About
Alan R. Siegel is an Associate Professor of Computer Science at New York University's College of Arts and Science. His research spans VLSI design, algorithm analysis, probability, combinatorial geometry, and mathematics education. He holds a Ph.D. (1983) and B.S. (1968) in Mathematics/Computer Science from Stanford University. His notable work includes studies on the Third International Mathematics and Science Study (TIMSS) and its implications for K-12 education, as well as foundational contributions to algorithmic hashing and geometric optimization.
Education:
- Ph.D., Computer Science, Stanford University, 1983
- B.S., Mathematics, Stanford University, 1968
Research Interests:
- VLSI design and circuit optimization
- Algorithm analysis and lower bounds
- Probability theory and median estimation
- Combinatorial geometry (e.g., isoperimetric inequalities)
- Mathematics education and international comparative studies
Key Contributions:
- Advanced hashing techniques for closed hashing (computable universal hash functions)
- Geometric optimization proofs for polygons and self-intersecting curves
- Analytical frameworks for median bounds in probability distributions
- Chernoff-Hoeffding bounds for heterogeneous random variables
Grants & Awards: None explicitly listed in the provided text.
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