Author Archives: Ajitesh Parihar

Student Research Project Presentations

Student Research Project Presentations

Time & Date: 9:30 am – 2:00 pm, Thursday, May 7, 2026
Location: Room C-130 and via Zoom (see email and registration information), Computer Science Department, Okanagan College
Registrations are open now:

Activity Diagram Analysis: https://events.vtools.ieee.org/m/558688
AlgoTrade & XGBoost: https://events.vtools.ieee.org/m/558962
Way-finding Mobile Application: https://events.vtools.ieee.org/m/558690
Line Diagram Analysis: https://events.vtools.ieee.org/m/558692

Join us for an exciting student research presentation!
Come support and learn from students as they share their work, there will be multiple presentations happening throughout the day.
Snacks and lunch will be provided, so bring your curiosity (and your appetite)!
We’d love to see you there!

Agenda:

09:30 am – 10:00 am | Coffee & Networking
10:00 am – 10:10 am | Opening Remarks
10:10 am – 10:40 am | Activity Diagrams Analysis for Visually Impaired Students: Dolcy
10:40 am – 10:45 am | Activity Diagrams Analysis for Visually Impaired Students Q&A: Dolcy
10:45 am – 11:00 am | Snacks & Refreshments
11:00 am – 11:25 am | “Way-finding Mobile Application for Navigation”: Kristina and Dolcy
11:25 am – 11:35 am | “Way-finding Mobile Application for Navigation” Q&A: Kristina and Dolcy
11:35 am – 12:00 pm | Snacks & Refreshments (Lunch)
12:00 pm – 12:30 pm | AlgoTrade & XGBoost: Harsh
12:30 pm – 12:45 pm | AlgoTrade & XGBoost Q&A: Harsh
12:45 pm – 01:00 pm | Snacks & Refreshments
01:00 pm – 01:25 pm | Line Diagram Analysis for Visually Impaired Student: Ajitesh
01:25 pm – 01:40 pm | Line Diagram Analysis for Visually Impaired Student Q&A: Ajitesh
01:40 pm – 02:00 pm | Snacks & Refreshments: Round Table & Open Discussions

Speakers’ Bio:

Dolcy Sareen is a fourth-year Computer Science student at Okanagan College. Dolcy is also the webmaster of the Okanagan College IEEE Student Branch. She is passionate about learning new technologies, with a strong focus on data. Dolcy enjoys connecting with people and continuously learning from new experiences.

 

Kristina Cormier is a fourth-year Computer Science student at Okanagan College. She has always been curious about science and technology. Recently, she has discovered a passion for data analysis and machine learning algorithms. Kristina is the Chair of the Okanagan College IEEE Student Branch. She coordinates with her team to help organize events and volunteering. Kristina truly enjoys mentoring, meeting new people and discovering new opportunities.

 

Harsh Saw is a fourth-year Computer Science student with hands-on experience spanning software engineering and AI/ML — from writing production code to deploying real-world systems. He has worked across multiple domains in industry, building technology that goes beyond the classroom. Passionate about turning ideas into working products, Harsh enjoys the full journey from early development to live deployment. He is driven by curiosity about what technology can do when it is built to actually work in the real world.

Ajitesh Parihar is a fourth-year Computer Science student and a Research Assistant at Okanagan College. He is a tech enthusiast who enjoys learning about innovations and technologies and is passionate about software engineering, cybersecurity, and algorithms. He enjoys meeting and working with people with diverse backgrounds.

 

 

Line Diagram Analysis for Visually Impaired Students – Student Presentation

Line Diagram Analysis for Visually Impaired Students

Time & Date: 01:00pm – 02:00pm , Thursday, May 7, 2026
Location: Room C-130 and via Zoom (see email and registration information), Computer Science Department, Okanagan College
Registration is open now: https://events.vtools.ieee.org/m/558692

Join us for an exciting student research presentation!
Come support and learn from students as they share their work, there will be multiple presentations happening throughout the day.
Snacks and lunch will be provided, so bring your curiosity (and your appetite)!
We’d love to see you there!

Agenda:

1:00 pm – 1:25 pm | Line Diagram Analysis for Visually Impaired Students: Ajitesh
1:25 pm – 1:40 pm | Line Diagram Analysis for Visually Impaired Students Q&A: Ajitesh
1:40 pm – 2:00 pm | Snacks & Refreshments: Round Table & Open Discussions

Abstract:

Line diagrams and mathematical function plots are commonly used in scientific and educational textbooks and articles to convey quantitative relationships. However, their visual nature presents significant challenges and barriers for visually impaired learners. Despite the ongoing efforts to improve accessibility in higher education, the non-text content still remains difficult to interpret non-visually. The existing diagram analysis approaches often focus on chart type classification, require manual user intervention for tasks such as label mapping, or fail to provide accessible end-to-end interaction for non visual analysis. Also, many of these systems do not explicitly consider the requirements of visually impaired users, resulting in workflows and interfaces that are not accessible. We propose an accessibility aware framework for automated analysis of line diagrams from raster images. The proposed end-to-end system performs CNN based curve segmentation, diagram type classification, label and tick extraction using optical character recognition, mapping of curve pixels to the diagram domain, and supports interactive querying along with a user interface compliant with the Web Content Accessibility Guidelines. Evaluation is conducted using a large synthetic dataset of 2D chart images representing a variety of mathematical functions and discrete point line charts, which is used for both model training and system-level assessment.

Speaker’s Bio:

Ajitesh Parihar is a fourth-year Computer Science student and a Research Assistant at Okanagan College. He is a tech enthusiast who enjoys learning about innovations and technologies and is passionate about software engineering, cybersecurity, and algorithms. He enjoys meeting and working with people with diverse backgrounds.

 

 

For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org)
Refreshments will be provided

Algorithmic Trading: XGBoost Machine Learning Model – Student Presentation

Algorithmic Trading: XGBoost Machine Learning Model

Time & Date: 12:00pm – 01:00pm , Thursday, May 7, 2026
Location: Room C-130 and via Zoom (see email and registration information), Computer Science Department, Okanagan College
Registration is open now: https://events.vtools.ieee.org/m/558962

Join us for an exciting student research presentation!
Come support and learn from students as they share their work, there will be multiple presentations happening throughout the day.
Snacks and lunch will be provided, so bring your curiosity (and your appetite)!
We’d love to see you there!

Agenda:

12:00 pm – 12:30 pm | AlgoTrade & XGBoost: Harsh
12:30 pm – 12:45 pm | AlgoTrade & XGBoost Q&A: Harsh
12:45 pm – 1:00 pm | Snacks & Refreshments

Abstract:

Stock markets generate enormous amounts of data every day, yet predicting how a stock will move throughout a trading session remains a difficult problem. This paper presents MarketSight, a system that learns from years of historical market data to forecast how individual stock prices will evolve across an entire trading day — before that day begins. By identifying patterns in past price behavior, the system produces a predicted price path for each stock, giving traders an early picture of likely intraday movement. The system runs automatically each night, updating its predictions with the latest available data. Experiments across approximately 500 US-listed stocks demonstrate meaningful forecasting accuracy, with predictions consistently outperforming naive baselines.

Speaker’s Bio:

Harsh Saw is a fourth-year Computer Science student with hands-on experience spanning software engineering and AI/ML — from writing production code to deploying real-world systems. He has worked across multiple domains in industry, building technology that goes beyond the classroom. Passionate about turning ideas into working products, Harsh enjoys the full journey from early development to live deployment. He is driven by curiosity about what technology can do when it is built to actually work in the real world.

 

 

For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org)
Refreshments will be provided

Cross-Platform 2D and 3D Way-finding Mobile Application for Navigation in Industrial Buildings and Parking Lots – Student Presentation

Cross-Platform 2D and 3D Way-finding Mobile Application for Navigation in Industrial Buildings and Parking Lots

Time & Date: 11:00am – 12:00pm , Thursday, May 7, 2026
Location: Room C-130 and via Zoom (see email and registration information), Computer Science Department, Okanagan College
Registration is open now: https://events.vtools.ieee.org/m/558690

Join us for an exciting student research presentation!
Come support and learn from students as they share their work, there will be multiple presentations happening throughout the day.
Snacks and lunch will be provided, so bring your curiosity (and your appetite)!
We’d love to see you there!

Agenda:

11:00 am – 11:25 am | “Way-finding Mobile Application for Navigation”: Kristina and Dolcy
11:25 am – 11:35 am | “Way-finding Mobile Application for Navigation” Q&A: Kristina and Dolcy
11:35 am – 12:00 pm | Snacks & Refreshments (Lunch)

Abstract:

Finding your way inside large buildings—like campuses, malls, or airports—can be difficult, especially when you’re short on time or in an unfamiliar place. Many existing solutions are expensive or rely on constant internet access. This project presents a mobile app that works both online and offline to help users navigate indoor and outdoor spaces. It uses interactive maps, QR codes for positioning, and a shortest-path algorithm to guide users efficiently. The system is designed to be affordable, easy to maintain, and scalable for different environments.

Speaker’s Bio:

Kristina Cormier is a fourth-year Computer Science student at Okanagan College. She has always been curious about science and technology. Recently, she has discovered a passion for data analysis and machine learning algorithms. Kristina is the Chair of the Okanagan College IEEE Student Branch. She coordinates with her team to help organize events and volunteering. Kristina truly enjoys mentoring, meeting new people and discovering new opportunities.

 

 

For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org)
Refreshments will be provided

Activity Diagrams Analysis for Visually Impaired Students – Student Presentation

Activity Diagrams Analysis for Visually Impaired Students

Time & Date: 9:30am – 11:00am , Thursday, May 7, 2026
Location: Room C-130 and via Zoom (see email and registration information), Computer Science Department, Okanagan College
Registration is open now: VTools Link

Join us for an exciting student research presentation!
Come support and learn from students as they share their work, there will be multiple presentations happening throughout the day.
Snacks and lunch will be provided, so bring your curiosity (and your appetite)!
We’d love to see you there!

Agenda:

9:30 am – 10:00 am | Coffee & Networking
10:00 am – 10:10 am | Opening Remarks
10:10 am – 10:40 am | Activity Diagrams Analysis for Visually Impaired Students: Dolcy
10:40 am – 10:45 am | Activity Diagrams Analysis for Visually Impaired Students Q&A: Dolcy
10:45 am – 11:00 am | Snacks & Refreshments

Abstract:

Diagrams are a very important part of education,learning and understanding , allowing the transmission of complex ideas in a visual format. However, current accessibility technologies introduce substantial limitations for visually impaired students in accessing these materials. Traditional approaches to fix this problem, such as audio descriptions and tactile graphics, either lack detail or are prohibitively expensive to scale. This review will focus on the current  status of accessible diagram technologies, such as tactile graphics, 3D printing, AI-driven recognition applications and methods proposed till now . We identify the major technical challenges and propose an integrated approach using multi-modal interaction by combining audio, and AI-enhanced diagram interpretation. The approach offers equal access to STEM visual content as part of the road to inclusive education.

Speaker’s Bio:

Dolcy Sareen is a fourth-year Computer Science student at Okanagan College. Dolcy is also the webmaster of the Okanagan College IEEE Student Branch. She is passionate about learning new technologies, with a strong focus on data. Dolcy enjoys connecting with people and continuously learning from new experiences.

 

For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org)
Refreshments will be provided

Data Collection and Staging Process Automation for Machine Learning in Algorithmic Trading – Students Presentation

Data Collection and Staging Process Automation Precision, Speed and Scalability for Machine Learning Modelling of Algorithmic Trading Stocks-Price Prediction

Time & Date: 9:00am – 11:00am , Wednesday, April 22, 2026
Location: Room E-301 and via Zoom (see email and registration information), Computer Science Department, Okanagan College
Registration is open now: https://events.vtools.ieee.org/m/555692

This project brings together three teams: Data Collection, Data Warehousing, and Machine Learning into a unified, end-to-end system for high-frequency stock price prediction.
Learn how we designed a scalable pipeline using distributed computing and XGBoost, covering system architecture, data engineering, and real-world ML applications in algorithmic trading.
This work also establishes a foundation for ongoing research and extended large-scale evaluation.
Open to students, faculty, and anyone interested in machine learning, data systems, or fintech.

Abstract:

This presentation discusses an automated data collection and staging pipeline for high-frequency stock price prediction using machine learning. The system integrates scalable ELT processes, data deduplication, and distributed training with XGBoost on high-performance computing infrastructure. Designed for precision, speed, and scalability, the framework enables efficient handling of large financial time-series datasets while maintaining robust predictive performance and optimized resource utilization.

Contributors:

This project was developed through a collaborative effort across three specialized teams:

Data Collection Team

Responsible for sourcing, aggregating, and preprocessing raw financial and market data.

  • Andrew Johnson
  • Emilio Iturbide
  • Reilly Mager
  • Lian Heckrodt
  • Cade Dempsey
  • Kristina Cormier

Data Warehouse Team

Designed and implemented the data storage architecture, ETL/ELT pipelines, and database systems.

  • Alex Anthony
  • Hayden Nikkel
  • Daemon Lewis
  • John Cortez
  • Jackson Rosco

Machine Learning Team (XGBoost)

Developed, trained, and evaluated machine learning models for predictive analytics and trading strategies.

  • Harsh Saw
  • Zane Tessmer
  • Kavaljeet Singh
  • Dante Bertolutti
  • Guntash Brar
  • Parag Jindal

Acknowledgements

We thank all contributors and collaborators who supported the development, testing, and deployment of this system.

Photographs

 

For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org)
Refreshments will be provided

Data Warehouse for Trading Stocks Algorithmatically – Student Presentation

Data Warehouse for Algorithmic Trading Stocks-Price Forecasting on Digital Research Infrastructure using Machine Learning Modelling

Time & Date: 9:00am – 10:00am , Wednesday, April 21, 2026
Location: Room HS107 and via Zoom (see email and registration information), Computer Science Department, Okanagan College
Registration is open now: https://events.vtools.ieee.org/m/555684

Join this presentation to explore how a Data Warehouse system is built to manage and process large-scale stock market data. The project demonstrates how raw financial data is transformed into structured formats that can be efficiently queried and used for predictive modelling.

You’ll learn:

  • How Data Warehouses store and organize large datasets
  • Star schema design in a real system
  • How data pipelines automate transformation of financial data
  • How machine learning models use prepared datasets for predictions
  • How large datasets are processed efficiently

Abstract:
This presentation explains how large volumes of stock market data are organized and processed using a structured database system. The system takes raw financial data and converts it into a format that is easier to store, search, and analyze.

The data is processed through an automated pipeline that calculates key financial values such as price changes and trading volume summaries. The structured data is then stored in an optimized system that allows fast access and efficient analysis.

This approach helps make large financial datasets more usable and easier to work with.

Speakers Bio:
Emilio Iturbide Gonzalez is a graduating Computer Science student at Okanagan College with interests in data systems, software engineering, and artificial intelligence.
He has worked on building a Data Warehouse system designed to manage and process large volumes of stock market data. His work focuses on creating efficient data pipelines, organizing complex datasets, and supporting data-driven applications.
He is interested in building practical systems that connect software engineering, data processing, and real-world applications in technology.

Photographs:

For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org)
Refreshments will be provided

Women in Computer Science and Technology

Dr. Bowen Hui

Computer Science, UBC Okanagan

Women in Computer Science and Technology

Time & Date: Monday, May 5, 2025, 10:00 am – 12:00 pm
Location: HS-201 and Zoom, Okanagan College, 1000 KLO Rd., Kelowna, BC, V1Y 4×8.
Registration: https://events.vtools.ieee.org/m/473418

Abstract:

Join us for an inspiring and exciting presentation by Dr. Bowen Hui!

We’ll explore the powerful presence of women in the Computer Science and Technology fields and explore how the future generation of women can get involved.

Whether you’re already coding or just curious about the field, join us in breaking barriers, sparking innovation, and supporting each other in this incredible industry!

All are welcome – let’s make a tech space where everyone can thrive!

Bio:

A results-oriented Analytics Professional with over 10 years of well-rounded experience delivering custom solutions in statistical applications, user modelling, preference elicitation, text mining, probabilistic inference models, and behavioural decision making systems. My passion is to apply advanced analytics to solve real-world problems.

Accomplishments:  Initiated, implemented, and managed automation project saving the company $400K in 2010. Awarded 26 graduate scholarships totalling $264,930. Author of 15 original journal, conference, and book chapter articles; obtained 1 patent and 1 copyright. Communicates effectively with clients and technical developers, has experience working in multicultural teams, and has experience in user training.

My specialties include user modelling, Bayesian networks, behavioural decision-making, text mining, analytics, statistical modelling, experiment design, and data analysis.

For further information, please get in touch with Youry Khmelevsky (email: tok-section [at] ieee.org) and subscribe to the news at okanagan@listserv.ieee.org
Refreshments and Pizza will be provided

Testing Data Pipeline Limits for Stock Market Forecasting with Machine Learning Integration

Joshua Padron-Uy, Computer Science Department
Okanagan College, BC

Testing Data Pipeline Limits for Stock Market Forecasting with Machine Learning Integration

Time & Date: Wed. Apr. 23, 2025, 6:30 pm – 7:15 pm
Location: HS-301 and Zoom, Okanagan College, 1000 KLO Rd., Kelowna, BC, V1Y 4×8.
Registration: https://events.vtools.ieee.org/m/482426

Abstract:

This research aims to investigate the performance of a data pipeline system implemented using an extract, transform, load (ETL) tool under increased data volume. The system utilizes a data warehouse (DW) to support an XGBoost machine learning model for forecasting closing stock prices. The data source comes from the Financial Modelling Prep (FMP) API, which provides large amounts of real-time and historical data from the stock market.

Bio:

Joshua Padron-Uy is a fourth-year Computer Science student working on a research project in the COSC 448 Research Methodologies. He is an aspiring student seeking to work in the tech industry. He is eager to learn about various areas, including software engineering, DevOps, data science, and most recently, data engineering.

For further information, please get in touch with Youry Khmelevsky (email: Youry at IEEE.org) and subscribe to the news at okanagan@listserv.ieee.org
Refreshments will be provided

IEEE Thompson Okanagan Section Elevation Celebration & Annual General Meeting

Join Us for the IEEE Thompson Okanagan Section Elevation Celebration & AGM

We are pleased to invite you to the Okanagan Subsection Elevation Celebration and the First Thompson Okanagan Section Annual General Meeting. This event marks an important milestone for our IEEE community, and we look forward to celebrating with you.

Date: Saturday, March 22, 2025
Time: 11:00 AM – 1:00 PM
Location: A146 – A Building (with S Building), Okanagan College

Register here: https://events.vtools.ieee.org/m/467550.

We are delighted to present the Digital Research Alliance of Canada: Digital Resource Infrastructure and Cybersecurity Workshop before the celebration, starting at 11 AM.
DRI Workshop Agenda:
11:00 am – 11:10 am | Opening Remarks (IEEE Section Chair, Dr. Youry Khmelevsky, and Okanagan Student Branch Chair Kristina Cormier)
11:10 am – 11:50 am | Introduction to DRI
11:50 am – 12:05 pm | Coffee Break
12:05 pm – 12:20 pm | Research Project Presentation (Kristina Cormier)
12:20 pm – 12:50 pm | Demonstration of DRI Services
12:50 pm – 1:00 pm | Discussion and Final Thoughts

Date: Saturday, March 22, 2025
Time: 1:00 PM – 5:00 PM
Location: S104 – S Building Theatre, Okanagan College

Section Celebration Agenda:
1:00 pm – 1:45 pm – Welcome Lunch, Celebration Opening (Section Chair, Dr. Youry Khmelevsky, and TOK Student Branches, Matthew Wilder, IEEE Area West Chair opening address)
1:45 pm – 2:15 pm – Intro & IEEE President Dr. Tom Murad Welcome
2:15 pm – 2:45 pm – Benefits of IEEE: Usman Munawar & Kristina Cormier
2:45 pm – 3:15 pm – Coffee & Social
3:15 pm – 4:00 pm – AGM
4:00 pm – 4:45 pm – Round Table, Celebration Closing

5:00 pm – 9:00 pm — 2025 Okanagan Innovation and Technology Expo at KF Aerospace Centre for Excellence

This is an excellent opportunity to connect with IEEE members, learn more about IEEE benefits, and participate in discussions about the section’s future.

Bios:

Dr. Tom Murad, The IEEE Canada President & Director IEEE – R7.

A member of the Engineering Order of Honour – Professional Engineers Ontario “PEO”, is a respected Technology leader, Innovator, thinker, Board Member, award-winning Educator, and distinguished speaker & advocate of innovation and creativity, specifically in the Areas of:

Engineering & Technology, Mechatronics, Digitalization, Smart Infrastructure, Industry – 4.0 & 5.0, Leadership, and technical education & Talents/skills development.

He Joined Siemens in Canada (2010 – 2023). His latest role was the “Country Lead (V.P.) of Engineering, Technical Excellence & Academics”, as well as being the founder & Director of the Awards winning “Siemens Canada Engineering and Technology Academy (SCETA)”, and the Siemens Mechatronics Systems Certification Program (2014 – 2020).

Prior to that, he held different Executive Management & C – Level roles with an extensive career in Professional Engineering, Innovative Technical Operations and including Academia and R&D work.

He is now Adjunct Professor at the College of Engineering & Physical Sciences – University of Guelph, “CTO” of Innoventus Engineering Inc., and a member of various Boards of Directors in Industry and Academia.

Dr. Murad holds a Bachelor of Engineering (Electrical & Electronics) and a Doctorate (Ph.D.) in Power Electronics and Industrial Controls from Loughborough University of Technology in the UK, with a Leadership Program Certificate from Schulich Business School, York University in Ontario, Canada.

Dr. Murad is:
IEEE Canada – President & Chair of the Board of Directors.
IEEE – Region 7 (CANADA) Director / Delegate (Global).
Board of Director – Ontario’s Government’s Post Secondary Education Quality Board “PEQAB”.
Board (Council) member – Engineering Institutes of Canada “EIC”.
Fellow of Engineers Canada “F.E.C”.
Fellow of Engineering Institutes of Canada “EIC”.
Awardee of IEEE Canada’s 2019 J.M. Ham Outstanding Engineering Educator Award.
Member of the PEO Licensing “Engineering Experience Review”- ERC Committee (since 2003).
Advisory Board Member – School of Mechatronic Systems Engineering at Simon Fraser University “SFU”.
Licensed Professional Engineer “P.Eng.” in Ontario (PEO & OSPE); Alberta (APEGA) & N.W.T. (NAPEG).
Chair – IEEE Toronto Section (2016-2017).
Ex-Vice Chair & Member of Board of Directors – Ontario Soc. Of Professional Engineers “OSPE”.
Ex-Member of Board of Directors – Canadian – German Centre for Innovation and Research.
Ex-Member – Board of Directors – Green Centre Canada.

Matthew Wilder’s Abstract:
Greetings from the Vancouver Section & welcome to the West Area of IEEE Canada
Presentation of Vancouver Section scholarship award

Matthew Wilder’s Bio:
Matthew Wilder is a Senior Engineer with TELUS Communications, a leading ISP and technology company headquartered in Vancouver, Canada. At TELUS, Matthew is responsible for IP Address Management and IPv6 strategy. Matthew serves the Institute of Electrical and Electronics Engineers (IEEE) as the West Area Chair of IEEE Canada. He also serves the Vancouver Section as Chair of the Conference Committee and has previously served as Chair of the Vancouver Section in 2022. Matthew also volunteers with the American Registry for Internet Numbers (ARIN) as the Advisory Council’s Vice Chair. He has written articles for IEEE Canadian Review and blogs for ARIN, ISOC, and other industry publications. Matthew holds a Bachelor of Applied Sciences from the University of British Columbia and a Master of Business Administration from the University of Victoria.

Usman Munawar’s Bio:

Mr. Usman Munawar is an accomplished IEEE Senior Member & HKN with over 12 years of experience bridging industry and academia. A seasoned electrical engineer and researcher, he has made significant contributions to the field, authoring 17 publications in esteemed journals, transactions, and conferences. His extensive expertise includes overseeing 125+ engineering design projects, addressing 25+ data science challenges, integrating 50+ industrial systems, and coding over 300 algorithms—from small-scale solutions to large, complex systems.

Mr. Munawar earned his M.A.Sc. in Electronic Systems Engineering from the University of Regina, Canada, where he was named to the Dean’s Honor List. He was also awarded the prestigious IEEE PES Outstanding Student Scholarship (2020). His academic journey includes completing Stanford University’s Technology Entrepreneurship program (2012), participating in Oxford and Cambridge’s Smart Village program (2017), and visiting the MIT Media Lab as an IEEE Delegate (2022).

Currently, Mr. Munawar serves as Project Manager at Powertech Labs Inc. (a subsidiary of BC Hydro), where he leads critical initiatives in Distributed Energy Resources (DERs) and founded the Future Energy Integration Lab. His expertise spans Smart Grid technologies, energy disaggregation, predictive maintenance, optimization, machine learning, deep learning, data mining, forecasting, and smart infrastructure solutions, with applications in Smart Cities and Smart Villages.

Previously, he worked as a Design and Development Engineer at Greenwave Innovations Inc. (2021–2023), where his contributions led to three international/national product awards. In 2017, he launched a successful renewable energy startup, completing 50 projects in just six months. Prior to 2019, he held academic roles, securing funding from major agencies such as USAID, UNESCO, and GIZ for impactful projects, including the deployment of solar-powered lighting in 133 sports facilities.

Kristina Cormier’s Bio:

Kristina Cormier is a fourth-year Computer Science student at Okanagan College. She has always been curious about science and technology. Recently, she has discovered a passion for data analysis and machine learning algorithms. Kristina is the Chair of the Okanagan College IEEE Student Branch. She coordinates with her team to help organize events and volunteering. Kristina truly enjoys mentoring, meeting new people and discovering new opportunities.

During AGM:

 

For further information, please get in touch with us
Youry Khmelevsky (email: tok-section [at] ieee.org) and
subscribe to the news at okanagan@listserv.ieee.org