A collaborative place for researchers, students, industry, and community.

Machine Learning Studies: Researchers

Randal Peters, Instructor, Applied Computer Education (ACE)

Projects: Natural Language Processing for Intent

Randal instructs upcoming generations of ICT specialists using first-hand experience from academic and entrepreneurial ventures. His interests include continuous learning of leading-edge trends in technology and developing new ways to apply them for the benefit of corporate and non-profit organizations.

Randal specializes in: data management and analytics; machine learning; system architectures and frameworks; object-oriented analysis and design; classroom instruction, and entrepreneurial advisement.

Haider Al-Saidi, Chair, Applied Computer Education (ACE)

Projects: Machine Learning Interpretation of Electroencephalographic Data; Ultrahaptics; Facial Recognition; Wheelchair Training Simulator; Natural Language Processing for Smart Desk

Haider chair’s the Applied Computer Education department at Red River College and is a senior member of the Institute of Electrical and Electronic Engineers (IEEE) which he joined in 1991. He currently serves the position Chair of the Business Technology Management Accreditation Council. In 2009 he was elected to chair the Winnipeg IEEE section. From 1993 until 2000, Haider led the development team of ICUCOM Corporation in Troy, NY, which then acquired by Applied Wave Research in El Segundo, CA where he worked there until 2002. Haider joined the Assiniboine Community College and developed with other team members the Wireless Communication Engineering Technology program in 2002. The same year he started Tiacomm, an IT startup company. Haider’s current interest is in the areas of adaptive systems, and machine learning. He started working in this field since he was at ICUCOM Corporation when he developed algorithms to solve the multipath phenomenon using decision feedback equalization.

Jon Ziprick, Instructor, Applied Computer Education (ACE)

Projects: Plant Phenotyping; Peer-to-Peer Learning; Deep Neural Networks

Jon is a faculty member in the ACE (Applied Computer Education) Department at Red River College. He has a PhD in Physics from the Perimeter Institute for Theoretical Physics / University of Waterloo, and more than 10 years experience doing research across both academia and industry, in the varied fields of computer science, mechanical engineering, physics and mathematics. Jon has supervised both undergraduate and graduate students in research projects leading to publications in high impact journals. Jon’s current interests are in machine learning, digital agriculture and quantum computing.