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Center for Applied AI and Business Analytics Faculty Expertise

Through their research, teaching and partnership with leading organizations, Drexel LeBow faculty contribute expertise and insight to academic and business communities — harnessing the power of AI and analytics to address challenges, equip organizations for business growth and prepare the workforce for a technology-driven future.

Daniel Albert, PhD
Assistant Professor of Management

Albert’s work focuses on AI’s intersection with strategic management and organizational development:

  1. Augmenting Decision-Making with AI
    Exploring the transformative impact of large language models (LLMs) on strategic decision processes and information analysis.

  2. Navigating AI Fear in Organizations
    Tackling AI-related apprehensions in the workplace by demystifying the technology and showcasing its potential for enhancing team and individual performance

  3. Strategic Integration of AI for Competitive Advantage
    Addressing the strategic challenges of leveraging AI within organizations for competitive advantage — using AI to create unique, innovative applications that add more value than what competitors achieve with similar technologies.

Murugan Anandarajan, PhD
Professor of Decision Sciences and MIS

Anandarajan’s expertise centers on the influence of technology on business decision making:

  1. Activating Unstructured Data
    Identifying and analyzing unstructured data sources, such as text, audio and images, to interpret and derive insights that can propel growth and accelerate business value

  2. Designing and Optimizing Data Governance Processes
    Creating custom data governance frameworks, policies and strategies to align with and support organizational objectives

  3. Assessing AI Readiness
    Evaluating organizations’ AI and analytics proficiencies — measuring their preparedness to integrate technologies across business operations and strategic initiatives

Orakwue Arinze, PhD
Professor of Decision Sciences and MIS

Arinze’s work combines the use of AI, machine learning and analytics in consumer marketing and retail:

  1. Integration of AI in Consumer Marketing
    Leveraging machine learning and analytics to enhance traditional strategies and deepen insights into consumer behavior

  2. Machine Learning in Retail Optimization
    Analyzing historical data and market trends to help retailers make informed and optimized decisions across pricing, product assortment and supply chain management

  3. Data-Driven Strategies for Market Competitiveness
    Equipping companies with insights into market trends, competitor behaviors and consumer sentiment to enable data-driven decision-making and resource optimization

Hande Benson, PhD
Professor of Decision Sciences and MIS

Benson’s work focuses on computational machine learning and ML-based decision making for organizations:

  1. Faster and scalable machine learning
    Designing and building state-of-the-art machine learning solutions that can help organizations gain insights at the speed they need.

  2. Machine Learning-based Decision Making for the Public Sector
    Collecting and analyzing public and private data and aiding nonprofit and government decision-makers convert these insights into actionable decisions.

  3. Portfolio Optimization and Management with AI/ML
    Combining traditional and state-of-the-art models for financial portfolio optimization with deep learning techniques to lower risk and increase expected returns.

Oliver Schaer, PhD
Assistant Professor of Decision Sciences and MIS

Schaer works on developing predictive decision tools to create organizational value. Specifically, his work focuses on:

  1. Overcoming Organizational Silos
    Aligning short- and long-term forecasts to allow business units to seamlessly share and translate information at all decision levels

  2. Reducing Judgmental Bias
    Developing data-driven tools so demand planners can make more informed and less biased decisions

  3. Improving Forecasting Methods
    Leveraging traditional methods with unstructured public data to improve forecasts or gain competitive intelligence

Connect with Us

Diana Jones

Executive Director, Center for Applied AI and Business Analytics, Dornsife Office for Experiential Learning

(215) 571-3545

Gerri C. LeBow Hall 1230