[RCAC Workshop]AI in Scientific Research & Education
📅 Date: December 4th, 2026 ⏰ Time: 1PM-2PM 💻 Location: Virtual 🏫 Instructor: Ashish
Artificial intelligence is becoming increasingly embedded in how researchers conduct scientific work and how educators design, deliver, and support learning. Researchers are using AI to explore literature, write and debug code, analyze data, generate hypotheses, automate repetitive workflows, and communicate scientific results. At the same time, educators are experimenting with AI-assisted tutoring, assessment, course development, feedback, and personalized learning experiences.
This session explores how AI can be used practically across scientific research and education while also examining the limitations and risks that come with these tools. We will discuss where AI can genuinely improve productivity and discovery, where human expertise remains essential, and how issues such as reliability, reproducibility, privacy, and responsible use should be considered. Practical examples will highlight how researchers, faculty, and technical teams can incorporate AI into existing workflows without treating it as a replacement for scientific judgment or instructional expertise.
Who Should Attend Faculty, researchers, graduate students, research software engineers, educators, instructional staff, data scientists, and technical professionals interested in applying AI within research or teaching environments. The session is especially relevant for those exploring how generative AI and emerging AI tools can support scientific and educational workflows.
Topics
AI-assisted scientific discovery and research workflows Literature review, synthesis, and knowledge exploration AI for coding, debugging, and scientific software development Data analysis, modeling, and scientific computing Generative AI for teaching, tutoring, and learning support AI-assisted course and educational content development Reliability, reproducibility, privacy, and responsible use Practical applications across scientific and academic disciplines
Level Beginner to Intermediate. No specialized AI background is required, although familiarity with common AI or generative AI tools will be helpful.
🔗 Register now: LINK