Who we are

The AI in Finance and Industry Research Focus Group at Purdue Statistics brings together faculty, students, and industry collaborators interested in developing and applying modern statistical, machine learning, and artificial intelligence methods to challenging problems in finance and industry.

Our research spans two complementary areas.

AI in Finance

Modern financial markets generate increasingly complex and high-frequency data through automated and algorithmic trading. Traditional stochastic models often become difficult to use when market frictions, price impact, information effects, microstructure noise, bid-ask spreads, and other realistic market features must be incorporated simultaneously.

Our group develops both mathematical and data-driven approaches to these problems. In particular, we study how modern AI and machine learning methods—including reinforcement learning, deep learning, generative models, transformers, and related techniques—can be used for financial time-series analysis, market microstructure, trading, portfolio management, and risk analysis.

We are especially interested in research that connects rigorous statistical and mathematical foundations with practical problems arising in modern financial markets.

AI in Industry

A second major focus of our group is the rapidly growing role of AI and statistics in advanced manufacturing and industrial systems.

Modern factories and manufacturing systems generate massive amounts of data from sensors, machines, production processes, logistics networks, and quality-control systems. These data create new opportunities for statistical learning and AI to improve manufacturing efficiency, reliability, quality, and decision-making.

Our research interests include smart factories, semiconductor manufacturing, process monitoring, anomaly detection, predictive maintenance, quality control, optimization, digital twins, industrial time-series analysis, and AI-assisted manufacturing systems.

Through academia-industry collaboration, we also explore real-world industrial problems and opportunities for translating statistical and AI research into practical applications.

AI in Industry Community

Our AI in Industry activities connect statistical research, AI methodology, student learning, and engagement with the broader industrial community.

AI in Industry Study Group

We are developing an AI in Industry Study Group for Purdue students and faculty interested in understanding how artificial intelligence, machine learning, and statistics are being used in modern industrial environments.

The study group provides an informal but research-oriented forum to study recent papers and emerging technologies, discuss real-world industrial problems, and develop research ideas in areas such as semiconductor manufacturing, smart factories, process monitoring, anomaly detection, predictive maintenance, quality control, optimization, and industrial AI.

As the semiconductor and advanced manufacturing ecosystem continues to grow in the Greater Lafayette area, the study group will also help students build the statistical, computational, and domain knowledge needed to participate in future research and industry opportunities.

ASA Interest Group on Statistics for Heavy Equipment Industries (HEI)

Our industrial statistics activities are also connected with the American Statistical Association Interest Group on Statistics for Heavy Equipment Industries (HEI), an initiative led by Purdue Statistics.

The HEI Interest Group brings together statisticians, researchers, engineers, and industry professionals interested in statistical and data-driven problems arising in heavy equipment industries, including construction, agriculture, mining, transportation, manufacturing, and related sectors.

The group provides a broader professional forum for developing connections between statistical methodology and important industrial challenges, while promoting collaboration among academia, industry, and the statistical community.

Together, the AI in Industry Study Group and the HEI Interest Group provide complementary opportunities: the Purdue-based study group supports student learning, research development, and local collaboration, while the ASA HEI Interest Group connects these efforts to a broader national community of statisticians and industry professionals.