SySTEM 2026

Challenge 1: Pneumatic Systems Analytics (Deterministic Pipeline)

Teams must design a data pipeline (ETL) for pneumatic systems that synchronizes data sources, imputes missing values, and filters statistical noise, computing system health metrics through pure mathematical logic without the use of Machine Learning.

Challenge 2: Pneumatic Systems Analytics (Prescriptive Inference)

Development of a Machine Learning model that analyzes the system state vector to identify degradation signatures and predict imminent failures using supervised and unsupervised learning.

Challenge 3: Automated Optical Inspection

Development of a computer vision system to detect manufacturing defects on PCBs (missing components, misplaced parts, defective soldering). Requires standardizing image capture, building a labeled dataset, and developing the detection algorithm.

Pre-registration

• Teams of 3 to 5 members, preferably interdisciplinary and optionally inter-institutional. Individual applicants will be helped to form a team.
• Pre-registration will open on the official Sapiex platform with the launch of the call.

Training & project proposal

• All pre-registered teams are invited to a free workshop covering technology project management methodology in detail.
• Training equips participants with foundational competencies needed to kick off the project.
• Each team must have at least one advisor as a guide throughout the contest. Teams are strongly encouraged to personally seek an academic, researcher, or domain expert advisor for tailored guidance (registered with the organizers for formal recognition).
• Teams submit a preliminary project proposal using the official template, endorsed by their advisor, to receive their training certificate.
• Proposals approved by the evaluation committee advance to Stage 3.

Project development

• Problem definition: clearly identify and articulate the real need or challenge addressed by the project, justifying its relevance and intended beneficiaries.
• Solution proposal: formulate the technical solution tailored to the selected challenge.
• Conceptual design & benchmark parameters: present the general solution architecture, main components, information flow, and simulated / validation results, along with industry standard benchmarks used for evaluation.
• AI / algorithmic integration proposal: explain and demonstrate how AI or computational algorithms were integrated to optimize the solution and deliver measurable added value, comparing parameters before and after optimization.
• Final project submission to the Organizing Committee for jury evaluation.

Project evaluation

• Projects are evaluated by a jury of academic experts and industry leaders against the evaluation criteria.
• Teams receive constructive feedback to foster professional growth.

Final presentation

• The top 5 teams evaluated in Stage 4 present and defend their project before the jury.
• 3 minutes for oral presentation, followed by a 4-minute Q&A session.

Awards

• Financial awards / cash prizes for the top 3 places.
• Formal recognitions awarded to all members of winning teams, including advisors.