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, 2021 - 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:

  • Introduction to Quantum Computing by Yuxiang Peng (Oct 5, 2021)
  • Variational Quantum Methods by Yiling Qiao (Oct 5, 2021)
  • Quantum Differentiable Programming by Haowei Deng and Kaiyan Shi (Oct 7, 2021)
  • Differentiable Agent-based Traffic Simulation & Reinforcement Learning by Montana Hoover, Ben Moskowitz, and Laura Zheng (Nov 2, 2021)
  • Pontryagin Differentiable Programming: Differentiable Control by Senthil Hariharan Arul (Nov 4, 2021)
  • Differentiable Autonomous Driving by Xijun Wang (Nov 4, 2021)
  • Differentiable Traffic Simulation by Sang Hyun Son (Nov 9, 2021)
  • Solving PDE Using Neural Networks by Hsien-Yu Meng (Nov 9, 2021)
  • Differentiable Convex Optimization by Sahil Singla (Nov 16, 2021)
  • Differentiable Physics & Rendering by Will Chambers (Nov 16, 2021)
  • Differentiable Rendering by Saeed Hadadan (Nov 18, 2021)
  • Neural Differentiable Rendering by Divya Kothandaraman (Nov 18, 2021)
  • Differentiable Graph Networks by Kezhi Kong (Dec 2, 2021)
  • Graph Convolutional Network by Zhiyuan (Howard) Hua (Dec 2, 2021)
  • Differentiable Point Registration by Jing Liang (Dec 9, 2021)
  • Therbligs for Action Segmentation ctionSegmentation.pptx by Eadom Dessalene (Dec 9, 2021)

  • 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%)