Hi there! I am a Senior Researcher at Microsoft Research, New York City. My work combines the elegance of machine learning and control theory with the practical impact of autonomous systems – to the end of developing principled data-driven analysis and synthesis for real-world dynamical systems.

During my PhD and postdoc, I worked on developing modeling methods for continuum, compliant, and configurable (C3) soft robots for medical assitive systems in cancer radition therapy. Leveraging the theory of nonlinear elastic deformations and modern machine machine learning methods, I provided mechanisms and methods suitable for the modeling (fiber-reinforced) elastomeric actuators and adapted principles from optimal and adaptive control theory for their manipulation. Nowadays, I worry about scalable modeling and control algorithms for manipulating real-world (physical) and often complex systems. In noo order of particular importance, I am focused on a range of topics spanning safety-critical learning systems, interactive machine learning, and devising optimally robust learning schemes for the control of nonlinear dynamical systems.

Community Service

I am an active member of the AI, control, and robotics research communities — regularly engaging in peer reviewing activities for NeurIPS, International Federation of Automatic Control – World Congress and Automatica alike, Institute of Physics, ICML, IEEE Access, Conference on Decision and Control, IROS, American Control Conference, ASME’s DSCC, ICRA, and Neural Computing and Applications among others.

Since January 2020, I have been a judge for NatGeo’s AI for Species Discovery Grant Applications. In addition, I serve regularly as Associate Editor for IEEE Robotics’ flagship conference – International Conference on Robotics and Automation (ICRA).

[Old-ish] Teaching Keepsakes

I mostly teach a mixture of undergrad and graduate level classes in Robotics at Brandeis.

I have left Brandeis.

A Short Treatise on Robots’ Kinematics and Kinetics.

• Being a tutorial organized for my colleagues in the MSR NYC RL Group. June, 2022.

• [Course Resources]

  • Introduction and Kinematic Geometry
    • Mechanics and Mechanisms, Pairs and Linkages, Serial, Parallel and Hyperredundant Robots
  • Mobility of Kinematic Structures
    • Freedoms, Constraints, The General (Relative) Mobility Criterion.
  • Rigid Body Motions in R^3
    • Motions in R^3, Euler and Fick Angle Parameterizations; Axis/Angle Parameterizations, Composition of Rotations.
  • Rigid Body Motions with Screw Theory
    • Screws: Displacement, Twists, Wrench. Group Theory Brief Intro. Connections of Screws with Rotations. The Exponential Map.

RBOT250: The Mathematical Foundations of Robotics, Spring 2021.

• Course Resource

RBOT101: Robot Manipulation, Planning and Control, Spring 2020.

• Course Resource

EECS 4342: Introduction to Robotics, Fall 2016.

This was a course I helped teach back in grad school to a mixture of Seniors and first-year ECE Masters students.The website I made in 2016 is highlighted below.

• Introduction to Robotics - EECS 5375

• Lecture One

In the words of my students:

“Thank you again Lekan. [Taking RBOT 250 with you] was quite a journey. But I feel more confident now with ROS because I figured all of the ROS system. I’ll be looking forward to see you run the class again.”

“Dr. Molu is very caring about his students. I love how he makes time for me to run over course notes, point out helpful reading materials, and work through problems together with me. I enjoy the examples and exercises he tasks us with.”

“I want to thank Lekan for teaching this course, I definitely learned a lot. I am interested in auditing it when Lekan runs it again.”