Munzir Zafar, Ph.d

Faculty Director (Academics) Graduate School Curation Program and Assistant Professor, Electrical and Computer Engineering
Dhanani School of Science and Engineering

Education

  • Ph.D. in Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta
  • M.S. in Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta
  • B.E. in Electronics, National University of Science & Technology, Karachi, Pakistan

Courses

  • Controls: Optimal Control, Adaptive Control, Nonlinear Systems, Linear Systems and Control
  • Robotics: Statistical Techniques in Robotics, Robotic Intelligence and Planning, Autonomous Control of Robotic Systems
  • Mechanical: Dynamics of Mechanical Systems, Robotics, Computer-Aided Design
  • Others: Convex Optimization, Computer Vision, Embedded Systems, Electrical Machinery Analysis, Advanced Computer Architecture

Teaching Experience

  • Instructor at Georgia Institute of Technology, 2016 to 2017.

Biography

Munzir Zafar is a highly accomplished Ph.D. graduate in Electrical & Computer Engineering, with a specialization in Robotics. His extensive educational background, rich research experience, and significant contributions to the field of robotics make him a sought-after professional in the industry. Throughout his career, Munzir has showcased exceptional skills in controls, robotics, mechanical dynamics, and software development. His research focuses on the whole-body control of wheeled inverted pendulum humanoids, and he has made significant strides in dynamic modeling, novel control algorithms, and simulation-based verification. Munzir is also adept in C/C++, Linux/Unix, MATLAB, SolidWorks, and electrical circuits design.

Publications

  • “Extending Riemmanian Motion Policies to Underactuated Systems” – ICRA 2020
  • “Barrier Functions in Cascaded Controller: Safe Quadrotor Control” – ACC 2020
  • “Hierarchical Optimization for Whole-Body Control of Wheeled Inverted Pendulum Humanoids” – ICRA 2019
  • “Semi-parametric Approaches to Learning in Model-Based Hierarchical Control of Complex Systems” – ISER 2018
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