The Research Institute in Data Science and Artificial Intelligence (RIDSAI) organizes three high-impact seminars each academic term, dedicated to advancing education and fostering collaboration in Artificial Intelligence (AI) and Data Science (DS). These events feature distinguished speakers from both academia and industry who share cutting-edge research, insights and practical applications.
Our seminars serve as a dynamic platform for addressing pressing challenges, exploring innovative solutions and facilitating interdisciplinary discussions. By bringing together experts and practitioners, RIDSAI aims to drive thought leadership and contribute meaningfully to the evolving landscape of AI and DS.
Please join the Research Institute in Data Science and Artificial Intelligence (RIDSAI) at our upcoming seminar on Evolution and current trends in AI and data science advancement. The event will feature short presentations by UNB researchers and industry partners on this theme followed by refreshments and a networking opportunity.
Abstract: The field of data science has evolved rapidly over the past decade, transforming from a niche technical skillset into a central pillar of decision-making across industries. As the practice matures, a key distinction has emerged between "doers" — those who write the code, build models, and create insights — and “advisors" — those who shape strategy, guide teams, and drive organizational impact through data. We will also discuss three guiding forces that will shape the future of data science over the next five years.
Bio: Jeremy Adamson is a leader in data and analytics strategy, and has a broad range of experience in aviation, energy, financial services, and public administration. Jeremy has worked with several major organizations to help them establish a leadership position in data science and to unlock real business value using advanced analytics.
Abstract: This talk will focus the research being carried out in her lab on developing AI-powered social agents that can provide personalized assistance and companionship. These agents leverage advanced AI techniques like generative AI and deep learning to exhibit human-like behaviors and adapt to individual user preferences. By investigating factors such as recommendation style, explanatory behavior of the agent, and human behaviour and expectations, her research aims to build trust and enhance the effectiveness of human-agent interactions. At the intersection of engineering and sociology, the talk will provide insights into harnessing sociological trust factors based on gender and personality in the design of AI agents.
Bio: Dr. Debasmita Mukherjee is an Assistant Professor in the Department of Electrical and Computer Engineering and Dr. J. Herbert Smith Centre for Technology Management and Entrepreneurship at the UNB. She received her PhD in Mechanical Engineering from The University of British Columbia in 2023.
Motivated by the dynamics and seamless collaboration within human teams, as well as the potential for working alongside highly adaptable AI agents, her research endeavors to create a safety-centric and natural communication framework for human-agent interaction within social scenarios. Her primary focus involves enhancing trust in custom AI agents though study of analogic and analytic trust factors and personalizing deep learning models to user behaviors using affective computing, naturalistic feedback mechanisms, probabilistic approaches, explainable AI techniques.
With experience in both research and development, spanning roles as a Senior Engineer in a multinational corporation and within academic settings, Dr. Mukherjee specializes in designing models geared towards deployment in real-world environments. Her research has been patented, published in prestigious journals and international IEEE conference as well as covered in news and media outlets.
Affiliation: UNB, Chemistry & RIDSAI
Abstract: The 2024 Nobel prizes in Physics & Chemistry not only celebrated the contributions of machine learning to the physical sciences, but it also generated food for thought and conversation. Guided by some pertinent questions and comments from leading colleagues, I will discuss how machine learning has shaped and likely will shape the landscape in STEM, from my perspective as a quantum chemist and beyond.
Bio: Stijn De Baerdemacker [he/him] is a Canada Research Chair T2 in Theoretical Chemistry and Associated Research Director of RIDSAI. Research in his QuNB quantum chemistry lab at UNB revolves around the development of quantum many-body methods to compute molecular properties, the analysis and development of interpretable machine learning tools and the design of quantum computing circuits in the search for quantum advantage in chemistry.
Abstract: Cyber-malice does not discriminate. Individuals and organizations are facing unprecedented amounts of threats, with substantial increases occurring over the last number of years. With the proliferation of AI, these threats are now becoming more difficult than ever to detect. The role of Human Intelligence in the safeguards and protection of our institutions is crucial and poised to become one of the key investments to ensure a secure future.
In this talk, we will highlight some of the most impactful events in recent years, the impact of AI in the threat landscape and the role of Human Intelligence in protecting ourselves and the organizations for which we work.
Nicole Bendrich’s Bio:
Nicole is a cybersecurity awareness solutions expert leading the Product Team at Beauceron Security. Her work focuses on innovation and collaboration with leading cybersecurity researchers to challenge perspectives in the cybersecurity awareness field and drive the industry forward.
Nicole works with some of North America’s largest enterprises, government, and critical infrastructure, helping awareness professionals create engaging, results-driven programs that foster a meaningful security culture and reduce risk.
Nicole holds a Master of Science in Engineering specializing in Machine Learning from the University of New Brunswick.
Rishabh Kalai’s Bio:
Rishabh is a Data Scientist at Beauceron Security, specializing in the human-side of cybersecurity. He holds a master’s degree in computer science from the University of New Brunswick (UNB), where he graduated in May 2024.
In his role, Rishabh analyzes large-scale data to identify trends and patterns that inform and enhance cybersecurity practices.
He focuses on using machine learning to close the loop on human feedback, helping organizations understand how human actions impact security outcomes and promote continuous learning.
Date: Nov. 27, 2024
Time: 1 to 3 p.m.
Location: Research Commons Event Space (318), Harriet Irving Library, UNB Fredericton
Kindly RSVP by Tuesday, Nov. 26.
Register to attend in person Register to attend virtually
Please share this invitation with colleagues and students who share an interest in Data Science and Artificial Intelligence research. Your participation is invaluable as we collectively navigate the frontiers of these transformative fields.