Dr. Joseph Thekinen, PhD

Joseph Mugshot

Assistant Professor

Schulich School of Engineering, Department of Mechanical and Manufacturing Engineering

Web presence

Phone number

Office: 403.220.4083

Location

Office: MEB404

email

I'm looking for...

Research partners

I am looking for self-motivated MSc and Ph.D. students to start at the earliest. A background in machine learning and inclination towards mathematics and programming is an asset, but not expected.

Background

Educational Background

PhD Mechanical Engineering, Purdue University, 2018

Master of Technology Indian Institute of Technology Kharagpur, 2014

Bachelor of Technology Indian Institute of Technology Kharagpur, 2014

Biography

Dr. Joseph Thekinen is an Assistant Professor in the Department of Mechanical and Manufacturing Engineering at the University of Calgary. He received his Ph.D. from the School of Mechanical Engineering at Purdue University. He did his B.Tech and M.Tech from Indian Institute of Technology Kharagpur, with honors such as university silver medal (for topping academics in his department), best Masters thesis award, ABS scholarship, and J.P. Ghose Memorial award. His research focuses on enhancing human-AI partnership in decentralized sociotechnical systems using algorithmic game theory, machine learning, network science, and experimental techniques.

Research

Areas of Research

Human-robot teams, decentralized design, cloud manufacturing

Courses

Course number Course title Semester
ENME 473 Fundamentals of Kinematics and Dynamics Of Machines Winter 2022

Projects

Creating Intelligent Design Assistants for Decentralized Design

The project objective is to transform the engineering design process using intelligent computational assistants that augment designer performance, foster collaboration in multidisciplinary design, and mitigate bias. Multidisciplinary design is challenging due to knowledge gaps between domain experts and conflicting objectives between disciplines. There could be hundreds of such subsystem disciplines, often coupled by the physics of the problem, depending on design complexity and organizational structure. My approach consists of building and designing new approaches using data from human subject experiments. I will use a web-based design studio that mimics a decentralized multidisciplinary design process as a research platform to collect human subject data on information exchange and design processes in decentralized design. The design assistant in the studio will work in a tight feedback loop in which the collected data will drive the development of successful AI-bolstered design assistants. The design assistants will also emphasize fine-tuning to the styles of individual designers, such as personality, expertise, and cognitive abilities.


Designing Effective Cobots for Smart Factories

An emerging theme in Industry 4.0 is human and collaborative robots (cobots) coworking. The next-generation AI-robotics technologies will work alongside humans instead of merely automating repetitive tasks. The project objective is to facilitate a paradigmatic shift where robots are not just teammates but strategic entities that improve team productivity and augment the behavior of their human counterparts. This project will answer questions such as how much decision-making autonomy should be allowed for a cobot to form an effective hybrid human-robot team? What are the features of robots that augment the performance of human teammates? What are the renewed roles and responsibilities of robots and humans? Are cooperative or collaborative robots more effective? The focus will be manufacturing systems with a high potential to benefit from cobots to maximize productivity, machine utilization, workforce potential, and safety. Some of the problems of interest are optimal robot-human pairings, smart scheduling, and dynamic resource allocation. 

Publications