Education
- BE, Dept. of Chemical Engg. & Tech. (DCET), Panjab University, Chandigarh
- MBA, Marketing, Management Development Institute (MDI), Gurgaon
- PhD (Information Systems), Operations and Management Information Systems, University of Connecticut
Biography
Dr. Rohit Aggarwal, a Professor of Information Systems at the University of Utah, specializes in advancing AI systems, with applications spanning software development, recruitment, and content creation. His research concentrates on extracting tacit knowledge of human experts and integrating it into AI agents, thereby enhancing their capability to support complex decision-making processes.
His work places a strong emphasis on refining the transparency and explainability of AI models' decision-making processes. He aims to demystify the inner workings of AI systems, making them more accessible and comprehensible to both experts and lay users alike. This endeavor is crucial for fostering trust, addressing ethical considerations, and promoting responsible AI usage. Through his research, Dr. Aggarwal seeks to develop AI systems that not only provide accurate and reliable results but also offer clear explanations for their decisions.
In addition to his work on explainability, Dr. Aggarwal is involved in developing a single, fine-tuned model that can effectively perform a wide range of tasks within a given domain using only a few-shot prompting technique. This approach eliminates the need to switch between task-specific adapters and layers, streamlining the deployment and utilization of AI models in real-world applications. Creating (synthetic) datasets for instruction tuning AI models using domain-specific tasks and datasets play importat role in this stream of work. Moreover, this initiative plays a crucial role in setting comprehensive benchmarks for evaluating AI systems across multiple dimensions, aiming to standardize performance metrics and ensure robustness in AI-driven solutions.
Another aspect of Dr. Aggarwal's research involves exploring the application of AI in the realm of advertising, specifically focusing on unique selling propositions (USPs). By leveraging the power of large language models (LLMs) and computer vision (CV) techniques, Dr. Aggarwal and his team are developing innovative methods to extract and analyze USP features from advertisements and landing pages. By understanding the most effective USPs in their industry, companies can refine their advertising campaigns, create more targeted content, crafting compelling narratives around these key differentiators, and ultimately improve their market positioning.
Dr. Aggarwal has published in premium business journals such as Management Science, Information Systems Research, MIS Quarterly, and POM, showcasing his extensive contributions to the academic community. He currently serves as SE at POM.
Former PhD students:
Dr. Nicholas Sullivan, Assistant Professor @ University of Mississippi, https://business.olemiss.edu/faculty-directory/dr-nicholas-sullivan/, Doctor of Philosophy (Ph.D.), Project Type: Dissertation. Role: Chair.
Dr. Michael Lee, Assistant Professor @ University of Nevada at Las Vegas, https://www.unlv.edu/people/michael-lee. Doctor of Philosophy (Ph.D.), Project Type: Dissertation. Role: Chair.
Dr. DongYoung Lee, Assistant Professor @ McGill University, https://www.mcgill.ca/desautels/dongyoung-lee. Doctor of Philosophy (Ph.D.), Project Type: Dissertation. Role: Member.