This course studies machine learning methods for molecular science. It covers the scientific foundations, neural architectures, and generative models used in applications such as drug and materials discovery.

The reusable written material is collected in the Machine Learning for Molecules lecture-note path.

Course format

This is a discussion-based course. Students watch the uploaded lecture videos before each class. Class time is reserved for questions, clarification, and discussion rather than a repetition of the videos.

The seminar sessions focus on paper reading and special topics. Students should read the assigned material before class and come prepared to discuss it.

Teaching team

  • Instructor: Prof. Sungsoo Ahn, KAIST
  • Invited lecturer: Prof. Sungbin Lim, Korea University

Schedule

Class meets every Monday and Wednesday from 10:30 AM to 12:00 PM, beginning Aug. 31. Invited-talk speakers will be announced after they are confirmed.

Lecture Date Topic Details
1 Aug. 31 (Mon) Introduction Separate introductions by Prof. Sungbin Lim and Prof. Sungsoo Ahn
2 Sep. 2 (Wed) AI for Science Basics Density functional theory and molecular dynamics
3 Sep. 7 (Mon) AI for Science Basics Drug discovery
4 Sep. 9 (Wed) AI for Science Basics Materials discovery
5 Sep. 14 (Mon) AI for Science Basics  
6 Sep. 16 (Wed) AI for Science Basics  
7 Sep. 21 (Mon) Architectures  
8 Sep. 23 (Wed) Architectures  
9 Sep. 28 (Mon) Architectures  
10 Sep. 30 (Wed) Architectures  
11 Oct. 5 (Mon) No class Public holiday: National Foundation Day (substitute holiday)
12 Oct. 7 (Wed) Architectures  
13 Oct. 12 (Mon) Midterm  
14 Oct. 14 (Wed) Midterm  
15 Oct. 19 (Mon) Generative Models  
16 Oct. 21 (Wed) Generative Models  
17 Oct. 26 (Mon) Generative Models  
18 Oct. 28 (Wed) Generative Models  
19 Nov. 2 (Mon) Generative Models  
20 Nov. 4 (Wed) Generative Models  
21 Nov. 9 (Mon) Generative Models  
22 Nov. 11 (Wed) Generative Models  
23 Nov. 16 (Mon) Seminar Paper reading and special topics
24 Nov. 18 (Wed) Seminar Paper reading and special topics
25 Nov. 23 (Mon) Seminar Paper reading and special topics
26 Nov. 25 (Wed) Seminar Paper reading and special topics
27 Nov. 30 (Mon) Seminar Paper reading and special topics
28 Dec. 2 (Wed) Seminar Paper reading and special topics
29 Dec. 7 (Mon) Invited talk Speaker to be announced
30 Dec. 9 (Wed) Invited talk Speaker to be announced
31 Dec. 14 (Mon) Invited talk Speaker to be announced
32 Dec. 16 (Wed) Invited talk Speaker to be announced