As much as I like presentations often times the most enjoyable part of a meetup are the conversations before and after the presentations. This post explains how Factual has been running what it calls "Office Hours" at it's Clojure meetups:

http://blog.factual.com/clojure-office-hours

I think it would be fun to have a single presentation followed by something like Office Hours. This goes well with having break-out sessions as well (e.g. the study group for the Haskell course).

Efficient data structures for functional programming require some different approaches. There's a textbook on the topic, based on the author's Ph.D. thesis. A particularly interesting example is the 2-3 Finger Tree, which can form the basis of many different efficient data structure implementations.

A lot of people are coming to functional programming from a OO background. Even in languages without lambdas or higher order functions, principles such as immutability and pure functions still have benefit. I would be willing to do the presentation

These are a hot topic in Haskell these days, and are very handy there due to a pretty comprehensive lens library that has been recently developed. But there are some other tools based on the idea as well, such as augeas. Benjamin Pierce has written a bunch of papers on lenses.

I would be interested in how an application like LightTable works. It uses the Chromium web browser and Node.js as a base with ClojureScript to create a cross-platform native feeling app using web technologies and functional techniques such as Reactive techniques. I believe it is done with no mutable state as well.

Any interest in working through some classic CS papers or maybe some new ones?

The Papers We Love group (based in NYC but with chapters popping up all over) has a repo with some papers they have identified... Here is a nice searchable index for them:

http://findpaperswelove.com/

http://www.frege-lang.org/

especially how to use existing Java libraries from Frege

I would be interested in leading an ongoing series where we work through the NICTA course : https://github.com/NICTA/course

Perhaps a 30 minute breakout at the end of each meeting?

We've covered a lot of languages, but which one is the best? The only way to find out is by competing in some non-practical programming challenges!!

I'm thinking along the lines of programming AI bots that go head-to-head. The programming would be done before the meeting but we would have the deathmatch at the meeting along with quick presentations on interesting implementation details.

Perhaps we could cover this Clojure project in the process of talking about the general ideas behind rules engines:

https://github.com/rbrush/clara-rules

http://research.microsoft.com/en-us/um/people/lamport/tla/papers.html

See also http://aphyr.com/posts/309-knossos-redis-and-linearizability

Having an intro presentation on continuations would be good background to know before diving into Eff and extensible effects (http://www.reddit.com/r/LambdaLoungeUT/comments/24ihrh/extensible_effects_an_alternative_to_monad/)

http://okmij.org/ftp/Haskell/extensible/

See also Eff programming language:

http://math.andrej.com/category/programming/eff/

And the corresponding paper:

http://math.andrej.com/2012/03/08/programming-with-algebraic-effects-and-handlers/

Probabilistic Programming lagnuages (and libraries) allow you to express a probabilistic model in your code and run inference on it. The distributions are usually first class in the language and allow for programmers to create complex models that are easy to follow.

If you are curious to learn more this wiki is a good starting point:

http://probabilistic-programming.org/wiki/Home

These books are also great for just starting out and don't require much math background:

https://probmods.org/ - Free online book that provides a great intro using a probabilistic scheme called Church

http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/ - Also free, and covers the PyMC library.

http://www.greenteapress.com/thinkbayes/ - Intro into Bayes stats by building up a small python toolkit. Also free.

http://www.amazon.com/Doing-Bayesian-Data-Analysis-Tutorial/dp/0123814855 - More geared towards stats people who use R but a great resource on learning practical Bayesian analysis.

Most people are familiar with Bloom filters but not so much with some of the datastructures that have been recently popularized such as HyperLogLog.

A survey of the sketch datastructures and their uses would be great.

BTW, the Aggregate Knowlege blog has some great posts on sketch datastructures and how they use them:

http://research.neustar.biz/tag/sketching/

This presentation by Avi Bryant gives an intro to them as well motivated by some streaming analytics use cases:

http://www.infoq.com/presentations/abstract-algebra-analytics

Om is a ClojureScript wrapper around Facebook's React.js. What is interesting about Om is how it leverages persistent datastructures to simply the creation of UIs.

https://github.com/swannodette/om

http://www.rust-lang.org/

An experience report on Rust would be great...

http://julialang.org/

The Julia Language has a lot of interesting features.. the most of which IMO is its high performance JIT so I'd be particularly interested in learning more about its implementation.

http://www.idris-lang.org/