Difference between revisions of "CMS 273, Winter 2021"

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* Michael Dickinson (BBE): Modeling and control of the effects of bilateral asymmetries in insect flight
* Michael Dickinson (BBE): Modeling and control of the effects of bilateral asymmetries in insect flight
* Frederick Eberhardt (HSS): Novel causal discovery algorithm for an application in cognitive neuroscience
* Frederick Eberhardt (HSS): Novel causal discovery algorithm for an application in cognitive neuroscience
* Bethany Ehlmann (GPS): Extracting Maximum Compositional Information from Hyperspectral Images for Earth and Planetary Exploration
* Bethany Ehlmann (GPS): Extracting maximum compositional information from hyperspectral Images for Earth and planetary exploration
* Christian Frankenberg (GPS): Trace gas plume detection and flux estimation from 2D imagery
* Christian Frankenberg (GPS): Trace gas plume detection and flux estimation from 2D imagery
* Matt Thomson (BBE): Real-time machine learning with self-organized neural networks
* Matt Thomson (BBE): Real-time machine learning with self-organized neural networks

Revision as of 06:58, 2 November 2020

Frontiers in Computing and Mathematical Sciences

Winter 2021
  • Organizers: Richard Murray (murray@caltech.edu), E. Schmidt, S. Feldman
  • Class meeting: 5 Jan (Tue), 12 pm via Zoom

The purpose of this course is to explore applications of tools from Computing and Mathematical Sciences to new problem domains. The course is organized around small teams consisting of CMS and non-CMS students who will work on projects of mutual interest in some faculty member's research area. Our main goals are for the participating CMS and science/engineering faculty to become more familiar with each other's work and expertise, and to get our graduate students interacting with one another.

The output of the course will be a short paper of the sort that could be sent to a conference. The paper should consist of a short description of the problem under study and the relevant CDS tools, followed by a preliminary set of results and a description of next steps to be pursued.

Course Schedule

WeekDateEvent
1TBDOrganizational meeting, 12 pm
TBDFirst team meeting, Location TBD @ 12 pm
2-4Work in teams; define problem to be studied + approaches
5TBDMidterm presentations, location and time TBD
6-8Work in teams
9TBDFinal presentations, location and time TBD
11TBDFinal reports due (by 5 pm)

Projects

  • Michael Dickinson (BBE): Modeling and control of the effects of bilateral asymmetries in insect flight
  • Frederick Eberhardt (HSS): Novel causal discovery algorithm for an application in cognitive neuroscience
  • Bethany Ehlmann (GPS): Extracting maximum compositional information from hyperspectral Images for Earth and planetary exploration
  • Christian Frankenberg (GPS): Trace gas plume detection and flux estimation from 2D imagery
  • Matt Thomson (BBE): Real-time machine learning with self-organized neural networks
  • Magda Zernicka-Goetz (BBE): Migration of the of the anterior signaling centre to specify location of the head / Building a developmental atlas of mammalian gastrulation - a dynamic molecular colouring book

Resources

Units and Grading

CMS 273 is a 9 unit course, offered either graded or pass/fail. Each team is expected to complete the following:

  • Project presentation: each team will make short (15-20 min) presentations in the middle and toward the end of the term, describing the focus of their project. Comments on these presentations will be provided to the team for incorporation in the final report.
  • Final report: each team will prepare a paper describing their work during the term. This should build on the midterm report by including some preliminary results and/or case studies.

In order to complete the work for the term, each team should plan on meeting at least once per week. The first team meeting will be on Friday, 10 Jan, at 12 pm in 107 Annenberg (at which time a regular meeting time can be established by the team).