Department of Biology MSc Thesis Defence - Zannat Mahal

Event Date: 
Wednesday, May 5, 2021 - 10:30am to 1:00pm EDT
Event Location: 
Zoom
Event Contact Name: 
Heather Suslyk
Event Contact E-mail: 

Title: “Enhanced Hydrolysis of Polyethylene Terephthalate (PET) by Ozone and Ultrasound pretreatment”

Supervisory Committee:
Dr. Sudip Rakshit (supervisor)
Dr. Kam Leung
Dr. Baoqiang Liao
Dr. Ebrahim Rezaei (external examiner)

Please contact biology@lakeheadu.ca for the meeting ID and password.
All are welcome to attend.

Department of Biology MSc Thesis Proposal - Georgina Tough

Event Date: 
Wednesday, April 28, 2021 - 1:00pm to 3:00pm EDT
Event Location: 
ZOOM
Event Contact Name: 
Heather Suslyk
Event Contact E-mail: 

Title: "Optimizing ratios of wood ash to papermill biosolids for use as a soil amendment in Thunder Bay to increase crop yield and soil quality”

Supervisory Committee:
Dr. Amanda Diochon (supervisor)
Dr. Kam Leung
Dr. Tarlock Sahota

Please contact biology@lakeheadu.ca for the meeting ID and password.
All are welcome to attend.

Computer Science Department Thesis Defense - Punardeep S. Sikka

Event Date: 
Monday, April 26, 2021 - 10:00am to 11:30am EDT
Event Location: 
Online
Event Contact Name: 
Rachael Wang
Event Contact E-mail: 

Please join the Computer Science Department for the upcoming thesis defense:

Presenter: Punardeep S. Sikka

Thesis title: Data Preparation & Model Development for Text Simplification

Abstract: Text simplification (TS), defined narrowly, is the process of reducing the linguistic complexity of a text, while still retaining the original information and meaning. More broadly, text simplification encompasses other operations; for example, conceptual simplification to simplify content as well as form, elaborative modication, where redundancy and explicitness are used to emphasize key points, and omission of peripheral or inappropriate information. TS is a diverse field with a number of target audience, such as beginner and foreign language learners, the dyslexic, the aphasic etc. This research provides a significant contribution towards the goal of building the first, fully automated and open-source system for TS. TS originally involved simplification through hand-crafted rules of language, a process which is not only extremely time-consuming, but also not applicable across languages. Most recent techniques have automated the rules learning process by using deep neural networks and language models. An extensive survey on TS was first conducted before starting system development, to identify current limitations and research obstacles. TS can be divided into two major components: lexical simplification that involves substituting complex words/phrases with simpler ones, and novel text generation, which generates new simplified version of the input text. This thesis focuses on the latter, focusing on data and models involved. To allow deep learning models to automatically learn simplification rules, a large amount of data is needed, especially in the form of simple and complex sentence pairs, needed to train sequence-to-sequence models. The lack of existing such data of particularly high quality necessitated a focus on a dataset development first. There are only two sources available 2 to extract complex/simple sentence pairs from: Regular & Simple English Wikipedia and the Newsela corpus. A Newsela dataset was extracted for this thesis, which is shown to outperform models trained using any previous Newsela extraction. Also, for this research, three deep learning models were developed, and used to benchmark most commonly used datasets for training TS models, and the effect of using each dataset quantified. The models were then used to set state-of-the-art benchmarks using the best training datasets available. An initial version of the web application for TS application was developed, in conjunction with other developers, which uses one of the three developed models. Having developed an initial system, this research is expected to continue, with the next steps of focusing on lexical simplification and multi-language simplification.

Committee Members:
Dr. Vijay Mago (supervisor, committee chair), Dr. Tin Duy Vo, Dr. Abdulsalam Yassine (Software Engineering)

Please contact grad.compsci@lakeheadu.ca for the Zoom link.
Everyone is welcome.

Juried Art Show 2021

Event Date: 
Friday, April 16, 2021 - 7:00pm EDT to Friday, May 7, 2021 - 9:00pm EDT
Tuesday, April 20, 2021 - 7:00pm EDT to Tuesday, May 11, 2021 - 9:00pm EDT
Tuesday, April 27, 2021 - 7:00pm EDT to Tuesday, May 18, 2021 - 9:00pm EDT
Tuesday, May 4, 2021 - 7:00pm EDT to Tuesday, May 25, 2021 - 9:00pm EDT
Event Location: 
https://us02web.zoom.us/j/81711336498 by Zoom
Event Contact Name: 
Jennifer Howie
Event Contact E-mail: 

poster

All welcome! Exhibition goes live at the Thunder Bay Art Gallery on Wednesday 14 April 2021 and can be accessed here: https://theag.ca

Computer Science Guest Speaker Series: Decentralized Artificial Intelligence

Event Date: 
Friday, April 16, 2021 - 12:00pm to 2:00pm EDT
Event Location: 
Online
Event Contact Name: 
Rachael Wang
Event Contact E-mail: 

THE DEPARTMENT OF COMPUTER SCIENCE GRADUATE SEMINAR 2021
Guest Speaker Series Presented By:

Dr. Muhammad Khan
"Decentralized Artificial Intelligence"

Friday, April 16, 2021
12:00 pm

Abstract:
Artificial intelligence at scale requires significant infrastructure and knowhow beyond the field. As a result, the development of cutting edge AI solutions has become the prerogative of a handful of corporations. This centralization of AI raises several technical and ethical issues around algorithm quality, human resource utilization and bias. Blockchain technology provides a means to build a more robust AI ecosystem in which different entities can not only participate but also collaborate without compromising their respective interests. Several projects already exist that enable small companies and independent developers to build AI services in the cloud and monetize them through public blockchains. As someone who is involved, I will provide an overview of the state of the art and the upcoming developments in this space.

Biography:
After a decade-long career in academia across three continents, Dr. Muhammad Khan took over as the VP Technology at InBridge Inc, which is a Canadian company building AI and blockchain solutions for industry.

He is spearheading the development of InBridge's IoT powered blockchain platform for environmental monitoring supported by the National Research Council (NRC) Canada as well as its enterprise AI and blockchain projects. Muhammad is a member of the Hyperledger Blockchain Media & Entertainment Group and helps in the development of Canadian technology standards at the CIO Strategy Council. With a masters from the University of Cambridge and a PhD from Calgary, he has held faculty positions at U of Calgary and Lethbridge among others.

He has over thirty publications on graph algorithms, software engineering, data science and blockchain technology, including a book. Over the years, his research has attracted funding from Cambridge Trusts, Noon Foundation, National Science and Engineering Research Council (NSERC) Canada, Alberta Innovates, Vanier-Banting Secretariat, Killam Trusts and Regional Innovation Network of Southern Alberta. Muhammad is passionate about building the Canadian tech ecosystem and supporting women entrepreneurs. In March 2019, he co-organized the BCHack Blockchain Hackathon and, in May, mentored a team of women from Lethbridge, Alberta, to third place finish in CryptoChicks International AI and Blockchain Hackathon. He has since developed and presented multiple emerging tech workshop series for entrepreneurs under the Western Economic Diversification (WED) Canada Women in STEM Program.


To register for this virtual event, please email grad.compsci@lakeheadu.ca and a Zoom link will be shared.

Everyone is welcome.

Department of Biology MSc Thesis Proposal - Cody Veneruzzo

Event Date: 
Friday, April 30, 2021 - 10:00am to 12:00pm EDT
Event Location: 
Zoom
Event Contact Name: 
Heather Suslyk
Event Contact E-mail: 

Title: “Impact of Microplastics on Oxygen Uptake in Freshwater Fishes”

Supervisory Committee:
Dr. Michael Rennie (supervisor)
Dr. Constance O’Connor
Dr. Michael Paterson

Please contact biology@lakeheadu.ca for the meeting ID and password.
All are welcome to attend.

Psi Chi Induction Ceremony

Event Date: 
Thursday, April 15, 2021 - 4:00pm to 5:30pm EDT
Event Location: 
Zoom
Event Contact Name: 
Aaron Craig
Event Contact E-mail: 

Hello students and faculty!

We are very pleased to invite you to Psi Chi's Annual Induction Ceremony! Our featured speaker for this year is Dr. Beth Visser. Dr. Visser will be discussing her research with the "dark triad" personality traits, which include machiavellianism, narcissism, and psychopathy. Her research draws inspiration from politicians and serial killers where it focuses on human malevolence. This will surely convince you that personality does matter!

This talk will take place on Thursday, April 15 at 4 pm via Zoom (please see link information below).

Prior to Dr. Beth Visser's talk, we will be hosting our annual 2021 Induction Ceremony welcoming our newest members to Psi Chi! In addition to all of this, everyone who is in attendance will receive a coupon for a locally-owned business, The Pasta Shoppe!

You can also visit our Facebook (Psi Chi Lakehead University), Instagram (@psichilu), or the Google Doc attached to this email to view the posters!

We hope to see you there!

Join Zoom Meeting
https://lakeheadu.zoom.us/j/94428067683
Meeting ID: 944 2806 7683

Sincerely,
-Your Psi Chi Executive Team

Anthropology MSc Thesis Defence - S. Friesen

Event Date: 
Thursday, April 15, 2021 - 2:00pm to 4:00pm EDT
Event Location: 
Zoom
Event Contact Name: 
Jennifer McKee
Event Contact E-mail: 

Sarah Friesen

Title: "Shape variation in the talus and medial cuneiform of chimpanzees and bonobos"

Join Zoom Meeting
https://lakeheadu.zoom.us/j/95997254508?pwd=ZnhsV0EydXFSdE9ZR3d3VU5IYWVO...

Meeting ID: 959 9725 4508
Passcode: 493950
One tap mobile
+12042727920,,95997254508# Canada
+14388097799,,95997254508# Canada
Find your local number: https://lakeheadu.zoom.us/u/aBKcfzjML


Equality in Business: Learning from Influential Women

Event Date: 
Friday, April 9, 2021 - 5:00pm EDT to Saturday, April 10, 2021 - 12:00pm EDT
Event Location: 
Zoom
Event Contact Name: 
Allison Buchanan
Event Contact E-mail: 

The Faculty of Business Students' Association (FoBSA) and the Business Orillia Student Society (BOSS) are hosting a virtual conference featuring influential women in business. Several speakers and workshops will be held the evening of April 9th and the morning of April 10th.

Learn about timely topics like building your career, leadership and social entrepreneurship.

Featuring speakers and workshop hosts: Sandi Boucher, Sharla Brown, Margarita Cargher, Barb Elinesky and Laura Vaughn.

$10 to sign up for the speakers, workshops and a door prize! Free to sign up for speakers.

For more information or to register in advance for this event, follow the link: https://docs.google.com/forms/d/e/1FAIpQLSc0cpF6ea666f-u-BgNKvua0o6q7R1U...

Computer Science Department Thesis Defense - Pedram Khoshnevis

Event Date: 
Tuesday, April 20, 2021 - 1:00pm to 2:30pm EDT
Event Location: 
Online
Event Contact Name: 
Rachael Wang
Event Contact E-mail: 

Please join the Computer Science Department for the upcoming thesis defense:

Presenter: Pedram Khoshnevis

Thesis title: Design, Development and Usability Evaluation of Social System Interface and Development of Computational Model

Abstract: In recent times, new machine learning algorithms, which aim to solve real-life problems, are developed by computer science researchers in collaboration with domain experts. There has also been an increased emphasis on the usability aspect of these algorithms by developing easy-to-use web interfaces. The graphical user interfaces (GUIs) designed for these algorithms are often designed solely to connect the web interfaces to the algorithm's functionality. While this is effective from researchers' perspective, the needs of new users (such as policymakers) in relation to software use are often neglected. The lack of consideration of new users' experience when developing GUIs often establishes usability issues for the technology and as a result expands the gap between the advances made in the computer science eld and other fields, most notably the social sciences. This thesis investigates the various design, development, and evaluation methods for social simulation software and provides valuable insights for researchers and user interface designers who seek to create an effective GUI. Additionally, this thesis provides a case study of how computational models can be effectively applied for approaching complex social problems such as homelessness. In chapter 3 the development and testing process of the Homelessness Visualization (HOMVIZ) platform is discussed. The HOMVIZ platform uses a deep learning algorithm in order to predict potential trends in homeless populations in a particular area of interest. Various aspects of the user interface (UI) design were analyzed and a 14 participant usability testing session was conducted in order to discern the perceived usability of the platform. The UI evaluation 1 session in this chapter involved software testing, focus groups, and questionnaires. These sessions provided our research with valuable qualitative and quantitative data. Chapter 4 explores moderated and unmoderated usability testing sessions and compares them in terms of efficiency, reliability, and flexibility. The research for this chapter was approved by the Lakehead University's Research Ethics Board. The usability testing was conducted with a sample size of 72 participants. The research presented in this chapter provides valuable insight regarding different usability testing session methods and the impact of a known phenomenon called careless responding (CR) on data quality. Chapter 5 provides an example of how computational models can help mitigate a more complex social problem such as homelessness. The research presented in this chapter focuses on the operation of homeless shelters within Canada and introduces eight computation models that have the potential to improve the quality of life of people experiencing homelessness.


Committee Members:
Dr. Vijay Mago (supervisor, committee chair), Dr. Muhammad Asaduzzman, Dr. Piper Jackson (Thompson Rivers University)

Please contact grad.compsci@lakeheadu.ca for the Zoom link.
Everyone is welcome.

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