nano Techniques in Cell Mechanobiology, Sun Y., Simmons C., Kim D.-H., eds., Cambridge University Press.

43. Chen K.-C., Yu Y., Kovacevic J., and Yang G. (2015) A sliding-window data aggregation method for super-resolution imaging of live cells, 2015 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 785-788.

42. Lee H.-C. and Yang G. (2015) Image-based computational methods for characterizing whole-cell scale spatiotemporal dynamics of intracellular transport, 2015 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 699-702. ISBI 2015 best paper award.

41. Yang G. (2014), Image-based computational tracking and analysis of spindle protein dynamics, in Experimental Techniques for Mitosis, Sharp D. ed., Methods in Molecular Biology, vol. 1136, DOI 10.1007/978-1-4939-0329-0_5, Springer.

40. Chen K.-C., Yang G., and Kovacevic J. (2014) Spatial density estimation based segmentation of super-resolution localization microscopy images, Proc. 2014 IEEE International Conference on Image Processing (ICIP), pp. 867-871.

39. Xu J.Q., Yu Y., Lee H.-C., Fan Q., Winter J., and Yang G. (2014) Cell penetrating peptide mediated quantum dot delivery and release in live mammalian cells, Proc. 36th Annual International Conference of IEEE Engineering in Medicine and Biology Society (EMBC2014), pp. 4260-4263.

38. Chen K.-C., Qiu M., Kovacevic J., and Yang G. (2014) Computational image modeling for characterization and analysis of intracellular cargo transport, Proc. of CompIMAGE'14, Lecture Notes in Computer Science, vol. 8641, pp. 292-303.  CompIMAGE’14 best paper award.

37. Lee H.-C. and Yang G. (2014) Computational removal of background fluorescence for biological fluorescence microscopy, Proc. 2014 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 205-208.

36. Lee H.-C. and Yang G. (2014) Integrating dimension reduction with mean-shift clustering for biological shape classification, Proc. 2014 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 254-257.

35. Chen K.-C. Kovacevic J., and Yang G. (2014) Structure-based determination of imaging length for super-resolution localization microscopy, Proc. 2014 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 991-994.

34. Gunawardena S., Yang G., and Goldstein L. S. B. (2013) Presenilin controls kinesin-1 and dynein function during AP vesicle transport in vivo, Human Molecular Genetics, vol. 22, pp. 3838-3843. 

33. Yang G. (2013), Bioimage informatics for understanding spatiotemporal dynamics of cellular processes (invited review), Wiley Interdisciplinary Review on Systems Biology and Medicine, vol. 5, pp. 367-380.

32. Yang G. and Olivo-Marin J.-C. (2013) Image-based representation and modeling of spatiotemporal cell dynamic, Proc. 2013 IEEE International Conference on Image Processing (ICIP), pp. 1198-1201.

31. Qiu M. and Yang G. (2013) Drift correction for fluorescence live cell imaging through correlated motion identification, Proc. 2013 IEEE International Conference on Image Processing (ICIP), pp. 452-455.

30. Booth-Gauthier E.A., Yang G., Dahl K. N. (2012), Shear stress induced changes in genome rheology and reorganization, Biophysical Journal, vol. 103, pp. 2423-2431.

29. Reis G.F.*, Yang G.*, Szpankowski, L., Weaver C., Shah S., Robinson J.T., Hays T. S., Danuser G., and Goldstein L.S.B. (2012), Molecular motor function in axonal transport in vivo probed by genetic and computational analysis in Drosophila, Molecular Biology of the Cell, vol. 23, pp. 1700-1714. (*: equal contribution authors)

28. Gable A., Qiu M., Titus J., Balchand S., Ferenz N. F., Ma N., Fagerstrom C., Ross R. L., Yang G., Wadsworth P. (2012), Dynamic reorganization of Eg5 in the mammalian spindle throughout mitosis requires dynein and TPX2, Molecular Biology of the Cell, vol. 23, pp. 1254-1266.

27. Roy S., Yang G., Tang Y., and Scott D. (2012), A simple photoactivation and image analysis module for visualizing and analyzing axonal transport with high temporal resolution, Nature Protocols, vol. 7, pp. 62-68, 2012.

26. Chen K.-C., Yu Y., Li R., Lee H.-C., Yang G., Kovacevic J. (2012) Adaptive active-mask image segmentation for quantitative characterization of mitochondrial morphology, Proc. 2012 IEEE International Conference on Image Processing (ICIP), pp. 2033-2036.

25. Qiu M., Lee H.-C., and Yang G. (2011) Nanometer resolution tracking and modeling of bidirectional axonal cargo transport, Proc. 2012 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 992-995.

24. Weinger J.S., Qiu M., Yang G., Kapoor T.M. (2011), A nonmotor microtubule binding site in kinesin-5 is required for filament crosslinking and sliding, Current Biology, vol.21, pp. 1-7.

23. Matov A., Edvall M.M., Yang G., and Gaudenz Danuser (2011), Optimal‐flow minimum-cost correspondence assignment in particle flow tracking, Computer Vision and Image Understanding, vol. 115, pp. 531-540.

22. Yang G. (2011) Nanometer resolution imaging and tracking of axonal cargo transport in normal and degenerative neurons (invited paper), Proc. 45th Annual Asilomar Conference on Signals, Systems, and Computers, pp. 431-435.

21. Goodman B., Channels W., Qiu M., Iglesias P., Yang G.^, Zheng Y.^ (2010), Lamin B restrains spindle pole separation in Xenopus egg extracts, Journal of Biological Chemistry, vol. 285, pp. 35238-35244. (^: corresponding authors)

20. Houghtaling B., Yang G., Matov A., Danuser G., and Kapoor T. M. (2009), Op18 reveals the contribution of non-kinetochore microtubules to the dynamic organization of the vertebrate meiotic spindle, Proc. Nat. Acad. Sci. vol. 106, pp.15338-15343.

19. Applegate, K., Yang G., Danuser, G. (2009) Measuring the dynamic cytoskeleton architecture in living cells, in Nanomedicine and Nanobiotechnology, Vogel V. et al. eds., pp. 167-206, Wiley-VCH.

18. Cameron L.A., Houghtaling B., and Yang G. (2009), Quantitative Fluorescent Speckle Microscopy, in Optical Imaging Techniques, Yuste R. et al eds., pp. 667-682, Cold Spring Harbor Laboratory Press.

17. Yang G.*, Cameron L.A.*, Danuser G., and Salmon E.D. (2008), Regional variation of microtubule flux reveals microtubule organization in Xenopus extract meiotic spindles, Journal of Cell Biology, vol. 182, pp. 631-639. (*equal contribution authors)

16. Yang G.*, Houghtaling B.R.*, Gaetz J., Liu J.Z., Danuser G., and Kapoor T.M. (2007), Architectural dynamics of the meiotic spindle revealed by single-fluorophore imaging, Nature Cell Biology, vol. 9, pp. 1233-1242. (*equal contribution authors)

15. Haghnia M., Cavalli V., Shah S.B., Schimmelpfeng K., Brusch R., Yang G., Herrera C., Pilling A., and Goldstein, L.S.B. (2007), Dynactin is required for coordinated bidirectional motility, but not for dynein membrane attachment, Molecular Biology of the Cell, vol. 18, pp. 2081-2089.

14. Dorn J., Danuser G., and Yang G. (2007) Computational processing and analysis of dynamic fluorescence image data, in Fluorescent Proteins, Methods in Cell Biology, vol. 85, pp. 497-538.

13. Yang G. and Nelson, B.J. (2007) Fundamentals of microscopy and machine vision, in Life Science Automation: Fundamentals and Applications, Zhang M.J., Nelson B.J., and Felder R.A. eds., pp.125-149, Artech House.

12. Cameron L.A., Yang G., Cimini D., Canman J.C., Kisurina-Evgenieva O., Khodjakov A., Danuser G., and Salmon E.D. (2006) Kinesin 5-independent poleward flux of kinetochore microtubules in PtK1 cells, Journal of Cell Biology, vol. 173, pp. 173-179. (Cover)

11. Shah S., Yang G., Danuser G., and Goldstein L.S.B. (2006) Axonal transport: imaging and modeling of a neuronal process, in Proc. Nobel Symposium 131: Controlled Nanoscale Motion in Biological and Artificial Systems. Lecture Notes in Physics, vol. 711, pp. 65-84, Springer-Verlag.

10. Yang G. and Nelson B.J. (2005) Optomechatronic design of microassembly systems for manufacturing hybrid microsystems, IEEE Transactions on Industrial Electronics, vol. 52, pp. 1013-1023.

9. Yang G., Matov A., and Danuser G. (2005) Reliable tracking of large-scale dense particle motion for fluorescent live cell imaging, Proc. Workshop on Computer Vision Methods for Bioinformatics, IEEE Int. Conf. Computer Vision and Pattern Recognition. pp. 9-17.

8. Yang G., Gaines J.A., and Nelson B.J. (2003) A supervisory wafer-level microassembly system for hybrid MEMS fabrication, Journal of Intelligent and Robotic Systems, vol. 37, pp. 43-68.

7. Yang G., and Nelson B.J. (2003) Automated microassembly, in MEMS Packaging, T.-R. Hsu ed., pp. 109-140, IEE Press.

6. Yang G., and Nelson B.J. (2003) Wavelet-based autofocusing and unsupervised segmentation of microscopic images, Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), vol. 3, pp. 2143-2148.

5. Yang G., and Nelson B.J. (2003) Micromanipulation contact transition control by selective focusing and microforce control, Proc. IEEE Int. Conf. Robotics and Automation (ICRA), vol. 3, pp. 3200-3206.

4. Yang G., and Nelson B.J. (2002) Integration of microscopic vision and microforce feedback for microassembly, Proc. 3rd Int. Workshop on Microfactories, pp. 145-148.

3. Greminger M., Yang G., and Nelson B.J. (2002) Sensing nanonewton level forces by visually tracking structural deformations, Proc. IEEE Int. Conf. Robotics and Automation (ICRA), vol. 2, pp. 1943-1948.

2. Vikramaditya B., Nelson B.J., Yang G., and Enikov E.T. (2001) Microassembly of hybrid magnetic MEMS, Journal of Micromechatronics, vol. 1, pp. 99-116.

1. Yang G., Gaines J.A., and Nelson B.J. (2001) A flexible experimental workcell for efficient and reliable wafer-level 3D microassembly, Proc. IEEE Int. Conf. on Robotics and Automation (ICRA), vol. 1, pp. 133-138.


Research Interests

biological image analysis and informatics, computer vision, artificial intelligence, computational biology, computational neuroscience


Students

现指导学生

吴诗雨  硕士研究生  085210-控制工程  

罗曜儒  博士研究生  081104-模式识别与智能系统  

Honors & Distinctions

2017 John Lawrence Seminar, Biological Systems & Engineering Division, Lawrence Berkeley National Laboratory

2015 Best Paper Award (with Hao-Chih Lee), 2015 IEEE International Symposium on Biomedical Imaging (ISBI)

2014 Best Paper Award (with Kuan-Chieh Chen), 2014 International Symposium on Computational Modeling
of Image Objects (CompIMAGE’14)

2014 Berkman Faculty Development Award, Carnegie Mellon University

2012 Faculty Early Career Award, National Science Foundation

2012 Invited attendee, IEEE Forum on Grand Challenges in Biomedical  Imaging, Bethesda, MD 

2011 Invited attendee, NSF Idea Lab on Innovations in Biological Imaging and Visualization 

2009 Wimmer Faculty Fellowship, Wimmer Foundation and Eberly Center for Teaching Excellence 
Carnegie Mellon University 

2007 Nominee for Burroughs-Wellcome Interfaces in Science Award, Scripps Research Institute 

2006~2007 La Jolla Interfaces in Science Interdisciplinary Fellowship, Burroughs-Wellcome Fund

1997 Outstanding Student Award, Institute of Automation, Chinese Academy of Sciences

1996 Elite Fellowship, Chinese Academy of Sciences

1989 Guanghua Fellowship, Tsinghua University


Experience

   
Work Experience

01/2019~present Professor, School of Artificial Intelligence, 

University of Chinese Academy of Sciences

01/2019~present Investigator, National Laboratory of Pattern Recognition, Institute of Automation, 

Chinese Academy of Sciences

07/2014~12/2018 Associate Professor, Department of Biomedical Engineering & Department of Computational Biology,

Carnegie Mellon University

10/2011~12/2018 Faculty, Center for Mechanics & Engineering of Cellular Systems, Carnegie Mellon University

01/2009~present Faculty, Molecular Biosensor and Imaging Center, Carnegie Mellon University

01/2009~present Faculty, Carnegie Mellon University-University of Pittsburgh Joint Ph.D. Program in Computational Biology

01/2009~06/2014 Assistant Professor, Department of Biomedical Engineering & Department of Computational Biology,

Carnegie Mellon University

04/1994~07/1995 Engineer, Wuhan Electronics Group Company Software Development Center

07/1991~04/1994 Engineer, Dongfeng-Citroen Automobile Company


Teaching Experience

At University of Chinese Academy of Sciences

Spring 2020 Research Integrity and Norms of Professional Technical Writing

Spring 2020 Biological Image Analysis and Informatics

Fall 2019  Digitial Image Processing and Analysis

Summer 2019 Biological Image Analysis and Informatics


At Carnegie Mellon University

Spring 2017~2018 BME42-672/ECE18-795/CB02-740 Fundamentals of Biomedical Imaging and Image Analysis

Spring 2010~2016 BME42-731/ECE18-795/CB02-740 Bioimage Informatics

Fall 2009~2017 BME42-620 Engineering Molecular Cell Biology

Spring 2011, 2012, 2014 BSC03-741 Advanced Cell Biology (co-instructor, 3 weeks per semester)

Spring 2009 CB02-701 Current Topics in Computational Biology 


Publications

   
Papers

60. Ba Q.*, Andrzejczuk L.*, Chai X., Kiselyov K.^, and Yang G.^ Image biomarkers of lysosomal storage diseases identified using machine learning, in preparation.

59. Li A., Chai X., Zhang Y. J.^ and Yang G.^ Isogeometric analysis based simulation and analysis of material transport in complex geometry of neurons, submitted to Scientific Reports.

58. Yu Y.*, Ba Q.*, Qiu M. and Yang G. High-resolution imaging and computational analysis of mitochondrial dynamics in Drosophila larval segmental axons, submitted to Journal of Visualized Experiments (invited paper).

57. Yu Y.*, Ba Q.*, Lee H.-C., and Yang G. A computational model of dynamic spatial organization of mitochondria in the axon, submitted to Quantitative Biology (invited paper).

56. Chai X. and Yang G. Quantifying robustness and sensitivity of convolutional neural networks for quantitative characterization of mitochondrial morphology, Quantitative Biology, accepted.

55. Chai X. and Yang G. Characterizing robustness and sensitivity of deep convolutional neural networks for segmentation of fluorescence microscopy images, accepted to 2018 IEEE International Symposium on Image Processing (ICIP).

54. Ba Q., Raghavan G., Kiselyov K., and Yang G. (2018), Whole-cell scale dynamic organization of lysosomes revealed by spatial statistical analysis,  Cell Reports, vol. 23, pp. 3591-3606.

53. Rastogi S.K., Raghavan G., Yang G.^, and Cohen-Karni T.^ (2017), Effects of graphene on nonneuronal and neuronal cell viability and stress, Nano Letters, vol. 17, pp. 3297-3301. (^corresponding authors)

52. Ba Q., & Yang G. (2017), Intracellular organelle networks: understanding their organization and communication through systems-level modeling and analysis (invited review), Frontiers in Biology, vol. 12, pp. 7-18, doi:10.1007/s11515-016-1436-9.

51. Chai X., Qian D., Ba Q., Li A., Zhang Y.J., and Yang G. (2017), Image-base measurement of cargo traffic flow in complex neurite networks, Proc. 2017 IEEE International Conference on Image Processing (ICIP), pp. 3290-3294.

50. Ming X., Chai X., Muthakana H., Liang X., Yang G., Zeev-Ben-Mordehai T. and Xing E. (2017) Deep learning based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms, Bioinformatics, vol. 33, pp. i13-i22.

49. Yang H., Wang J., Tang H., Ba Q., Yang G., and Tang X. (2017), Mitochondrial shape analysis using large deformation diffeomorphic metric curve matching, Proc. 2017 IEEE Engineering in Medicine and Biology Conference (EMBS), pp. 4062-4065.

48. Yu Y., Lee H.-C., Chen K.-C., Suhan J., Qiu M., Ba Q., Yang G. (2016), Inner membrane fusion mediates spatial distribution of axonal mitochondria, Scientific Reports, doi:10.1038/srep18981.

47. Liao T., Lee H.-C., Yang G., Zhang Y. J. (2016), Shape correspondence analysis for biomolecules based on volumetric eigenfunctions, Molecular Based Mathematical Biology, vol. 3, pp. 112-127.

46. Weaver L. N., Ems-McClung S. C., Chen S.-H., Yang G., Shaw S.L., Walczak C. E. (2015), Ran-GTP gradient spatially regulates XCTK2 within the spindle, Current Biology, vol. 25, pp. 1509-1514.

45. Lee H.-C., Tao L., Zhang J., and Yang G. (2015), Shape component analysis: structure-preserving dimension reduction on biological shape spaces, Bioinformatics, doi:10.1093/bioinformatics/btv648.

44. Yang G. and Lee H.-C. (2015), Computational image analysis techniques for cell mechanobiology, in Micro and Nano Techniques in Cell Mechanobiology, Sun Y., Simmons C., Kim D.-H., eds., Cambridge University Press.

43. Chen K.-C., Yu Y., Kovacevic J., and Yang G. (2015) A sliding-window data aggregation method for super-resolution imaging of live cells, 2015 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 785-788.

42. Lee H.-C. and Yang G. (2015) Image-based computational methods for characterizing whole-cell scale spatiotemporal dynamics of intracellular transport, 2015 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 699-702. ISBI 2015 best paper award.

41. Yang G. (2014), Image-based computational tracking and analysis of spindle protein dynamics, in Experimental Techniques for Mitosis, Sharp D. ed., Methods in Molecular Biology, vol. 1136, DOI 10.1007/978-1-4939-0329-0_5, Springer.

40. Chen K.-C., Yang G., and Kovacevic J. (2014) Spatial density estimation based segmentation of super-resolution localization microscopy images, Proc. 2014 IEEE International Conference on Image Processing (ICIP), pp. 867-871.

39. Xu J.Q., Yu Y., Lee H.-C., Fan Q., Winter J., and Yang G. (2014) Cell penetrating peptide mediated quantum dot delivery and release in live mammalian cells, Proc. 36th Annual International Conference of IEEE Engineering in Medicine and Biology Society (EMBC2014), pp. 4260-4263.

38. Chen K.-C., Qiu M., Kovacevic J., and Yang G. (2014) Computational image modeling for characterization and analysis of intracellular cargo transport, Proc. of CompIMAGE'14, Lecture Notes in Computer Science, vol. 8641, pp. 292-303.  CompIMAGE’14 best paper award.

37. Lee H.-C. and Yang G. (2014) Computational removal of background fluorescence for biological fluorescence microscopy, Proc. 2014 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 205-208.

36. Lee H.-C. and Yang G. (2014) Integrating dimension reduction with mean-shift clustering for biological shape classification, Proc. 2014 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 254-257.

35. Chen K.-C. Kovacevic J., and Yang G. (2014) Structure-based determination of imaging length for super-resolution localization microscopy, Proc. 2014 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 991-994.

34. Gunawardena S., Yang G., and Goldstein L. S. B. (2013) Presenilin controls kinesin-1 and dynein function during AP vesicle transport in vivo, Human Molecular Genetics, vol. 22, pp. 3838-3843. 

33. Yang G. (2013), Bioimage informatics for understanding spatiotemporal dynamics of cellular processes (invited review), Wiley Interdisciplinary Review on Systems Biology and Medicine, vol. 5, pp. 367-380.

32. Yang G. and Olivo-Marin J.-C. (2013) Image-based representation and modeling of spatiotemporal cell dynamic, Proc. 2013 IEEE International Conference on Image Processing (ICIP), pp. 1198-1201.

31. Qiu M. and Yang G. (2013) Drift correction for fluorescence live cell imaging through correlated motion identification, Proc. 2013 IEEE International Conference on Image Processing (ICIP), pp. 452-455.

30. Booth-Gauthier E.A., Yang G., Dahl K. N. (2012), Shear stress induced changes in genome rheology and reorganization, Biophysical Journal, vol. 103, pp. 2423-2431.

29. Reis G.F.*, Yang G.*, Szpankowski, L., Weaver C., Shah S., Robinson J.T., Hays T. S., Danuser G., and Goldstein L.S.B. (2012), Molecular motor function in axonal transport in vivo probed by genetic and computational analysis in Drosophila, Molecular Biology of the Cell, vol. 23, pp. 1700-1714. (*: equal contribution authors)

28. Gable A., Qiu M., Titus J., Balchand S., Ferenz N. F., Ma N., Fagerstrom C., Ross R. L., Yang G., Wadsworth P. (2012), Dynamic reorganization of Eg5 in the mammalian spindle throughout mitosis requires dynein and TPX2, Molecular Biology of the Cell, vol. 23, pp. 1254-1266.

27. Roy S., Yang G., Tang Y., and Scott D. (2012), A simple photoactivation and image analysis module for visualizing and analyzing axonal transport with high temporal resolution, Nature Protocols, vol. 7, pp. 62-68, 2012.

26. Chen K.-C., Yu Y., Li R., Lee H.-C., Yang G., Kovacevic J. (2012) Adaptive active-mask image segmentation for quantitative characterization of mitochondrial morphology, Proc. 2012 IEEE International Conference on Image Processing (ICIP), pp. 2033-2036.

25. Qiu M., Lee H.-C., and Yang G. (2011) Nanometer resolution tracking and modeling of bidirectional axonal cargo transport, Proc. 2012 IEEE International Symposium on Biomedical Imaging (ISBI), pp. 992-995.

24. Weinger J.S., Qiu M., Yang G., Kapoor T.M. (2011), A nonmotor microtubule binding site in kinesin-5 is required for filament crosslinking and sliding, Current Biology, vol.21, pp. 1-7.

23. Matov A., Edvall M.M., Yang G., and Gaudenz Danuser (2011), Optimal‐flow minimum-cost correspondence assignment in particle flow tracking, Computer Vision and Image Understanding, vol. 115, pp. 531-540.

22. Yang G. (2011) Nanometer resolution imaging and tracking of axonal cargo transport in normal and degenerative neurons (invited paper), Proc. 45th Annual Asilomar Conference on Signals, Systems, and Computers, pp. 431-435.

21. Goodman B., Channels W., Qiu M., Iglesias P., Yang G.^, Zheng Y.^ (2010), Lamin B restrains spindle pole separation in Xenopus egg extracts, Journal of Biological Chemistry, vol. 285, pp. 35238-35244. (^: corresponding authors)

20. Houghtaling B., Yang G., Matov A., Danuser G., and Kapoor T. M. (2009), Op18 reveals the contribution of non-kinetochore microtubules to the dynamic organization of the vertebrate meiotic spindle, Proc. Nat. Acad. Sci. vol. 106, pp.15338-15343.

19. Applegate, K., Yang G., Danuser, G. (2009) Measuring the dynamic cytoskeleton architecture in living cells, in Nanomedicine and Nanobiotechnology, Vogel V. et al. eds., pp. 167-206, Wiley-VCH.

18. Cameron L.A., Houghtaling B., and Yang G. (2009), Quantitative Fluorescent Speckle Microscopy, in Optical Imaging Techniques, Yuste R. et al eds., pp. 667-682, Cold Spring Harbor Laboratory Press.

17. Yang G.*, Cameron L.A.*, Danuser G., and Salmon E.D. (2008), Regional variation of microtubule flux reveals microtubule organization in Xenopus extract meiotic spindles, Journal of Cell Biology, vol. 182, pp. 631-639. (*equal contribution authors)

16. Yang G.*, Houghtaling B.R.*, Gaetz J., Liu J.Z., Danuser G., and Kapoor T.M. (2007), Architectural dynamics of the meiotic spindle revealed by single-fluorophore imaging, Nature Cell Biology, vol. 9, pp. 1233-1242. (*equal contribution authors)

15. Haghnia M., Cavalli V., Shah S.B., Schimmelpfeng K., Brusch R., Yang G., Herrera C., Pilling A., and Goldstein, L.S.B. (2007), Dynactin is required for coordinated bidirectional motility, but not for dynein membrane attachment, Molecular Biology of the Cell, vol. 18, pp. 2081-2089.

14. Dorn J., Danuser G., and Yang G. (2007) Computational processing and analysis of dynamic fluorescence image data, in Fluorescent Proteins, Methods in Cell Biology, vol. 85, pp. 497-538.

13. Yang G. and Nelson, B.J. (2007) Fundamentals of microscopy and machine vision, in Life Science Automation: Fundamentals and Applications, Zhang M.J., Nelson B.J., and Felder R.A. eds., pp.125-149, Artech House.

12. Cameron L.A., Yang G., Cimini D., Canman J.C., Kisurina-Evgenieva O., Khodjakov A., Danuser G., and Salmon E.D. (2006) Kinesin 5-independent poleward flux of kinetochore microtubules in PtK1 cells, Journal of Cell Biology, vol. 173, pp. 173-179. (Cover)

11. Shah S., Yang G., Danuser G., and Goldstein L.S.B. (2006) Axonal transport: imaging and modeling of a neuronal process, in Proc. Nobel Symposium 131: Controlled Nanoscale Motion in Biological and Artificial Systems. Lecture Notes in Physics, vol. 711, pp. 65-84, Springer-Verlag.

10. Yang G. and Nelson B.J. (2005) Optomechatronic design of microassembly systems for manufacturing hybrid microsystems, IEEE Transactions on Industrial Electronics, vol. 52, pp. 1013-1023.

9. Yang G., Matov A., and Danuser G. (2005) Reliable tracking of large-scale dense particle motion for fluorescent live cell imaging, Proc. Workshop on Computer Vision Methods for Bioinformatics, IEEE Int. Conf. Computer Vision and Pattern Recognition. pp. 9-17.

8. Yang G., Gaines J.A., and Nelson B.J. (2003) A supervisory wafer-level microassembly system for hybrid MEMS fabrication, Journal of Intelligent and Robotic Systems, vol. 37, pp. 43-68.

7. Yang G., and Nelson B.J. (2003) Automated microassembly, in MEMS Packaging, T.-R. Hsu ed., pp. 109-140, IEE Press.

6. Yang G., and Nelson B.J. (2003) Wavelet-based autofocusing and unsupervised segmentation of microscopic images, Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), vol. 3, pp. 2143-2148.

5. Yang G., and Nelson B.J. (2003) Micromanipulation contact transition control by selective focusing and microforce control, Proc. IEEE Int. Conf. Robotics and Automation (ICRA), vol. 3, pp. 3200-3206.

4. Yang G., and Nelson B.J. (2002) Integration of microscopic vision and microforce feedback for microassembly, Proc. 3rd Int. Workshop on Microfactories, pp. 145-148.

3. Greminger M., Yang G., and Nelson B.J. (2002) Sensing nanonewton level forces by visually tracking structural deformations, Proc. IEEE Int. Conf. Robotics and Automation (ICRA), vol. 2, pp. 1943-1948.

2. Vikramaditya B., Nelson B.J., Yang G., and Enikov E.T. (2001) Microassembly of hybrid magnetic MEMS, Journal of Micromechatronics, vol. 1, pp. 99-116.

1. Yang G., Gaines J.A., and Nelson B.J. (2001) A flexible experimental workcell for efficient and reliable wafer-level 3D microassembly, Proc. IEEE Int. Conf. on Robotics and Automation (ICRA), vol. 1, pp. 133-138.