Class Presentations by Students

Each student is expected to lead a lecture of his/her choice of topics, with the instructor's apporval. All students are required to meet the instructor on one-to-one basis to discuss the lecture materials in detail prior to the presentation. One week before the scheduled presentation, s/he will be expected to submit a draft version of the presentation materials and an initial treatment of the selected topics. The instructor will provide timely feedback about the pre-talk. Reading materials and/or discussion issues will be posted on the course web site, at least one day prior to each lecture. All class members will be expected to have read the listed readings, by the start of the relevant class.

Important Deadlines:

  • By Sept 30, 2023 - Choose a presentation topic and inform the instructor
  • One week before the presentation - Submit a draft of presentation materials and select a 'discussant' to lead Q&A
  • One lecture before the presentation - Hand out copies of reading materials, if not available online
  • One day before the presentation - Post the presentation materials on the web
  • Instructions for posting the lecture notes, reading materials, etc.


    Here is the list of topics to be presented by students in the chronological order:

  • Neural Radiance Fields by Sam Audia (Oct 24, 2023)
  • Neural Radiance Fields and Leveraging NeRF to Dynamic Contents by Jacob Clements (Oct 24-26, 2023)
  • Leveraging NeRF to Dynamic Contents by Shengjie Xu (Oct 26, 2023)
  • Differentiable Navigation & Path Planning by Paul Zaidins (Oct 31, 2023)
  • Enhancing Sampling Efficiency in RL by Mohamed Bashir Dafaalla Elnoor (Oct 31-Nov 2, 2023)
  • Reinforcement Learning from Human Feedback (RLHF) by Bhrij Patel (Nov 2, 2023)
  • Physics Informed Neural Networks for Fluid Simulations by Cashen Diniz (Nov 7, 2023)
  • Differentiable Fluid Simulation by Shrey Patel (Nov 7-9, 2023)
  • Learning Vector Fields for Dynamical Systems by Cole Saborio (Nov 9, 2023)
  • NL-to-SQL Generation Models by Neal Ahmad Anwar (Nov 28, 2023)
  • Differentiable Circuit Simulation and Optimization by Xuliang Dong (Nov 30, 2023)
  • Differentiable Digital Signal Processing and JAX by Leslie Li (Nov 30, 2023)
  • 3D Pose Estimation Using Audiovisual Learning by Seong Jong Yoo (Nov 30-Dec 5, 2023)
  • Hand Manipulation by Amir-Hossein Shahidzadeh (Dec 5, 2023)
  • Differentiable Optics by Sachin Shah (Dec 5, 2023)
  • Differentiable Autonomous Driving by Darius Kianersi (Dec 7, 2023)
  • Differentiable Learning for Geometry Processing by Sathwik Yanamaddi (Dec 7, 2023)

  • Each student presentation will be graded based upon:

  • Advanced Preparation According to the Specification (40%)
  • Analysis and Discussion of the Materials (40%)
  • Style and Clarity of the Actual Presentation (20%)