Driving innovation at the intersection of technology and impact.
The Data Engineering and Predictive Analytics Lab (DEPA Lab) at Morgan State University, led by Dr. Kofi Nyarko, is dedicated to unraveling the intricacies of complex systems and providing transformative insights. DEPA Lab focuses on applied research in Computer Vision, Machine Learning, and Artificial Intelligence Techniques.
We develop innovative machine learning models and algorithms for near real-time data collection, transformation, analysis, prediction, and visualization. DEPA Lab promotes inclusivity and innovation in data engineering and predictive analytics.
The Center for Equitable AI and Machine Learning Systems (CEAMLS) facilitates the development and deployment of socially responsible and equitable AI systems, ensuring they benefit everyone while educating the public about their impacts on health, prosperity, and happiness.
Analyze and visualize complex IoT networks for actionable insights.
Secure networks through advanced analytics and visualization techniques.
Optimize algorithms for real-world decision support and autonomous systems.
Automating traffic data analysis, pose estimation, and scene perception for diverse applications.
Advancing trustworthy and unbiased AI systems while addressing algorithmic bias.
Creating interactive visualization tools for enhanced situational awareness.
Developing robust algorithms for real-time navigation in challenging environments.
At DEPA Research Lab, we are at the forefront of cutting-edge research, solving complex real-world challenges through interdisciplinary approaches. Explore some of our groundbreaking projects:
Developing an AI-powered tool to evaluate student comprehension by analyzing essays and generating quizzes in Canvas QTI/XML format, ensuring meaningful learning over AI-assisted responses.
Learn MoreAssessing leading LLMs for their ability to generate dialect-specific text while maintaining semantic consistency, sentiment alignment, and reducing bias in AI-driven linguistic diversity.
Learn MoreUtilizing real-time segmentation techniques within the SAM framework to improve navigation for wheelchair users by accurately identifying traversable surfaces in diverse environments.
Learn MoreA benchmarking framework for evaluating cloud-based and open-source ML services across tasks like object detection and facial recognition, promoting transparency and efficiency in AI service selection.
Learn MoreIntegrating Generative AI into an academic advisory system to provide instant, AI-driven responses on course details, degree programs, and graduation requirements for student support.
Learn MoreDeveloping a scalable system that allows data analysts to execute SQL-like queries on video content without deep computer vision expertise, bridging AI with real-world applications.
Learn MoreThe CLAIRE (Cross-Referencing Labels, Actions, and Interactions for Robust Explanations) project aims to integrate YOLO detections and LLM vision to analyze video frames.
Learn MoreThis research utilizes advanced machine learning techniques to detect cracks and structural anomalies in materials under stress.
Learn MoreThis research utilizes edge computing and CAD modeling to develop real-time, on-device decision-making and innovative robotic solutions. By optimizing navigation algorithms and overcoming physical design limitations, it advances the capabilities of autonomous systems in complex, real-world environments.
Learn MoreThis research explores cutting-edge approaches to enhance the ability to track individuals across video frames accurately and consistently.
Learn MoreStay updated with the latest happenings, publications, and events at DEPA Research Lab.
DEPA Lab has been recognized for its groundbreaking research on equitable AI systems, fostering innovation in AI ethics and shaping policy frameworks for a fairer, more inclusive future.
Read MoreDEPA Lab has made significant strides in advancing equitable AI systems, presenting groundbreaking research that addresses fairness, inclusivity, and transparency in artificial intelligence.
Read MoreJoin DEPA at the CEAMLS Symposium as we delve into groundbreaking advancements in machine learning and AI. This annual event showcases DEPA's commitment to driving progress in AI and ML technologies.
Read MoreOur diverse and talented team is committed to advancing research and innovation, solving real-world problems through technology.
Email: kofi.nyarko@morgan.edu
Address: Room 112 and 113 Schaefer Engineering Building, School of Engineering, 1700 E Cold Spring Ln, Baltimore, MD 21251