Join the SPARC Lab

We’re recruiting talented, passionate, and driven PhD students to join the lab! We are seeking to review and admit students in the 2025-2026 application cycle, for a Fall 2026 start date. If you have a strong background in robotics, machine learning, and/or control theory and a passion for learning, please apply to the Tufts Mechanical Engineering PhD program and mention my name in your application.

For more information about the position, please see our informational flyer below. I’m looking forward to meeting you!

We’re looking for motivated undergrad and masters students to join the lab! Research in this lab is heavily grounded in control theory and mathematical optimization. While not strictly required, prior coursework or familiarity with the following subjects is highly useful.

A Note for Prospective Students: If you haven’t taken ME 31, ME 130, and/or ME134 yet, I strongly encourage you to look through Control Systems Engineering, Feedback Systems, and Probabilistic Robotics. They are an excellent representation of the theoretical nature of the SPARC lab’s research.

Core Subjects and Recommended Reading

• Control Theory (ME30, 31, 130)
  • Control Systems Engineering by Norman Nise | (link)
  • Feedback Systems: An Introduction for Scientists and Engineers by Åström & Murray | (link)
• Dynamics (ME21, 121)
• Robotics (ME35, ME134, CS138)
  • Probabilistic Robotics by Thrun, Burgard, and Fox | (link)
  • Underactuated Robotics by Tedrake | (link)
  • Reinforcement Learning: An Introduction by Sutton and Barto | (link)
• Math & Applied Math:
  • CS168: Convex Optimization
    • Convex Optimization by Boyd and Vandenberghe | (link)
  • MATH70: Linear Algebra
  • ES55: Numerical Methods
  • ES56: Probability and Statistics
  • MATH51: Differential Equations
  • MATH135 & 136: Real Analysis
    • Understanding Analysis by Stephen Abbott | (link)
• Machine Learning (CS135)

Please see the flyer below for application information and ways to get involved with the lab.