Tatiana Chakravorti, a doctoral candidate in the College of Information Sciences and Technology at Penn State, will deliver “Enhancing Research Replicability using Human-Centered AI” as part of CSRAI's Young Achievers Symposium. This lecture is free and open to the Penn State community.
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 Young Achievers Symposium
The Young Achievers Symposium highlights early career researchers in diverse fields of AI for social impact. The symposium series seeks to focus on emerging research, stimulate discussions, and initiate collaborations that can advance research in artificial intelligence for societal benefit. All events in the series are free and open to the public unless otherwise noted. Penn State students, postdoctoral scholars, and faculty with an interest in socially responsible AI applications are encouraged to attend.