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Home Page for Shuvra Nath | Parasol Laboratory

Picture Shuvra Nath
MS Student
Algorithms & Applications Group

Parasol Laboratory url: http://parasol.tamu.edu/~shuvra03/
Department of Computer Science and Engineering email:
Texas A&M University office: 407C HRBB
College Station, TX 77843-3112 tel: (979) 402-0126
USA fax: (979) 458-0718

I am a MS student at Texas A & M University currently working with Professor Nancy Amato. I am currently working on randomized motion planning algorithms and their applications in the field of Computational Biology. I have also interest in path smoothing and user guided motion planning.


My research interests include Motion Planning and Computational Biology.

Access my CV here


Computational Biology:

Protein Folding
Study of protein folding can help us to develop better structure prediction algorithms. It can also help to find a better treatment for diseases like Alzheimer's and Mad cow which are caused by misfolded proteins. We model protein folding at its various stages using motion planning algortihms and simulate our proteins like robots having a high degree of freedom
Motion Planning:
Multi-directional Rapidly Exploring Random Graph (mRRG)
In this work, we propose multi-directional Rapidly Exploring Random Graph (mRRG) for robotic motion planning which is a variant of Rapidly Exploring Random Graph (RRG). Instead of expanding a vertex in the tree towards a single random direction during each iteration, mRRG expands the vertex towards m random directions. Our results show that searching in multiple directions in this way produces bushier roadmaps with shorter paths and more topologically distinct paths than previous methods. For proteins we show that our method is effective in achieving better energy landscape coverage and more unfolded pathways quickly as compared to T-RRT and PRM.


Protein Folding

A Multi-Directional Rapidly Exploring Random Graph (mRRG) for Protein Folding, Shuvra Nath, Shawna Thomas, Chinwe Ekenna, Nancy M. Amato, In ACM Conference on Bioinformatics, Computational Biology and Biomedicine, pp. 44-51, Orlando, FL, USA, Oct 2012.
Proceedings(ps, pdf, abstract)