AE 598

Fall 2025 Part of Term 1

Part of Term 1
Aug 25-Dec 10

Special Topics

SHOW FINAL EXAM SCHEDULE

Credit: 1 TO 4 hours.

Subject offerings of new and developing areas of knowledge in aerospace engineering intended to augment existing formal courses. Topics and prerequisites vary for each section. See Class Schedule or departmental course information for both.

May be repeated in the same or separate terms if topics vary to a maximum of 12 hours.

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AE 598 class schedule data for fall 2025
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
59193	Online	EDO	ARRANGED	n.a.	n.a.	Tsukamoto, H	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Estimation of Dynamical System Section Info: Fundamentals of estimation of dynamical systems, with a special focus on aerospace systems: measurements and sensor fusion; observability and Luenberger observer; optimal estimation and Kalman filtering; nonlinear estimation; Bayesian filtering and sampling-based estimation; spacecraft orbit determination; estimation in aerospace systems. Prerequisite: STAT 361, STAT 400, or MATH 461; AE 353. Restricted to online non-degree, online MCS, online MSME, online MSCEE, and online MSAE students. For more details on this course section, please see http://engineering.illinois.edu/online/courses/. Non-Degree students may enroll on a space-available basis with consent of the Graduate Program Coordinator (ae-grad@illinois.edu). Restriction(s): Restricted to MS: Civil Engr - Online - UIUC, MS:Industrial Engr Online-UIUC, MS:Mechanical Engineerng -UIUC, MS:Env Engr CivilEngr ONL-UIUC, NDEG:Engineering GR ONL - UIUC, MS: Aerospace Engr-Online-UIUC, MENG:Engr:Energy Sys Onl-UIUC, MENG:Mech Engineering Onl-UIUC, MENG:Elec & Comp Eng ONL -UIUC, or MENG:Engr:AeroSys Online- UIUC.
55834	Lecture-Discussion	EDS	12:30PM -1:50PM	TR	403B2 Engineering Hall	Tsukamoto, H	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Estimation of Dynamical System Section Info: Fundamentals of estimation of dynamical systems, with a special focus on aerospace systems: measurements and sensor fusion; observability and Luenberger observer; optimal estimation and Kalman filtering; nonlinear estimation; Bayesian filtering and sampling-based estimation; spacecraft orbit determination; estimation in aerospace systems. Prerequisite: STAT 361, STAT 400, or MATH 461; AE 353.
65308	Lecture	MF	12:30PM -1:50PM	TR	3018 Campus Instructional Facility	Evrard, F Villafane Roca, L	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Multiphase Flows Section Info: This course provides a graduate-level introduction to multiphase flow theory and modeling. Topics that will be covered include: forces acting on particles, droplets, and bubbles; averaged governing equations for meso-/macro-scale modeling; particle-turbulence interactions; surface tension at interfaces between immiscible phases. A list of final project themes will be given by the instructor, but students are welcome to propose their own. Prerequisites: Fluid Dynamics (AE 311, AE 312, AE 412, TAM 435, or equivalent), or permission from instructor.
63703	Online	MFO	ARRANGED	n.a.	n.a.	Evrard, F Villafane Roca, L	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Multiphase Flows Section Info: This course provides a graduate-level introduction to multiphase flow theory and modeling. Topics that will be covered include: forces acting on particles, droplets, and bubbles; averaged governing equations for meso-/macro-scale modeling; particle-turbulence interactions; surface tension at interfaces between immiscible phases. A list of final project themes will be given by the instructor, but students are welcome to propose their own. Prerequisites: Fluid Dynamics (AE 311, AE 312, AE 412, TAM 435, or equivalent), or permission from instructor. Restricted to online graduate non-degree, online MCS, online MSME, online MSCEE, and online MSAE students. For more details on this course section, please see http://engineering.illinois.edu/online/courses/. Non-degree students may enroll on a space-available basis with consent of the Graduate Program Coordinator (ae-grad@illinois.edu). Restriction(s): Restricted to MS: Civil Engr - Online - UIUC, MS:Industrial Engr Online-UIUC, MS:Mechanical Engineerng -UIUC, MS:Env Engr CivilEngr ONL-UIUC, NDEG:Engineering GR ONL - UIUC, MS: Aerospace Engr-Online-UIUC, MENG:Engr:Energy Sys Onl-UIUC, MENG:Mech Engineering Onl-UIUC, MENG:Elec & Comp Eng ONL -UIUC, or MENG:Engr:AeroSys Online- UIUC.
42991	Online	ONE	ARRANGED	n.a.	n.a.	Tsukamoto, H	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Estimation of Dynamical System Section Info: This section is for students who have time conflicts with the in-person section of Estimation of Dynamical Systems. Please email aero-ugrad-advising@illinois.edu to request approval to register for this section. Students in this section will be expected to attend on-campus office hours and exams for this course.
39795	Online	ORL	ARRANGED	n.a.	n.a.	Tran, H	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Reinforcement Learning Section Info: Topic: Multi-Agent Reinforcement Learning. Description: This course will discuss concepts and algorithms for multi-agent reinforcement learning (MARL). The goal is for students to understand: (1) key concepts, (2) key algorithms and their implementation, and (3) new topics in the field. Topics include single-agent reinforcement learning (MDPs, value-based methods, policy methods), games, tabular MARL algorithms, and deep learning-based MARL algorithms. Prerequisites: probability and statistics (STAT 361, STAT 400, ISE 300, or equivalent) or permission from the instructor. Restricted to online graduate non-degree, online MCS, online MSME, online MSCEE, and online MSAE students. For more details on this course section, please see http://engineering.illinois.edu/online/courses/. Non-degree students may enroll on a space-available basis with consent of the Graduate Program Coordinator (ae-grad@illinois.edu). Restriction(s): Restricted to MS: Civil Engr - Online - UIUC, MS:Industrial Engr Online-UIUC, MS:Mechanical Engineerng -UIUC, MS:Env Engr CivilEngr ONL-UIUC, NDEG:Engineering GR ONL - UIUC, MS: Aerospace Engr-Online-UIUC, MENG:Engr:Energy Sys Onl-UIUC, MENG:Mech Engineering Onl-UIUC, MENG:Elec & Comp Eng ONL -UIUC, or MENG:Engr:AeroSys Online- UIUC.
70408	Lecture-Discussion	RL	2:00PM -3:20PM	TR	410B1 Engineering Hall	Tran, H	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Reinforcement Learning Section Info: Topic: Multi-Agent Reinforcement Learning. Description: This course will discuss concepts and algorithms for multi-agent reinforcement learning (MARL). The goal is for students to understand: (1) key concepts, (2) key algorithms and their implementation, and (3) new topics in the field. Topics include single-agent reinforcement learning (MDPs, value-based methods, policy methods), games, tabular MARL algorithms, and deep learning-based MARL algorithms. Prerequisites: probability and statistics (STAT 361, STAT 400, ISE 300, or equivalent) or permission from the instructor.