Welcome to Ying Ding's Home Page

I am Ying Ding (丁影), a Ph.D. candidate of Joint CMU-Pitt Program in Computational Biology. My research advisor is Prof. Zuckerman.

Department of Computational Biology
School of Medicine, University of Pittsburgh
3501 Fifth Avenue
Suite 3064, Biomedical Science Tower 3 (BST3)
Pittsburgh, PA 15260

Email: yid5"at"pitt.edu or yingd"at"cmu.edu

If you wish to be the best man, you must suffer the bitterest of the bitter.

• Monte Carlo Statistical Sampling

Statistical Sampling of peptides and proteins in a fast fashion using various monte carlo statistical sampling methods such as Sequential Monte Carlo (SMC), Markov Chain Monte Carlo (MCMC), Annealled Importance Sampling (AIS).

• Statistical Learing Theory

• Artem B. Mamonov, Divesh Bhatt, Derek J. Cashman, Ying Ding, and Daniel M. Zuckerman.
  General library-based monte carlo technique enables equilibrium sampling of semi-atomistic protein models.
  The Journal of Physical Chemistry B, 113(31):10891–10904, 2009.[pdf]

 

• Ying Ding, Artem B. Mamonov and Daniel M. Zuckerman.
  Efficient equilibrium sampling of all-atom peptides using Library-Based Monte Carlo. (in revision) [pdf]

2007-2008 Outstanding Academic Achievement Award of Joint CMU-Pitt PHD Program in Computational Biology

B.S. Bioinformatics, Huazhong University of Science and Technology (China)

Probability and Mathematical Statistics I (CMU) (Fall 2007)

Cellular and Systems Modeling (CMU) (Fall 2007)

Molecular Biophysics I (Pitt) (Fall 2007)

Machine Learning (CMU) (Spring 2008)

Computational Structural Biology I (Pitt) (Spring 2008)

Laboratory Methods for Computational Biologists (Pitt) (Spring 2008)

Scientific Ethics (Pitt) (Summer 2008)

Computational Physics (Pitt) (Fall 2008)

Computational Genomics(CMU) (Spring 2009)