Tamilla Triantoro, PhD
Associate Professor, Business Analytics at Quinnipiac University
Tamilla Triantoro, Ph.D. is an Associate Professor in the School of Business at Quinnipiac University. She has directed graduate and undergraduate programs in Business Analytics at Quinnipiac University and the University of Connecticut. Her expertise includes Artificial Intelligence, Human-AI Collaboration, and the Future of Work. She has spoken about these topics in various parts of the world. and presented her work on six continents. With a Ph.D. from the City University of New York, where she researched online user behavior, Dr. Triantoro brings a deep understanding of the human element to her work.
All Sessions by Tamilla Triantoro, PhD
Optimizing Workplace with AI and Generative BotsMachine Learning | Beginner-Intermediate
This study investigates the interplay between artificial intelligence, human skills, and task characteristics, and their impact on organizational performance. Applying the Resource-Based View and Task Technology Fit theories, we explored how generative AI designed for collaboration, as both a firm resource and a capability, can enhance task execution across different dimensions - routine/creative tasks and easy/complex tasks. We conducted an experimental study involving the development of a marketing campaign with distinct subtasks reflecting these dimensions. Our findings show that firms can gain substantial benefits from integrating AI and that AI improves task outputs in automation, support, creation, and innovation. Our study also suggests a nuanced relationship between humans and AI in creative tasks with humans outperforming AI. The study highlights the value of upskilling and reskilling in AI, and proposes a strategic blend of AI and human creativity for optimal results. These findings have implications for understanding the role of AI in organizational tasks and formulating effective strategies for AI integration in business and beyond. Our exploration includes the innovative use of GPT models as decision-support tools, integrating diverse theoretical perspectives and a clear task division between humans and AI, to enhance both the efficiency and effectiveness of AI-human interactions in various decision-making contexts.
Data Synthesis, Augmentation, and NLP Insights with LLMsLLMs | All Levels
Data synthesis, augmentation, and NLP insights with LLMs offer a foundational approach to understanding and utilizing artificial intelligence in data science. This workshop is designed to guide participants through the process of creating synthetic data, enhancing datasets through augmentation, and applying NLP techniques to extract valuable insights. These skills are essential in various fields such as social media analysis, customer behavior studies, content generation, and more. By participating in this workshop, you will learn how to generate realistic and functional synthetic data using LLMs. You will also explore methods to enrich this data and make it more applicable for real-world scenarios. Additionally, you will apply NLP techniques to synthesized and augmented data to uncover patterns, sentiments, and trends.