Webinar Recap | Inside WashU Engineering: Computer Science & Engineering Special Session

In June 2026, the McKelvey School of Engineering at Washington University in St. Louis (WashU) hosted an online special session featuring the Department of Computer Science & Engineering (CSE) and the Department of Electrical & Systems Engineering (ESE).

The session focused on key topics including artificial intelligence (AI), robotic systems, engineering education, research directions, and future career development. Faculty members and representatives from WashU Engineering introduced the school’s educational approach in AI and intelligent systems from multiple perspectives, including curriculum structure, research areas, program selection, and industry trends.

Talent Development: From Technical Knowledge to Complex Problem-Solving Skills

With the rapid advancement of artificial intelligence, the demand for interdisciplinary engineering talent continues to grow.

During the session, WashU Engineering introduced multiple graduate-level pathways related to artificial intelligence and emerging technologies, including:

• Computer Science

• Computer Engineering

• Cybersecurity Engineering

• Master of Engineering

• Data Mining & Machine Learning Certificate

The school emphasized that the development of artificial intelligence is not driven by a single technical field, but rather by the integration of multiple disciplines, including computer science, mathematics, statistics, logic, and engineering.

Therefore, engineering education at WashU focuses not only on helping students acquire technical expertise, but also on developing their abilities in:

• Analyzing and solving complex problems;

• Conducting innovative research;

• Collaborating across disciplines;

• Applying technologies to real-world scenarios.

Core Curriculum: From AI Fundamentals to Cutting-Edge Applications

In terms of curriculum design, WashU Engineering has developed a comprehensive AI learning pathway covering fundamental theories, algorithmic approaches, and practical applications.

Relevant courses and research areas include:

• Artificial Intelligence

• Machine Learning

• Reinforcement Learning

• Computer Vision

• Natural Language Processing

• Multi-Agent Systems

• Human-AI Interaction

• Large Language Models

• AI Safety

The session highlighted that although AI technologies are evolving rapidly, a strong foundation in computer science remains essential for advanced AI learning and research.

Algorithmic thinking, system design capabilities, and mathematical foundations continue to be critical components in developing future AI professionals.

Graduate Programs in CSE: How to Choose Between MS and MEng?

For graduate programs in Computer Science & Engineering (CSE), the session introduced two degree options with different educational goals.

Master of Science in Computer Science (MS in CS)

The MS program is more research-oriented and designed for students interested in academic research or future PhD studies.

The program structure includes:

• 3 core courses;

• 21 credits of elective courses;

• An optional 6-credit master’s thesis.

This program is suitable for students who:

• Plan to pursue a PhD degree;

• Are interested in algorithm research and fundamental technology development.

Master of Engineering in Computer Science & Engineering (MEng in CSE)

The MEng program places greater emphasis on engineering practice and professional development.

Key features include:

• No master’s thesis option;

• A 6-credit project as the capstone experience;

• Flexible course selection.

The program also allows students to:

• Take additional courses based on their academic background;

• Explore engineering or business-related electives;

• Expand career opportunities through interdisciplinary learning.

New ESE Program: Master of Engineering in Robotics and Intelligent Systems

The session also introduced the upcoming Master of Engineering in Robotics and Intelligent Systems (MEng in Robotics and Intelligent Systems) program offered by the Department of Electrical & Systems Engineering (ESE).

This program focuses on challenges arising as artificial intelligence enters the physical world, including:

• Autonomous driving systems affected by visual and environmental changes;

• Potential errors generated by large language models;

• Reliability challenges of intelligent systems operating in complex environments.

The program will mainly focus on two research directions:

1. Perception and Uncertainty Quantification

This area focuses on improving robots’ ability to understand and respond to changing environments.

Research topics include:

• Making decisions under changing lighting conditions and complex environments;

• Adjusting action strategies based on uncertain information;

• Improving the safety and reliability of intelligent systems.

2. Language-Guided Autonomous Systems

This area explores the application of large language models in autonomous systems.

Research focuses include:

• Translating natural language instructions into executable machine tasks;

• Improving interaction between AI systems and humans;

• Exploring applications of large language models such as ChatGPT and DeepSeek in intelligent systems.

Skills Required for Robotics and Intelligent Systems

The session highlighted that students pursuing robotics and intelligent systems should develop strong engineering foundations, including:

• Python / C++ programming skills;

• Experience with ROS (Robot Operating System) and simulation tools;

• Mathematical foundations in control systems, optimization theory, and machine learning.

Career Development: Building Competitiveness Through Coursework and Practical Experience

During the career development discussion, WashU introduced the regional industry environment and career opportunities available to engineering graduate students.

The St. Louis area offers technology and industry resources, including companies such as Boeing, as well as biomedical research institutions.

For engineering professionals with the following skill backgrounds, industry demand remains strong:

• Artificial Intelligence (AI);

• Computer Vision (CV);

• Image Processing;

• Biomedical Engineering.

The school encourages students to plan their practical experiences early and actively seek internship opportunities during their studies.

Academic Planning: From Course Adaptation to Research Opportunities

The session provided several recommendations for international students entering graduate programs.

During the first semester, students are encouraged to:

• Plan their course workload appropriately;

• Gradually adapt to the U.S. graduate education system;

• Build connections with professors through classroom participation.

During later stages of study, students can explore research opportunities, such as research rotations, to participate in laboratory projects and gain a deeper understanding of potential research areas.

Introduction to Multi-Agent Systems and Reinforcement Learning

The session also introduced research areas related to Multi-Agent Systems and Reinforcement Learning (RL).

Topics covered included:

• Multi-agent game theory;

• Markov Decision Processes (MDP);

• Q-learning algorithms;

• Intelligent decision-making methods in dynamic and uncertain environments.

These research areas are closely connected with the development of robotics, autonomous systems, and intelligent applications.

International Student Support: Application and Visa Services

For international students concerned about application procedures and visa processes, WashU introduced its related support services.

The session highlighted:

Apply Early

For fall admission, the application deadline is in late December. Students who submit complete applications early may receive admission decisions sooner, allowing additional time for visa preparation.

University Support

After admission, the Office for International Students and Scholars (OISS) provides support services, including visa guidance and informational resources.

If students encounter challenges during the visa process, they are encouraged to communicate with academic advisors and relevant university offices for assistance.