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“Enhancing Research Replicability using Human-Centered AI” - Tatiana Chakravorti, Penn State
Date & Time: September 12, 2025 from 03:00 PM - 04:00 PM
Location: E202 Westgate and Virtual via Zoom
This event is part of the Young Achievers Symposium series hosted by Penn State's Center for Socially Responsible Artificial Intelligence.
About the Talk
Reproducibility, replicability, and transparency are cornerstones of scientific integrity, ensuring that research findings are trustworthy and robust. Open science practices such as sharing data, code, and methodologies have become central to advancing these principles, enabling other researchers to validate and build upon existing work. In the past decade, the open science and science of science communities have made significant strides in addressing concerns about the credibility of published findings. However, substantial gaps remain. Many researchers remain unaware of the challenges posed by the reproducibility crisis or are uncertain about best practices for producing reliable, transparent research. In the context of rapidly evolving artificial intelligence (AI) technologies, our study explores how AI can support and improve scientific credibility. At the same time, it recognizes the importance of explainability in AI systems and human AI collaboration, particularly when applied to high-stakes tasks such as evaluating scientific validity. The core aim of this work is to foster a more open, interpretable, and globally accessible scientific process where research outputs are not only available but also understandable and usable across disciplines.
About the Speaker
Tatiana Chakravorti is a doctoral student in Informatics in the College of Information Sciences and Technology at Penn State, under the supervision of Dr. Sarah Rajtmajer, where she applies advanced research and problem-solving skills to real-world challenges. Her work focuses on improving the reproducibility and reliability of published research through technology-driven solutions and cross-disciplinary collaboration. She has led and contributed to projects focused on human-centered AI, human-AI collaboration, usability testing of AI tools, large-scale survey design, and the science of science. These experiences have equipped her with strong expertise in data analysis, experimental design, and AI usability, as well as the ability to collaborate across teams and deliver actionable, technology-enabled outcomes.
About the Series
The CSRAI Young Achievers Symposium series highlights early career researchers in diverse fields of AI for social impact. The series seeks to focus on emerging research, stimulate discussions, and initiate collaborations that can advance research in artificial intelligence for societal benefit.
Our events and programs are open to all students regardless of sex, gender, sexual orientation, race, or any other protected class. The College of Information Sciences and Technology is committed to building a community of belonging for all.