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

Program

Sergii Baibara
Director of IBA Ukraine, part of IBA Group

From Robotic Process Automation (RPA) to Intelligent Process Automation (IPA) (slides: RPA IEEE QR)

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:

• The Shift from RPA to Intelligent Automation.
• Classification Algorithms in Action — Illustrate how classification algorithms streamline corporate operations.
• Information Extraction for Corporate Data — examine ML’s role in extracting data from unstructured corporate documents.
• Signature Recognition for Enhanced Security — explore the role of ML in recognizing and authenticating signatures in various corporate documents.
• Revolutionizing AI with GPT Models — uncover the latest advancements in Generative Pre-trained Transformer (GPT) models, highlighting their impact on the corporate sector.
• Delegating tasks to AI: Balancing Trust and Risk — emphasize the importance of understanding the cost of errors in each process.
• Specialized Platforms for Corporate Automation — advocate for a balanced approach with a human-in-the-loop for continuous quality improvement.

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

Dr. Josh Mutus
Director of Quantum Materials at Rigetti Computing

Quantum computing with superconducting qubits

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

Unleashing Potential: Harnessing Foundation Models (Large Language Models) in Business and Research
(IEEE-Okanagan_Chapter-Oct24th-2023)

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