May 2022 Issue

Social Media Updates!


We also want to hear from you! Come share your story with us !

Welcome Message from Editor and Team!

Welcome to Spring 2022!

We welcome you to May issue of IEEE Newsletter, Toronto section.

Enjoy reading (Smart Cane) capstone project Smart Navigation Guide for Visually Impaired People”

Meet Dr. Muhammad Jaseemuddin in our IEEE supporters  section. Enjoy his research achievements and appreciate his contributions to IEEE.

For the section upcoming events, please visit New Events page.

You can find newsletter’s previous issues here.  You can explore our Library to access links to various newsletters, resources and chapter activities.

By launching this newsletter, we intend to cover IEEE achievements and success stories specific to the Toronto area.

If you have any questions, suggestions, or concerns, please address them to the editor; Fatima Hussain at We hope to hear from you, and we welcome your feedback!

Get Involved with Us!

IEEE Toronto section is looking forward to hearing from you. your contributions are welcome to this monthly newsletter. We invite our members to share and submit:

  • Short Story (about IEEE members, WIE members)
  • News items and Affinity group reports
  • Technical Articles/Blogs (Brief discussions of cutting edge research, new technological tools, topics of your choice)


Articles should be submitted in Word format. Word count for News items, Affinity group reports is 50 to 200 words and for blogs/ articles is 500 to 800 words.

Happy New Year!

Warmest thoughts and best wishes for a Happy New Year! May this new year bring us lots of new and exciting opportunities in our lives, with peace, love, and prosperity. Let’s welcome the year-2022 hoping that the new year is safe and better than the previous, full of happiness and joy. We start this as a new chapter of our lives, lets do everything possible to make the upcoming year better, both personally and professionally. Although the last couple of years have been challenging for all of us, this is the best time to regroup ourselves, rearrange our hopes, goals, missions, and work even harder towards them.

Evolutionary Algorithms to Enhancing Business Intelligence

Salah Sharieh, Head, Transformation Office at RBC.

Adjunct Professor Ryerson University, Tech Titan 2019

Over the years, the amount of produced data has increased exponentially, leading to the development of robust infrastructure and massive databases able to cope with the demands for managing information. Data in isolation is meaningless; it requires to be analyzed in order to be transformed into valuable information.  This information is translated into useful knowledge and the process of transforming data into knowledge is called Knowledge Discovery (KDD) which uses Data Mining (DM) techniques. DM is the core of the KDD process and that it uses algorithms to explore and discover unknown patterns.

DM is defined as the process of extraction of useful information, patterns and trends from large quantities of data which could be found in sources such as databases, texts, images and data on the Web.  While KDD explores, analyses and models masses of data hosted in repositories, it identifies useful and novel patterns from complex data sets.

Learning is the process of extracting knowledge in most DM methods. A model learns from training data by a learning algorithm, which is evaluated using a test dataset. Due to a high degree of randomness or limitations in the algorithms, several iterations might be necessary before a satisfactory model is found. A model produces a classification/prediction function which foretells the values of future data. These methods are also known as Supervised Learning methods. The main steps within the KDD process are:

1. Business understanding: Define the goals to be achieved and understand the environment in which knowledge discovery will take place.

2. Data Pre-processing:

a. Identification and selection of a data set which will be used for learning during the data mining process

b. Data cleansing for ensuring the completeness and reliability of data

c. Data transformation for preparing better data to increase the accuracy of the results Statistical methods such as regression analysis, cluster analysis or decision trees can be used in this task.

3. Evaluation: Interpretation of knowledge patterns through a visualization tool. In this step, the results are compared and evaluated against the original goals that were set in the beginning of the process.

4. Deployment: Report the results of the data mining study and apply them as convenient.

The taxonomy of the DM paradigms provides an understanding of methods and their grouping. DM is divided in two types a) Verification-oriented which verifies a user’s hypothesis (traditional statistics); and b) Discovery-oriented where the system finds new rules and patterns autonomously. The latter method consists of two methods: Descriptive, focused on data interpretation, also known as unsupervised learning. The second method is Prediction, which aims to build a behavioral model able to predict values and develop patterns; this is also known as supervised learning.

Other DM techniques are Association, Prediction, Sequential Patterns, and Similar Time Sequences. In Association, the relationship of a particular item in data transactions is used to predict patterns through the use of association rules; the rules consist of a confidence factor and a support factor. In Classification, methods learn different functions from an item which are mapped into classes. The set of classes, the attributes and the learning set can predict the class of other unclassified data. Sequential pattern analysis aims to find similar patterns in data transactions over a business period. Lastly, Time sequences; discover sequences similar to a known sequence over a past and present business period.

EA and DM techniques are playing an important role in supporting Business Intelligence (BI) thus enabling knowledge extraction that can be tactically used to design business strategies, product development and market analysis. The objective of BI is to support better business decision making. For that purpose, it uses technology, applications and methods for the analysis of data. DM, not only “identifies nuggets of information that can result in profitability”  but also, can be expanded to retrieve more meaningful data based on behaviours rather than on statistical methods only.  However, it also comes with some limitations and disadvantages. In order for DM algorithms to be effective, it is necessary to have a competitive data set where the system can infer learning, despite the fact Web data mining is complex due to the massive  volume of information.

About Author

Dr. Salah Sharieh is a senior technical Innovator with extensive experience in business, technology, and digital transformation. Working at RBC, he led the delivery of the first Developer Portal in Canada, enabling API economy and allowing external Developers across industries to collaborate and innovate. As Technical Head with BMO, Salah’s technical and leadership skills managed his team to deliver several high-profile initiatives such as the first mobile account open in Canada, the first bio-metric touch ID solution, and the first integrated tablet solution for investment and everyday banking.

Salah is a Yeates School of Graduate Studies member at Ryerson University, where he supervised Ph.D. and Master’s students. One of his research areas is the new role of CIOs in the new Digital Economy. In addition, he taught several courses in areas like security, algorithms, and networks. Salah holds the degree of Doctor of Philosophy from McMaster University. He has more than forty-five peer-reviewed publications and has contributed to several books

Upcoming Events

International Conference on Soft Computing & Machine Intelligence (ISCMI) 2022 ( November 26-27)

The Conference will be held in Toronto, Canada during November 26-27, 2022. The main objective of ISCMI 2022 is to present the latest research and results of scientists related to Soft Computing & Machine Intelligence topics. This conference provides opportunities for the delegates to exchange new ideas face-to-face, to establish business or research relations as well as to find global partners for future collaborations. We hope that the conference results will lead to significant contributions to the knowledge in these up- to- date scientific fields.
ISCMI 2022 is organized by 
India International Congress on Computational Intelligence(IICCI), and technically sponsored by the IEEE Toronto Section and IEEE Toronto Women in Engineering.

Paper submission and registration details can be found here.

IEEE Newsletter Library

Aerospace & Electronic Systems Society:

Biometrics Council:

Circuits & Systems Society:

Communications Society – Technical Committees:

Computer Intelligence Society:

Computer Society:

Control Systems Society:

Future Directions:

Geoscience and Remote Sensing Society:

Industry Applications Society:

Information Theory Society:

Instrumentation & Measurement Society:

Intelligent Transportation Society:

Internet Initiative:

Internet of Things (IOT):

Life Members:

Magnetics Society:

Oceanic Engineering Society:

Power & Energy Society:

Robotics & Automation Society:


Signal Processing:

Smart Grid:

Solid-State Circuits Society:

Systems Council:

Systems, Man and Cybernetics Society:

Ultrasound, Ferroelectrics, and Frequency Control Society:

Vehicular Technology Society:

Women in Engineering (WIE):

Young Professionals:

Every year in March, the Canadian engineering community celebrates National Engineering Month. It is the largest celebration of engineering excellence. It is to celebrate the diversity of thought and people that make up the engineering profession, and demonstrates that there’s a place for everyone, especially women, in engineering to learn and grow together. The world of engineering keeps growing and we have to change with it. Here are some statements from IEEE Chapter Chairs and supporters.

Lian Zhao, Chair of Vehicular Technology Chapter, IEEE Toronto Section:

I am happy to celebrate the International Women’s Day, as a way to highlight Equity, Diversity, and Inclusion (EDI) for women to engage in all areas of specialization, and to recognize the achievements and contributions of Women Engineers and Women Researchers.

Mehrdad Tirandazian, Chair of Systems, Man and Cybernetics (SMC) Chapter, IEEE Toronto Section:

Engineering is a discipline dedicated to problem solving, it consists of different fields of Science and Mathematics, and helps us to clean the environment and water systems, create clean and efficient transportation systems, find new sources of energy, and find solutions to some of the world’s most complex challenges too.

Sylvia Raynham, Previous WIE Treasurer, IEEE Toronto Section:

I like to thank the IEEE Toronto Section for presenting me the “Appreciation of Service Award”. One has said that “women are the pillar of the society”, being a member of Women in Engineering and having 2 daughters who are part of the STEM (Science, Technology, Engineering and Math) work force. I strongly recommend women and men continue to striving for the best that they can be to tackle some of the world’s big issues and participate in the more demanding careers in the STEM area such as Artificial intelligence specialist, Data Scientist, Robotics.

Hadeel Elayan Mohammad, Vice Chair of Communications Chapter, IEEE Toronto Section:

Engineering is a passion that I nurtured through my continuous quest to explore all that is new and dig deep into problems until I find solutions. Studying engineering allowed me to constantly rediscover myself as I am always exposed to the most novel technologies and trends. It made me realize that truly disruptive technologies can emerge at the interface of diverse research arenas which is the key to innovative solutions. For all young women interested in a career in STEM, particularly engineering, I would say not to fear failure, but rather fear not trying. Always remember that when one door closes, somewhere a window opens. It’s only through persistence that we can find who we are. Salute to all strong women, may we know them, may we be them, may we raise them.

Abdul Bhuiya, Vice Chair of PELS&CE Chapter, IEEE Toronto Section:

There are a couple of things that comes to mind when I think of engineering. I think of solving, designing, inventing, testing, creating, etc. To me, all these words are just part of what it means to be an engineer. It allows us to dream big and mold them into reality. It is a form of art, and it is the satisfaction you get when you see your work come to realization. Sometimes we find ways to solve difficult problems with simple solutions and other times, we have problems that require us to put hours of work and thought into it. There is so much to engineering and this only hits half of what it means to be an engineer. Everything you design and create will be questioned. We study the trade-offs e.g., cost vs. performance, we study the environmental effects of our work, and we ensure our work is done correctly, safely, and thoroughly. We are held to have the highest of standards, so the public can trust the work we do and the products they use. Engineering can open so many doors and possibilities for your career growth and ambitions. I believe anyone can become an Engineer. It doesn’t matter who you are, if you have the right mindset, motivation, and creativity, you can really accomplish great feats.

Shermineh Ghasemi, Secretary of Computational Intelligence,  IEEE Toronto Section:

It’s easy for us to get caught up in negative patterns, versus seeing what positive changes you can make. Especially for women and minorities, we need to learn to see challenges as stepping-stones instead of hurdles. They really can bring you experience and closer to your goals.

Julia Wagner, Chair IEEE University of Toronto Student Branch:

By studying engineering, I feel that my future has unlimited possibilities with the fields I can work in and the impact I can have on the world. While being an engineer can be challenging, I look forward to the rewards of doing complex work and providing an example to women interested in pursuing a career in engineering.

Younas Abbas, Vice Chair, Computer Chapter, IEEE Toronto Section:

Engineering is at its pinnacle and we are in the position to find cures for diseases, elevate the suffering from those parts of the world where hunger, poverty, lack of education and absence of basic necessities of life are ailing humanity. The world has come so far with the help of technology overcoming numerous problems which were a dream in the past centuries. The evolution of science has helped humanity to explore the galaxies, go deeper into the oceans, finding ways to save the endangered species of our home planet earth and about finding new homes for humanity on other planets.

No matter which direction humanity would pursue, women have been playing a great role to bring us to the next level. From centuries, women like Fatima Al-Fihri who belongs to a migrant community in Fes, Morocco established the first degree-granting education institute (recognized by UNESCO and Guinness World Records) in the year 859 to Maire Curie (Marie Salomea Skłodowska Curie 1867-1934) a great physicist and chemist, Edith Clarke an electrical engineer, Grace Murray Hopper a computer scientist, Katherine Johnson, Chien-Shiung Wu, Rosalind Franklin. The list is very long. They were never a step behind to serve humanity and still playing their part. Recently in west Germany when a couple, Sahin and Tureci, founder of BioNTech breakthrough in finding the cure for COVID-19 it has proved that women are a crucial counterpart for curing humanity.

These great women and a lot more I wasn’t able to mention, deserved to be recognized well. The world still needs to learn that equality in every form is necessary to be treated everywhere and humans should not be identified on the basis of their gender, race, color, or anything else but what actually they do.

Our Team

Dr. Fatima Hussain

Newsletter Editor | IEEE Toronto Section

Dr. Fatima is working as a Manager, Event Management and Analytics  in “Behaviour Analytics and Insider Threat” team, Global Cyber Security,  Royal Bank of Canada (RBC), Toronto, Canada. She is responsible for employee risk profiling and detection of insider threats, by establishing baseline behaviours.

She is also an Adjunct Professor at Ryerson University, Toronto and her role includes the supervision of graduate research projects. Dr Hussain’s background includes a number of distinguished professorships at Ryerson University and University of Guelph where she has been awarded for her research, teaching and course development accomplishments within Wireless Telecommunication and Internet of Things.

Her research interests include Insider Threat Detection, API Security, Cyber Security and Machine Learning. She is a prolific author with various conference and journal publications to her credit. Dr. Hussain received her PhD and MASc degrees in Electrical and Computer Engineering from Ryerson University, Toronto. Upon graduation she joined the Network-Centric AppliedResearch Team (N-CART) as a post doctoral fellow where she worked on various NSERC-funded projects in the realm of the Internet of Things.

Dr. Ameera Al-Karkhi

Newsletter Coordinator | IEEE Toronto Section

Dr. Ameera Al-Karkhi is working as a Professor at Sheridan College. She holds PhD in Computing, Science and Engineering Department from University of Salford, UK. She has worked as Postdoctoral Fellow at Ryerson University and University of Guelph, in areas such as, IoT Environment, Cloud Computing and Contextual Security. She has also worked as a Data Scientist at ML4BD Inc. and contributed in various projects including Feature Selection, Classifiers Development and Data Analysis using machine learning techniques.

She has various academic publications in different conferences and journals in Computer Engineering, Machine Learning and IoT domains. Her research interests include providing and developing solutions in the area of Cyber Security, User Identity Assertion and Context Aware systems within Internet of Things environments and Cloud Computing.

Melanie Soliven

Webmaster | IEEE Toronto Section

Melanie Soliven is an undergraduate Computer Science student at Ryerson University. Her interest in coding and the growing tech industry lead her to the Computer Science program at Ryerson. As part of her education, she has learned how to write programs in Python, Java, and C. In her free time, she likes to illustrate and develop her skills in front-end web development.

She is currently the volunteer webmaster for the IEEE Toronto Section.

Newsletter Archive

Find previous issues of the Toronto Section Newsletter here.




Editor: Fatima Hussain

Coordinator: Ameera Karkhi

Webmaster: Melanie Soliven