2023 R7 IEEE IAS Workshop
Time & Date: 12:45 p.m., Saturday, December 16th, 2023
Location: Venue: Kaiser 2020/2030, Fred Kaiser Building (KAIS), UBC Vancouver.
Program: http://www.okanagan.ieee.ca/wp-content/uploads/2023/12/IEEE-IAS-Workshop-Program-v4.docx
The Okanagan College Department of Computer Science is looking for project proposals from industry for its Capstone Project courses COSC 224 and 471.
In the capstone project course, second-year students in teams of 3 to 5 and senior students in teams of 7 to 15 work on projects proposed by industry or other organizations.
The projects can be general in software development or specialized in software engineering.
For additional information on the projects and the Capstone Software Project courses, please visit http://www.okanagan.bc.ca/cosc and
If you have any questions, please get in touch with the Computer Science Department at Okanagan College: capstones [dot] okanagan [dot] bc [dot] ca or chair[dot]cis at okanagan[dot]bc[dot]ca
Sergii Baibara
Director of IBA Ukraine, part of IBA Group
Time & Date: 9:30 a.m., Tuesday, December 5th, 2023
Location: Room HS 102 and online in Zoom, Okanagan College, Kelowna, 1000 KLO Rd, Kelowna V1Y 4X8
Registration is open now: https://events.vtools.ieee.org/m/386898
Abstract:
In the ever-evolving landscape of corporate automation, the transition from Robotic Process Automation (RPA) to Intelligent Process Automation (IPA) is critical nowadays. Integrating Machine Learning (ML) technologies and sophisticated Generative Pre-trained Transformer (GPT) models reshape how financial institutions optimize their processes.
This presentation delves into Intelligent Process Automation, where traditional boundaries are surpassed, unlocking unprecedented possibilities. From the classification of tasks using ML algorithms to the revolutionary impact of GPT models, we explore each facet and unravel a narrative that underscores the transformative power of automation in the corporate sector.
During the talk, we will discuss the following topics:
Bio:
Sergii Baibara currently serves as the Director of IBA Ukraine, part of IBA Group, a position he has held since July 2012. IBA Group – 30 years in IT business, started as JV with IBM. He has 26 years of experience in the international IT software business, Including S&T AG and SAS Institute. Sergii has been developing RPA practices since 2016.
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
Pizza and Refreshments will be provided
Time & Date: 5 p.m., Wednesday, November 8th, 2023
Location: Room E 102, Okanagan College, Kelowna, 1000 KLO Rd, Kelowna V1Y 4X8 (Zoom: https://ca01web.zoom.us/j/65884995637?pwd=M2JqV25WMWNaYkJxK3kySGt3THplZz09)
Registration is open now: https://events.vtools.ieee.org/m/382340
Bios:
Thais Damasceno is a dynamic professional with 3+ years of work experience who is shifting from a legal career in Brazil to the world of technology in Canada. Following a year of legal practice, she relocated to Canada to enhance her English and discovered her passion for programming. Thais worked during a 9-month software developer internship at Willowglen Systems Inc, a pivotal experience that solidified her commitment to the industry. There, she worked mainly with JavaScript and C++. In Fall 2023, she embarked on her journey at Okanagan College, where she’s dedicated to advancing her technology expertise. This strives to bring innovative solutions to complex challenges, bridging her legal background with her technical knowledge.
Daniel Tumback has a background as a residential framer; however, his true passion is working on computers. After years of working in construction, he decided to go and get an undergraduate degree in computer information systems. He has a passion for building things, from assembling the components of a computer to building houses. He hopes to take that same passion into the computer science world and help build the future of computer components. He has a keen interest in the future of quantum computing and hopes to one day be on the front line of quantum development to truly help build the next generation of computing hardware.
Alexander Ross is a computer science enthusiast and aspiring professional. He is a 23-year-old Computer Science enthusiast with a strong foundation in programming and a dedication to innovation. His journey in the world of technology began at Okanagan College, where he is currently enrolled in the Computer Information Systems (CIS) program. As a third-year student, he has honed his skills in Java, C, C++, HTML/CSS, JavaScript, VB.NET, SQL, and SPARC while gaining expertise in Database Analysis and Design, micro-controllers, and circuitry design. In addition to his technical proficiency, he has had the opportunity to work in dynamic and high-stress environments. During his tenure at Kal Tire, he mastered adaptability and time management. Beyond his educational and work experiences, he is a quick learner with strong communication skills. He is excited about the possibilities and is eager to continue his journey in the world of technology.
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
Pizza and Refreshments will be provided
Dr. Josh Mutus
Director of Quantum Materials at Rigetti Computing
Time & Date: 5 p.m., Wednesday, December 6th, 2023
Location: Room E 309, Okanagan College, Kelowna, 1000 KLO Rd, Kelowna V1Y 4X8
Registration is open now: https://events.vtools.ieee.org/m/382333
Abstract:
What is a quantum computer, and what might it be useful for? I’ll describe how a quantum computer, based on superconducting qubits, works. I’ll also describe fault-tolerant quantum computing (FTQC), and the applications where a quantum computer might vastly outperform even the largest high-performance computing facility. What might such a “utility-scale” quantum computer look like, and how big would it be to solve problems intractable on today’s machines?
Bio:
Dr. Josh Mutus currently serves as the Director of Quantum Materials at Rigetti Computing, a position he has held since April 2021. He holds a Ph.D. in Physics from the University of Alberta and an undergraduate degree from the University of Windsor. Before joining Rigetti Computing, Josh was a member of the Google Quantum Hardware group as a Senior Research Scientist, where he worked for over six years from 2014 to 2021. Before Google, he did post-doctoral work at UC Santa Barbara.
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
Pizza and Refreshments will be provided
Fatemeh Hendijani Fard, PhD
Assistant Professor
Irving K. Barber Faculty of Science| Computer Science
The University of British Columbia
Time & Date: 5 p.m., Tuesday, October 24th, 2023
Location: Room EME 1121, UBC Okanagan, The University of British Columbia, Kelowna BC, V1V 1V7 Canada
Registration is open now: https://events.vtools.ieee.org/tego_/event/manage/378215
Abstract:
Leveraging Large Language Models (LLMs) has marked a significant milestone in recent months, notably with the introduction of ChatGPT in early 2023. These models have demonstrated remarkable potential in addressing straightforward queries and tasks. However, to fully exploit their capabilities in handling routine inquiries, adept prompt engineering is essential. Furthermore, the adaptability of LLMs to novel tasks and domains is pivotal. It is crucial to recognize that each company or research field possesses unique requirements, necessitating tailored adaptations of LLMs. The specificity of these needs often hinges on domain-specific data, demanding meticulous consideration. How can these models be tailored to classify your data effectively? What strategies can be employed when dealing with a limited dataset? Complex scenarios, such as querying vast repositories of textual files stored in directories, underscore the challenges. These files encompass diverse modalities, formats, and structures, ranging from structured to entirely unstructured content.
In this research presentation, we will delve into an exploration of LLM capabilities and pinpoint the areas where they encounter limitations. Subsequently, we will elucidate various techniques for fine-tuning these models, especially in scenarios where data availability is constrained. By addressing these challenges, we aim to provide valuable insights into harnessing the full potential of LLMs, ensuring their optimal performance in diverse and data-intensive applications.
Bio:
Dr. Fatemeh Hendijani Fard is an Assistant Professor at The University of British Columbia, Okanagan, Canada, where she leads the Data Science and Software Engineering lab. Her research interests lie at the intersection of Natural Language Processing and Software Engineering, with a focus on code representation learning and transfer learning for low-resource languages, as well as mining software repositories. She collaborates closely with industry partners and has contributed her expertise as a program committee member and reviewer for esteemed journals and conferences, including IEEE Transactions on Software Engineering, ACM International Conference on the Foundations of Software Engineering, and IEEE/ACM International Conference on Automated Software Engineering. Dr. Fard is an IEEE Senior member, and she actively gives back to the community by mentoring females interested in Artificial Intelligence.
For further information, please contact Youry Khmelevsky (email: Youry at IEEE.org) and subscribe for the news at okanagan@listserv.ieee.org)
Pizza and Refreshments will be provided
Emilio Sagre, Gustavo Dutra, Niha Siddikha Sachin, Steven Whang
Data Analytics, Langara College
Time & Date: 5 p.m., Wednesday, December 14th, 2022
Location: Room HS301 and via Zoom (see an email and registration information)
Registration is open now: https://events.vtools.ieee.org/m/337514
Abstract:
Creating accurate predictions in the stock market has always been a great challenge in finance. With the rise of machine learning as the next level in the forecasting area, this research compares four machine learning models and their accuracy for forecasting three well-known stocks traded in the NYSE in the short term over the period from March 2020 to May 2022. We deploy, develop, and hypertune XGBoost, Random Forest, Multi-layer Perceptron, and Support Vector Regression models and report the models that produce the highest accuracies from our evaluation metrics: RMSE, MAPE, and MPE.
Speakers Bio:
For further information, please contact: Youry Khmelevsky (email: Youry at IEEE.org) and subscribe for the news at https://listserv.ieee.org/cgi-bin/wa?SUBED1=okanagan&A=1)
Pizza and Refreshments will be provided
Evan MacKinnon
Computer Science Department
Okanagan College
and
Dakota Joiner
Computer Science Department
Okanagan College
Time & Date: 4 p.m., Wednesday, April 27, 2022
Location: Room E102 and via Zoom (see email and registration information), Computer Science Department, Okanagan College
Registration is open now: https://events.vtools.ieee.org/m/312801
Abstract:
Phylogeny is the evolutionary history of a species or group of organisms. Evolutionary trees can be analogized to graph trees, thus determination of these structures aids in inferring the evolutionary history of groups of organisms, extant and extinct. K-leaf power graphs enhance the ability of researchers to map paralogous and xenologous speciation events in what is a considerably difficult area to correctly predict past relationships.
Forbidden subgraph characterization is a method by which to characterize a graph class with a set of graphs that do not belong to that class. Identification of minimal forbidden induced
subgraphs is one method of characterizing the k-leaf powers of graph trees. A tree is a k-leaf power if, and only if, the leaves are connected by at most distance k. Structures for 2-leaf, 3-leaf, and 4-leaf powers are well understood, however, there does not exist a published list of forbidden subgraph leaf powers for values of k ≥ 4. In service of cladistics, k-leaf powers are frequently edited by adding or removing nodes and edges to the closest “proper” representation of a pairwise comparison of groups of organisms.
We demonstrate a deterministic, reductionist approach to generating 4-leaf, 5-leaf, and 6-leaf powers using Python, the graph library Networkx, and the Nauty suite of graph generation and labelling programs. The list of non-k-leaf powers in this range has not been proven finite, so this approach does not cover all possible structures should the list be infinite.
Speakers Bio:
For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org) and subscribe for the news at https://listserv.ieee.org/cgi-bin/wa?SUBED1=okanagan&A=1)
Pizza and Refreshments will be provided
Albert Wong, Ph.D.
Math Department, Langara College
IEEE Member
and
Youry Khmelevsky, Ph.D.
Computer Science Department
Okanagan College
Time & Date: 4 p.m., Tuesday, March 29, 2022
Location: Room L318 (up to 16 peoples), Langara College, 100 West 49th Avenue, Vancouver B.C., Canada V5Y 2Z6 and Online (Via email and Registration below)
Registration is open now: https://events.vtools.ieee.org/m/309786
Abstract: A profitable algorithmic stock trading algorithm benefits from a forecasting system that can produce accurate short-term forecasts. Based on this premise, we proposed to build up our previous experience in building short-term forecasting models using machine learning models. The research project aims to develop effective algorithmic trading algorithms based on accurate short-term forecasts for financial time series using machine learning models. The project focuses on three research activities: (1) building a data warehouse containing the targeted financial time series and other time series considered valuable as input to the machine learning models. Data acquisition, processing, and staging routines that are required to feed the data warehouse dynamically are evaluated and developed. A data visualization and business intelligence layer is also built on top of the data warehouse; (2) a short-term forecasting model based on machine learning is developed using the various time-series data from the data warehouse. Machine learning algorithms such as neural network, random forecast, support vector regression, XGBoost, and long short-term memory (LSTM) are evaluated in conjunction with several performance criteria to identify the most accurate model from a short-term trading perspective; (3) an automated evaluation system is developing to assess the effectiveness of existing algorithmic short-term trading strategies. Novel algorithms are also developed and evaluated using the evaluation system and the short-term forecast machine learning model.
The current research project was motivated by 3 NSERC funded projects:
Speakers Bio:
For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org) and subscribe for the news at https://listserv.ieee.org/cgi-bin/wa?SUBED1=okanagan&A=1)
Refreshments will be provided
Dennis Estacion, CET, CITP, MBA, CPA, CMA
Senior Endpoint Security Architect
IEEE Member
Time & Date: Moved to 2022 (bad road conditions in BC).
Location: Room E207, 1000 KLO Rd., Kelowna, BC (at Okanagan College) and Online (TBA via emails and vTools)
Registration is open now: https://events.vtools.ieee.org/m/294130
Abstract: Information security is to protect information from unauthorized use, disruption or destruction. There are three categories of control used to secure information: management, physical and operational security. Endpoint Security is the practice of securing endpoints or entry points of end-user devices, and falls under this operational security category, being one of the security topologies applied to a subset of systems like desktops, laptops or other mobile devices. The four common attack vectors of endpoint security are shadow IoT devices, BYOD/mobile devices, insider threat and insecure applications. Some consequences of endpoint security failure are theft and sale of the customer and member list to competitors, payroll data leaked to employees, private information of customers or employees leaked, and your data encrypted and held for ransom. Any of the resulting financial, regulatory and reputational impacts could undermine a company’s viability. Endpoint security is no longer optional for any size of the enterprise.
Speakers Bio:
Graduated: Bachelor of Science in Electrical Engineering, University of the Philippines
Graduated: MBA, Queen’s University
Current Designations: Certified Engineering Technologist (ASET); CITP (Certified I.T. Professional), American Institute of CPAs; Chartered Professional Accountant (CPA) – granted this designation concurrently after the unification of Alberta accounting bodies in 2015; Certified Management Accountant (CMA), CMA Alberta
Information Technology Security Experience:
For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org) and subscribe for the news at https://listserv.ieee.org/cgi-bin/wa?SUBED1=okanagan&A=1)
Refreshments and Pizza will be provided