ASME 2026 Student Hackathon
Background
The Computer & Information in Engineering (CIE) Division of the American Society of Mechanical Engineers (ASME) held past hackathon events at the IDETC/CIE 2020, 2021, 2022, 2023, 2024, and 2025 Conferences. events have provided students and engineering practitioners with a unique platform to explore how cutting-edge data science and machine learning techniques can address real-world engineering challenges.
Building on this legacy, the CIE Division is excited to host the ASME-CIE Hackathon once again at the IDETC/CIE 2026 Conference. This year's hackathon will focus on AI for integrated design-to-manufacturing, exploring how advanced AI systems can support geometry reasoning, design optimization, CAD model editing, and automated manufacturing planning. The challenges reflect the future of industrial intelligence, where AI helps connect engineering intent, design decisions, and production-ready workflows across the full product development lifecycle.
Participants will have the opportunity to work with state-of-the-art datasets and tackle pressing and innovative challenges in the field, gaining hands-on experience with the tools and techniques shaping the future of engineering innovation.
The event will be held in a hybrid format, combining both virtual and on-site participation, and will take place as a pre-conference event.
Hilton Americas Houston
Houston, TX
August 13 - 22, 2026 virtually and August 23, 2026 in person
in conjunction with
ASME IDETC/CIE 2026 Conference (August 23 - 26, 2026 in person)
Registration Details
- A $50 registration fee per participant will apply for the Hackathon event. Participants can register either as a conference add-on or as a stand-alone event.
- This is a hybrid event, offering both virtual and on-site participation options. If you are unable to attend in person, please email us at idetccie.seikm@gmail.com so we can assist you in connecting virtually.
- Participants are not limited in the number of problems they can choose to tackle during the Hackathon.
Register
Important Dates
August 11, 2026, 11:59pm EDT
Registration Deadline
August 13, 2026, 12 – 3pm EDT
Virtual Hackathon Kick-off
August 23, 2026
Hybrid Hackathon Closing
August 23, 2026, 6am EDT
due for Hackathon Deliverables
August 23, 2026, 10:30am – 4:15 pm EDT
Final Presentations
August 23, 2026, 4:15 – 5:30pm EDT
Hackathon Judging
August 23, 2026, 5:30 - 6:30pm EDT
Closing Ceremony
* By registering for the Hackathon, you agree to allow your information to be shared with other registrants and volunteer leaders for the purpose of communicating event information and intra team communication.
Award Information
Exciting prizes await! For each problem category, the top three teams will be awarded prizes. Prize amounts will be announced soon!
Note: Teams will be judged within their respective problem topic areas, and awards will be selected separately for each category.
In addition to prizes, participants can apply for the ASME 2026 CIE/IDETC Hackathon - Travel Award & Fee Reimbursement Application Form. The travel award ($150) is for in-person/on-site participants, and the fee waiver ($50) is for virtual participants. Applications are considered after registration and are conditioned upon completing the event.
Eligibility
Undergraduate students, graduate students, postdocs, and non-students (e.g. professionals) are welcome to attend the Hackathon and experience the exciting competitions.
Hackathon Team and Presentation
- All participants must be registered by August 11, 2026 11:59 pm EDT. Everyone will be placed in a team up of 1-3 members. You may form a team based on your own preference. All implementations must be based on the original work.
- Each Hackathon team will continue their own meetings via their own chosen platform between 08/13/26 and 08/23/26.
- Each team needs to present their teamwork including the technical approach and submit the results to their own GitHub repository by the submission deadline.
- Team final presentation, results, and technical approaches will be evaluated based on a technical committee (separated with the Hackathon organizing committee).
Problem Statements
The full statement can be accessed by clicking on the links under the statement.
Preparing CNC machining programs from CAD designs involves interpreting geometry, manufacturing intent, and evolving part states into precise execution instructions. The CAM planning process is highly expertise-driven and experiential. This challenge focuses on creating an intelligent workflow that can automatically reason about machining decisions such as operation order, tool selection, cutting parameters, and toolpath generation. Participants are tasked with modeling how material removal changes part geometry at each step and using that understanding to drive downstream decisions. The key technical challenge is maintaining accuracy and manufacturability while minimizing manual intervention and iterative rework. Successful solutions will demonstrate how advanced algorithms or AI can enable reliable, scalable, and production‑ready CAM automation.
Siemens Problem Link
Modern engineering is plagued by the "lock-in trap," where teams are forced to commit to suboptimal designs early in the process due to the prohibitive cost of updating high-fidelity models. This project addresses that bottleneck by leveraging AI-driven surrogate physics and implicit modeling to shift the paradigm from manual iteration to a code-first inverse design approach. Participants must develop a robust, multi-disciplinary workflow that automatically maps mission requirements back to an optimized blended wing body aircraft, requiring a simultaneous solution for both structural integrity and aerodynamic performance. The challenge lies in executing a high-efficiency inverse search that minimizes mass and satisfies wing tip deflection and stress constraints, while ensuring the resulting geometry inherently achieves the target aerodynamic goals for the specified mission.
Link coming soon
Autodesk is challenging hackathon teams to push AI into real-world 3D design editing. While most CAD AI research focuses on generating models from scratch, engineers spend far more time refining, fixing, and updating existing designs: a harder, more practical problem that remains largely unsolved. This challenge is grounded in neuralCAD-Edit, a benchmark of expert-collected multimodal editing tasks that shows today's best foundation models still lag far behind human CAD experts. The task is to build harnesses around powerful foundation models (e.g. GPT, Gemini, Claude) to allow them to edit 3D CAD models. This may involve combinations of tool use, visual inspection, feedback loops and multiple agents to create a system that can truly assist real-world engineering workflows.
Autodesk Problem Link
Hackathon Organizers
Prof. Yinshuang Xiao (Colorado State University), yinshuang.xiao@colostate.edu
Prof. Yaoyao Fiona Zhao (McGill University), yaoyao.zhao@mcgill.ca
Prof. Zhenghui Sha (University of Texas – Austin), zsha@austin.utxas.edu
Prof. Hyunwoong Ko (Arizona State University), hyunwoong.ko@asu.edu
Dr. Zhuo Yang (Georgetown University, National Institute of Standards and Technologies), zy253@georgetown.edu
Dr. Laxmi Poudel (General Electric), Laxmi.Poudel@ge.com
Dr. Yan Lu (National Institute of Standards and Technologies), yan.lu@nist.gov
Jiarui Xie (McGill University), jiarui.xie@mail.mcgill.ca