An agricultural engineer by training, Jaskaran has a diverse academic and professional background, spanning three continents and multiple disciplines. He holds a Ph.D. from 不良研究所, a master鈥檚 degree from Auburn University (USA), and a bachelor鈥檚 degree from Punjab Agricultural University (India). He has also worked as a Sr. Data Scientist with the Government of Manitoba, applying his skills in machine learning and data analysis to various domains. His research interests include use of machine learning for climate change adaptation, hydrological simulation, biomass handling, wastewater reuse, and soil and water quality. He has published 23 peer-reviewed papers and participated in more than 40 presentations at international conferences. He is passionate about finding solutions to global challenges related to the environment, climate change, and food security.
Previous Work Experience
Sr. Data Scientist, Department of Consumer Protection and Government Services, Government of Manitoba, Canada (2022 鈥� 2023)
Postdoctoral Fellow, Water Resources Engineering, School of Engineering, University of Guelph, Ontario, Canada (2021 鈥� 2022)
Teaching Assistant for multiple courses, 不良研究所, Quebec, Canada (2015-2019)
Sr. Design Engineer, Research and Development, CLAAS India Pvt. Ltd., India (2009-2012)
Awards and Recognitions
Mitacs Globalink Research Award to conduct research on wastewater treatment in rural areas of Punjab, India (2018)
USDA-NIFA (United States Department of Agriculture - National Institute for Food and Agriculture) funded Student Travel Grant to present research in 2018 Global Water Security for Agriculture and Natural Resources Conference, Hyderabad, India (2018)
IC-IMPACTS (India-Canada Centre for Innovative Multidisciplinary Partnerships to Accelerate Community Transformation and Sustainability) HQP Network Engagement Workshop funding award (2018)
Graduate Excellence awards from the Department of Bioresource Engineering, 不良研究所 (2014-19)
Schulich Graduate Fellowship award (2014-15)
Graduate award from the United States Department of Energy (USDOE) and United States Department of Agriculture (USDA), Auburn University, USA (2012-14)
President - Alabama Delta Beta Chapter of Alpha Epsilon (ASABE: American Society of Agricultural and Biological Engineers Honor Society), Auburn University, USA (2013-14)
Research Interests
Use of machine learning to develop climate-resilient agricultural practices
Improving existing hydrological simulation models using machine learning techniques
Wastewater reuse in agriculture to promote food security
Developing sustainable technologies to prevent deterioration of soil and water quality
Mathematics (Agric&Envir Sci): Measures of central tendency and dispersion; binomial and Poisson distributions; normal, chi-square, Student's t and Fisher-Snedecor F distributions; estimation and hypothesis testing; simple linear regression and correlation; analysis of variance for simple experimental designs.
Offered by: Plant Science
Two 1.5-hour lectures and one 2-hour lab
Please note that credit will be given for only one introductory statistics course. Consult your academic advisor.
Bioresource Engineering: The communicative skills of surveying. The fundamentals of surveying through the application of reasoning, tools, techniques, and instruments. Practices in use of basic surveying equipment including steel tape, level, and theodolite. The use and operation of Total Stations. The procedures and methods for the measurement of distances, elevations, angles and positions. Basic surveying calculations, including traverse adjustments.
Bioresource Engineering: A disciplined general approach to the solution of engineering problems, and the implementation of these solutions using structured programming methods in a current computational environment.
Offered by: Bioresource Engineering
3 lectures and one 2-hour lab per week
Note that a B+ must be obtained in this course in order to be permitted to register in BREE 504
Bioresource Engineering: General circuit laws and DC circuits; electromagnetic circuits; inductance and
capacitance, natural and forced response of circuits; analysis of single phase and three phase networks; transformers, AC and DC motors/generators.
Offered by: Bioresource Engineering
Three lectures and one 2-hour lab or problems per week.
Physics (Agric & Envir Sci): Kinematics in one and two dimensions. Newton's laws of motion. Circular motion and orbits. Rotation of a rigid body. Momentum. Work and energy, power. Conservation principles. Simple harmonic motion. Waves and sound.
Offered by: Bioresource Engineering
Fall
Three 1-hour lectures, one 2-hour lab, one 1.5-hour tutorial per week
Physics (Agric & Envir Sci): Kinematics in one and two dimensions. Newton's laws of motion. Circular motion and orbits. Rotation of a rigid body. Momentum. Work and energy, power. Conservation principles. Simple harmonic motion. Waves and sound. Includes
calculus-based applications.
Offered by: Bioresource Engineering
Three 1-hour lectures, one 2-hour lab, and one 1-hour tutorial per week.
Bioresource Engineering: Applications of Geographic Information Systems (GIS) and spatial analysis techniques to the presentation and analysis of ecological information, including sources and capture of spatial data; characterizing, transforming, displaying spatial data; and spatial analysis to solve resource management problems.
Offered by: Bioresource Engineering
Prerequisite(s): At least one environmental science course and one ecology course or permission of instructor
Bioresource Engineering: Philosophical and mathematical principles of computational modelling and simulation: Concepts of verification, parameterization, validation, and sensitivity analysis. Introduction to basic concepts of finite element modelling: Direct stiffness and weighted residual methods. Introduction to software packages for general systems and multiphysics, finite-element-based modeling. Emphasis on biosystems engineering applications, e.g., ecosystem dynamics, material properties, solid and structural mechanics, heat transfer, fluid dynamics, electrical and machinery systems.
Bioinformatics: Bioinformatics methods and reasoning in relation to genomics, proteomics and metabolomics strategies with an emphasis on functional genomics data. The course will cover introduction to UNIX, Perl programming, data processing and integration, file parsing, relational database design and implementation, angled towards solutions relevant for genomics.
Offered by: Plant Science
Prerequisite: Understanding of cell and molecular biology (equivalent to a cell or molecular biology course) or permission from instructor.
