American Univesity of Beirut

Saadeddine Mneimneh

​​​Brief on current research

​​​​Prof. Mneimneh’s research focus is in algorithms and the mathematical modeling of various physical and biological systems with applications to networks, graphs, optimization and approximation algorithms, computational biology, probabilistic analysis, and discrete mathematics. Some of his current research that He believe could foster collaboration/discussion with CAMS members includes (but is not limited to) the following topics:

  • Networks: preferential attachment in hypergraphs and simplicial complexes
  • Biology: Optimization problems inspired by RNA interactions
  • Discrete Mathematics: Infinite Skolem sequences, counting right triangles on a grid, and variations on the Tower of Hanoi.
  • Probabilistic analysis: Blindsort (a sorting algorithm that is not allowed to read) and random formations of islands (and pools) on a two dimensional surface.

Some of these topics can also provide rich material for student engagement through seminars and/or small projects. In particular, several aspects related to blindsort, Skolem sequences, and the Tower of Hanoi make interesting simulation and analysis projects.

Schedule o​​f Lectures

  • ​Lecture 1: July 19, 2022 at 3pm - College Hall, Auditorium B1
    Title: Modeling and Analysis of Affiliation Networks with Preferential Attachement and Subsumption
    Abstract: Preferential attachment describes a variety of graph-based models in which a network grows incrementally via the sequential addition of new nodes and edges, and where existing nodes acquire new neighbors at a rate proportional to their degree. Some networks are better described as groups of nodes rather than a set of pairwise connections. These groups are called affiliations, and the corresponding networks affiliation networks. When viewed as graphs, affiliation networks do not necessarily exhibit the power law distribution of node degrees that is typically associated with preferential attachment. They do, however, when viewed as hypergraphs and simplicial complexes (a special case of hypergraphs), suggesting an underlying evolutionary preferential attachment mechanism not at the graph level. I will present such mechanism for affiliation networks and discuss some of the resulting properties, such as assortativity, clustering coefficient, and distances.

  • Lecture 2: July 21, 2022 at 3pm - College Hall, Auditorium B1
    Title: Fibonacci where you least expect it
    Abstract: People have always been fascinated by the Fibonacci sequence, patterns associated with it, and of course the well celebrated golden ratio. I came across all of these in my teachings about programming and algorithms, unexpectedly. I will share my experience with three problems, each of which started as a simple programing task, and ended up being Fibonacci-ish when pursued mathematically. This talk might be of interest to students in computer science and mathematics, but also to a general audience who does not mind a little bit of math in their daily life.​

Biogrpahy: Saad Mneimneh is an associate professor in computer science at Hunter College of the City University of New York (CUNY). His research is in network algorithms and biologically inspired computational problems, including switching, load balancing, and multiple RNA interaction. Recently, he has been focusing on mathematical modeling of networks and physical/biological systems, probabilistic analysis and statistics, and discrete mathematics. He received a BE in Computer and Communication E​ngineering from the American University of Beirut (AUB) in June 1995, and MS and PhD from MIT in June 2002. He joined Southern Methodist University in 2003 and was visiting Professor at the City University of New York (CUNY) from 2006 to 2011. He joined CUNY in 2012. He is a recipient of a number of research Awards from industry, NSF, and private research foundations. Professor Mneimneh is a doctoral faculty at The Graduate Center of CUNY. He is currently visiting AUB for a summer position jointly sponsored by CAMS and MSFEA.

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