MS&E Senior Projects
As a culmination of the major, MS&E's senior project course offers students a hands-on experience.
Student teams start by selecting and defining a problem with a sponsor organization. They then design, test, analyze, and provide recommendations to the sponsor using their cumulative MS&E education. Finally, students present their engineered solutions for these in-depth, real-world problems.
Senior projects often open a variety of doors for students, including continued research engagements and employment opportunities with sponsor organizations.
But don't just take our word for it—four years after completing their senior project, a team of first-place project winners shared how they've used the skills they learned and mindsets they developed during the senior project as they've navigated the first few years of their careers (video is for Stanford affiliates only).
Hear from the Pie Ranch team—Alex Hellman, Sami Koire and Kate Salmon, with additions from teammate Maddie Kerr—below:
Explore senior projects from 2026 below on this page, and find earlier projects using these links:
2026 senior projects: Adaptation in a changing landscape
As winter quarter drew to a close, MS&E undergraduates gave presentations detailing the research they performed as part of their senior capstone projects. Using a variety of MS&E techniques across a wide array of industries, student teams helped sponsor organizations adapt to a rapidly changing world.
Students drew on their course work, utilizing both quantitative and qualitative techniques to inform their work on the projects. In teams of three to four, they acted as consultants to their sponsor organizations, tackling real-world problems during a 10 week quarter.
Many of this year's projects made use of AI-powered tools, and some even built custom AI agents as deliverables. Sponsor organizations ranged from manufacturers like Gallant Sports and House of Livara, to investment firms like New Enterprise Associates and non-profits like Nest that serve to impact the community at large. While the students wrapped their findings into a final presentation at the end of spring quarter, their work will continue to be utilized by their sponsors long into the future.
Teams met regularly with their faculty mentors throughout the quarter to refine their work and fine-tune their final presentations. This year's faculty mentors included professors Riitta Katila, Irene Lo, Elisabeth Paté-Cornell, Markus Pelger, Alicia Sheares, and James Sweeney.
Note: Videos are included for teams whose sponsor organizations gave permission to share the final presentations. Each project also has a written summary.
A decision framework for AI in medtech
As Ajax Health prepared to deploy its newly raised investment fund, the team was tasked with helping the firm determine how to approach artificial intelligence-oriented investment opportunities in the medical device industry.
Ajax Health team ▶️
US market entry strategy
The team set out to develop a data-driven US market entry strategy for their sponsor organization, a textile manufacturer with decades of experience abroad.
Anonymous sponsor team
Breedj go-to-market and expansion strategy
The team was tasked with answering two core questions: Where should Breedj open new offices, and what go-to-market strategy can support growth toward its financial targets?
Breedj team ▶️
Task legitimacy bias and student time health
The team helped Doodle determine which research directions to pursue in the areas of time health and task legitimacy as part of its new Doodle Time Institute.
Doodle Time Institute team ▶️
Fun Loving Company: A go-to-market strategy
The team helped build a go-to-market strategy and establish a phased growth roadmap with clear milestones and success metrics for Fun Loving Company as it develops a novel product in the beverage industry.
Fun Loving Company team ▶️
Operational optimization for Gallant Sports
As Gallant Sports prepares to grow its sports venue construction business, the team identified operational bottlenecks across its project lifecycle, and based on these findings, developed both short-term operational improvements and long-term strategic investments to support scalable growth.
Gallant Sports team
From pilot to scaled cosmetics manufacturing facility
The team addressed three main goals. First, they identified operational bottlenecks that limit Livara's capacity to manufacture skincare and cosmetic products. Second, they developed a model to evaluate how changes in labor, equipment capacity, and automation affect output and revenue. Third, they researched aspects of selecting and building a new factory location.
House of Livara team ▶️
IBM sponsors three senior project teams
Three teams took on projects related to different areas of IBM's business, including supply chain modeling, competitive analysis, and developing marketing recommendations.
IBM teams
AI agents for venture capital workflows
The team built AI-powered tools to help investors at New Enterprise Associates spend less time on repetitive research tasks and more time on the parts of their job that require judgment.
New Enterprise Associates team ▶️
Investment strategy and portfolio construction for Nest
The team helped Nest build an investment strategy and recommend specific investment vehicles and portfolio allocations for its operating and strategic funds.
Nest team
PINTAR's employer intelligence system
The team built an AI-driven employer intelligence tool that can identify, score, and rank US employers most likely to hire from PINTAR's Indonesian talent pipeline.
PINTAR team
Residential natural gas expansion in Tanzania
The team built a comprehensive financial model to analyze the economic viability of Rashal Energies' residential natural gas project and provided an estimate of the government subsidy required to kickstart the project without needing to take on additional debt.
Rashal Energies team ▶️
Market analysis and GTM strategy in the Voice AI agent industry
The team helped Sanas analyze whether it should enter the Voice AI agent market, and, after determining that it should, how best to position itself to compete in the field among established players.
Sanas team
Improving estimates of pediatric heart transplant compatibility
The team analyzed data from multiple sources, then used their findings to develop a framework that can support clinicians during donor-recipient compatibility evaluations.
SURF Stanford Medicine team
When should a market maker refuse a bet?
The team built a tool to help mitigate risk for traders in prediction markets, where market makers risk trading against participants with superior or faster information.
Tauroi Technologies team ▶️