|Title:||Lecturer and CS100 Course Coordinator|
- PhD, Computer Science, State University of New York at Stony Brook, 2001. Advisor Steven Skiena
- Internship at IBM Thomas J. Watson Research Center, Deep e-Commerce Department, summer 2000, optimization problems
- Eleventh International School for Computer Science Researchers in Computational Biology, University of Catania, 1999
- BS, computer science, City University of New York, 1994, cum laude
- DIMACS-Celera Genomics Graduate Student Award, 2001
- Graduate Council Fellow, SUNY, 1996-present
- Runner up for Best Speaker Award, Graduate Research Conference 2000, SB Dept of Computer Science
Introduction to Computational Biology CIS 786 Spring 2004
Introduction to Computer Science I CIS 113 Fall 2003
Introduction to Computational Biology CIS 786 Spring 2003
Object Oriented Programming CIS 601 Fall 2002
Introduction to Computational Biology CIS 786 Spring 2002
Data Structures and Algorithms CIS 335 Spring 2001
Current work focuses on the topography of the RNA coding space corresponding to a target protein. The objective is to shed light on the question: Of the exponentially many sequences which could encode a certain protein, why does evolution select a particular one? Also, algorithms to design energetically minimal and maximal RNA sequences which code for a target protein. Designing RNA Structures: Natural and Artificial Selection (with Steve SkiePublicationsna), Recomb 02 (forthcoming).
Optimizing Combinatorial Library Construction via Split Synthesis, (with Steve Skiena), Recomb99.
A presentation in chemist-friendly format of the findings on efficient use of split synthesis to create libraries of organic compounds. Efficient Split Synthesis for Targeted Libraries, Journal of Combinatorial Chemistry; 2000; 2(1); 10-18.
We model the synthesis of a library of small organic molecules by split synthesis technology as a directed, acyclic graph, and develop two robust and efficient algorithms for reducing the size of the dag while restricting the number of compounds generated. The paper includes extensive data from simulations.