ToDo-List & Ideas

Roadmap

Here are some ideas we hope to cover/implement in the future.

Time: Monday 3:00 pm CT

Location: Zoom (Ether)

Current schedule (2020 Fall)

DatePersonSubject
Sep. 21GeorgeAgent-based and non-markovian models of the spread of COVID-19
Oct. 05Kevin L.PSLQ
Oct. 19PaulLinear Sum Assignment
Nov. 02MayishaGraphing Temporal Dynamics in fMRI
Nov. 16Abid[Something computational topology]
Nov. 30GregPersistent Homology
Dec. 07RyanThe magic of NUTS

2016 schedule

2017sp schedule

2017fa schedule

2018sp schedule

2019sp schedule

2019fa schedule

2020sp schedule

Speaker Guidelines

TL;DR Do unto others as you would have them do unto you.

At minimum, an AIG presenter should prepare a few slides and an example code.

  1. The slides should explain: - what the algorithm is - how a minimum example works - why the algorithm might be practically useful
  2. A code that demonstrates the simplest problem the algorithm solves.
  3. Make a pull-request (PR) to the website repository to make your presentation and code eternal. Follow instructions in the README.md file.

The presentation should be 30-50 min if given without interruptions. Interactive elements are encouraged. e.g. a Jupyter notebook demo. with tweakable parameters given by the audience.

Ideas for presentations

  • Machine learning.
    • Back propogation.
    • Clustering.
    • Boltzmann machine.
  • Control theory and signal processing.
    • Model reduction.
    • Kalman filter.
    • Hidden markov model.
    • Proportional-integral (PI) controller.
  • Stochastic algorithms.
    • The Metropolis approach to sampling and alternatives
    • Global balance (pentalty method).
    • Quasi-random numbers.
    • Ant Colony Optimization
    • Parallel tempering.
    • Stochastic hill climbing.
    • Bayesian networks.
    • Simulated annealing
    • Evolutionary, and genetics algorithms.
    • Particle Swarm Optimization
    • Belief propogation
    • Gibbs sampling
  • Encryption.
    • Symmetric-key, Public-key (RSA) cryptography
    • Cryptanalysis (breaking encryption).
    • Hashing.
  • Optimzation.
    • Global Newton methods
      • line search
      • trust region
      • iterative solution of linear equations
      • matrix free
    • Generalized minimal residual method (GMRES)
      • preconditioning
      • additive Schwarts
      • Algebraic and geometric multi-grid
      • Block Jacobi
    • Quadratic optimization.
    • Convex optmization.
    • Steepest descent, Conjugate gradiant, Quasi-Newton, ….
    • Noisy optimization.
    • Compilers (fortan).
    • Simplex method.
  • Linear Algebra.
    • Random matrix theory.
    • QR / SVD. principle component analysis
    • Diagnolization, inversion.
    • Lanczos
    • Fast Fourier transforms (FFT).
  • Numerical solutions to differential equations.
    • Finite differences
    • Finite elements
    • Finite volumes
    • Spectral elements
    • PDE solvers (additional problems from multivariate)
    • Energy conserving or time-reversal invariant versions.
    • Runge-Kutta and family.
  • Data compression.
    • Image compression techniques (one or more).
    • Compressed sensing (probabilistic approach and connections to stat mech).
    • Compressed sensing (l-1 technique).
  • Image Processing
    • Image recognition
    • Automatic focus
  • Visualization
    • Marching Cubes
  • Quantum computing.
    • Quantum annealing.
    • Quantum error correction.
    • Quantum encryption.
    • Quantum stabilizers.
    • Grover algorithm.
    • Shor algorithm.
  • Parallelism.
    • Parallel linear algebra.
    • OpenMP and MPI
    • GPU, Cuda, …
  • Computer networks/the internet.
    • Google search bar, page rank.
    • The Internet protocal suite.
    • Packet switching vs. cell-based switching.
    • Mobile networks.
    • Error detection and correction, Hamming codes.
    • Internet security.
    • Network routing.
  • Classic CS algorithms
    • Quicksort, Graph theory, …
    • Cellular atomata.
    • Theory of computation (Turing, finite state machine, definition of language, regular expressions).
    • complexity theory.