{"685313":{"#nid":"685313","#data":{"type":"news","title":"Georgia Tech Students Take Charge with New AI and Engineering Course","body":[{"value":"\u003Cp\u003ETwo Georgia Tech Ph.D. students created a student-run, faculty-graded, fully-accredited course that links math, engineering and machine learning.\u003C\/p\u003E\u003Cp\u003EAndrew Rosemberg, with assistance from Michael Klamkin, both student researchers with the U.S. National Science Foundation AI Research Institute for Advances in Optimization (AI4OPT), designed the course to bridge gaps they saw in existing classrooms.\u003C\/p\u003E\u003Cp\u003E\u201cWhile Georgia Tech offers excellent courses on optimization, control, and learning, we found no single class that connected all these fields in a cohesive way,\u201d Rosemberg said. \u201cIn our research, it was clear these topics are deeply interconnected.\u201d\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EProblem-driven learning\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThe course starts with fundamental problems and works backward to the methods required to solve them. Rosemberg said this approach was intentional. He said that courses often center around methods in isolation rather than showing how the methods contribute to the larger context. This keeps the course focused on problem-driven discovery.\u003C\/p\u003E\u003Cp\u003EThe class also serves as a way for Rosemberg and Klamkin to strengthen their own teaching and mentoring skills.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EGoals and structure\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThe primary goal of the course is to help students build a clear understanding of how mathematical programming, classical optimal control, and machine learning techniques such as reinforcement learning connect to one another. Students are also working to produce a structured book by the end of the semester.\u003C\/p\u003E\u003Cp\u003E\u201cThe hope is that this resource will not only solidify our own learning but also serve as a guide for other students who want to approach these problems in the future,\u201d Rosemberg said.\u003C\/p\u003E\u003Cp\u003EResponsibilities are distributed across participants, with each student delivering lectures, reviewing peers\u2019 work, and contributing to collective discussions. Rosemberg and Klamkin provide additional support where needed, while faculty mentor and director of AI4OPT, Pascal Van Hentenryck, ensures the class stays aligned with broader academic objectives.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EStudent ownership and collaboration\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003ERosemberg noted that the student-led model gives students a deeper sense of ownership, making them responsible for their own learning, and having a stronger impact. This model allows students to determine what to learn and why, which promotes critical thinking.\u003C\/p\u003E\u003Cp\u003EThe course uses GitHub as its primary workflow platform. Rosemberg said adds transparency and prepares students for real-world research practices.\u003C\/p\u003E\u003Cp\u003E\u201cGitHub functions much like university systems such as Canvas or Piazza. It also has the added benefit of making all contributions visible to the world,\u201d Rosemberg explained. \u201cThis helps students take pride and ownership of their work, while also introducing them to Git, an essential tool for software development and modern STEM research.\u201d\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EEmerging insights and challenges\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EStudents have begun aligning their research with course themes, including shaping qualifying exam topics around the intersections of operations research, optimal control and reinforcement learning. Rosemberg said exploring the comparative strengths of these fields side by side has been one of the most rewarding outcomes.\u003C\/p\u003E\u003Cp\u003EBalancing independence with guidance has proven to be the greatest challenge. He said they have been evolving alongside the students in real time and have learned to emphasize mutual responsibility to promote the collective progress of the class.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003ELooking ahead\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003ERosemberg said future iterations of the course may place more emphasis on setting expectations early, given the effort required to deliver a lecture in this format.\u003C\/p\u003E\u003Cp\u003EHis advice for others who may want to replicate the model is to focus on building a committed core team.\u003C\/p\u003E\u003Cp\u003E\u201cStart with a small, motivated group,\u201d Rosemberg said. \u201cLike a startup, success depends less on the structure and more on the dedication of the people involved.\u201d\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAndrew Rosemberg, with assistance from Michael Klamkin, both AI4OPT Institute student researchers, designed the course to bridge gaps they saw in existing classrooms.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Two Georgia Tech Ph.D. students created a student-run, faculty-graded, fully-accredited course that links math, engineering and machine learning."}],"uid":"36660","created_gmt":"2025-09-26 15:50:18","changed_gmt":"2025-09-26 16:09:43","author":"jbjorne3","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Panama City, Panama","dateline":{"date":"2025-09-26T00:00:00-04:00","iso_date":"2025-09-26T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"678161":{"id":"678161","type":"image","title":"4.png","body":null,"created":"1758902158","gmt_created":"2025-09-26 15:55:58","changed":"1758902158","gmt_changed":"2025-09-26 15:55:58","alt":"Georgia Tech Student Led Class","file":{"fid":"262150","name":"4.png","image_path":"\/sites\/default\/files\/2025\/09\/26\/4.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2025\/09\/26\/4.png","mime":"image\/png","size":4028175,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2025\/09\/26\/4.png?itok=NBu-DXn_"}}},"media_ids":["678161"],"groups":[{"id":"1214","name":"News Room"},{"id":"1188","name":"Research Horizons"},{"id":"660368","name":"Tech AI (Artificial Intelligence)"}],"categories":[{"id":"194606","name":"Artificial Intelligence"}],"keywords":[{"id":"188776","name":"go-research"},{"id":"187915","name":"go-researchnews"}],"core_research_areas":[{"id":"193655","name":"Artificial Intelligence at Georgia Tech"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EJaci Bjorne\u003C\/p\u003E","format":"limited_html"}],"email":["jaci@gatech.edu"],"slides":[],"orientation":[],"userdata":""}}}