Krishna Kumar
Principal Investigator, Artificial Intelligence and Predictive Analytics for Aerospace Systems (AIPAAS) Laboratory, Toronto Metropolitan University
Principal Investigator, Space Electronics Test and Integration (SETI) Laboratory, Toronto Metropolitan University
Principal Investigator, Space Systems Dynamics and Control (SSDC) Laboratory, Toronto Metropolitan University
Professor
Faculty of Engineering and Architectural Science
Department of Aerospace Engineering
Toronto, Ontario
kdkumar@torontomu.ca
Office:
(416) 979-5000 ext. 4908
Expert In
Artificial intelligence and machine learning
Big data analytics
Formation flying
Genetic algorithms and genetic programming
Internet-of-Things (IoT) for space / terrestrial
Micro- and macro-satellite technologies
Micro-electro-mechanical systems
Miniature wireless systems
Nano-technologies
Real-time predictive analytics
Solar power satellites
Spacecraft dynamics and control
Technology and intelligent systems
Theme: Transformative technology
Wireless sensor networks
Bio/Research
How can we prevent accidents before they happen? According to Krishna Kumar, through the Internet of Things and Big Data analytics.
Over the last seven years, Kumar and his graduate students have been focused on troubleshooting spacecraft attitude control, orbital maneuvering and formati...
Click to Expand >>
Over the last seven years, Kumar and his graduate students have been focused on troubleshooting spacecraft attitude control, orbital maneuvering and formati...
Click to Expand >>
Bio/Research
How can we prevent accidents before they happen? According to Krishna Kumar, through the Internet of Things and Big Data analytics.
Over the last seven years, Kumar and his graduate students have been focused on troubleshooting spacecraft attitude control, orbital maneuvering and formation flying, as well as miniature wireless systems.
While the majority of the work has applications exclusive to space, Kumar is also using the knowledge they’ve gained to develop solutions for problems here on earth—such as algorithms that allow companies like Bombardier and MHICA to create proactive maintenance schedules to make trains and engines failsafe. “With a minimum amount of data,” says Kumar, “my grad students and I can predict engine failure six months in advance.”
For Kumar, the collaborative nature of engineering research is the only way to efficiently problem solve. “Working alone might be fine in other professions, but not when you’re wrestling with some of the biggest challenges in industry and society.”
Click to Shrink <<
Over the last seven years, Kumar and his graduate students have been focused on troubleshooting spacecraft attitude control, orbital maneuvering and formation flying, as well as miniature wireless systems.
While the majority of the work has applications exclusive to space, Kumar is also using the knowledge they’ve gained to develop solutions for problems here on earth—such as algorithms that allow companies like Bombardier and MHICA to create proactive maintenance schedules to make trains and engines failsafe. “With a minimum amount of data,” says Kumar, “my grad students and I can predict engine failure six months in advance.”
For Kumar, the collaborative nature of engineering research is the only way to efficiently problem solve. “Working alone might be fine in other professions, but not when you’re wrestling with some of the biggest challenges in industry and society.”
Click to Shrink <<