Cincinnati, OH | Dayton, OH | San Francisco, CA
Also known as: vicfcs
Expertise in large-scale machine learning research and innovative applications, including: Dynamic graph link prediction ( social networks, drug vs. target gene networks), Image mining(MRI 3D brain images, developmental biology images), cloud computing, parallel computing. Experience: Tightly working with developmental biologists, MRI brain imaging neural scientists, and software engineers for several research projects, funded by NIH, NSF. Involved also in large-scale bioinformatics system development. Research published on tier 1 international research venues: NIPS, ICDM, ICPR, HBM, IEEE transactions, etc. Career Goals: Large-scale machine learning scientist / SDE position, to creatively solve challenging problems. Expected PhD graduation date: Oct 2011. Software programming skills: Java, Spring, Hibernate, C/C++/MFC, Matlab, Perl, PHP, MySQL, JavaScript, AJAX, etc; Package: MPI (parallel computing library), Hadoop, NVidia CUDA GPU computing library, OpenCV, OpenGL, etc; ?? ????????? ????????????????????????????????????????? ??????????????????????????????????????????????????????? ??????????????????????????????????????????“????�??????????????????? ???????????????????????????????????????????????????????????????????????????????????????? Specialties Keep in state-of-the-art in these research fields: Machine learning: supervised learning, unsupervised learning, semi-supervised learning, dimensionality reduction algorithms. Graph mining : social network, dynamic graph link prediction. Computer vision: content-based image retrieval, object detection, object tracking, etc.
