Dr. Kofi Nyarko is a tenured Professor in the Department of Electrical and Computer Engineering at Morgan State University, a premier HBCU and R2 research institution. He is the founding Director of the Center for Equitable Artificial Intelligence and Machine Learning Systems (CEAMLS), a multidisciplinary research hub committed to advancing responsible and inclusive AI development. Under his leadership, CEAMLS has become nationally recognized for pioneering research, outreach, and capacity building aimed at ensuring AI technologies are designed and deployed with equity and social impact in mind.

As Director of CEAMLS, Dr. Nyarko organizes the annual International Symposium onEquitable AI, which brings together thought leaders in policy, academia, and industry. He plays an active role in state-level AI strategy as a member of the Maryland Responsible AI Council (MRAC), advising on public-sector AI deployment and data governance.

Beyond research and policy, Dr. Nyarko is committed to education and workforce development. He has developed inclusive AI curricula at the undergraduate and graduate levels, co-leads the Summer AI Research Institute for high school teachers and undergraduate students, and supports cross-institutional mentoring through private and public funding initiatives.

Dr. Nyarko is the recipient of the 2020 US Black Engineer HBCU STEM Innovation Award, honoring his contributions to STEM innovation and institutional development. A frequent speaker, evaluator, and consultant, he has presented nationally on AI ethics, autonomous systems, and equity in technology innovation. He continues to serve as a mentor, advocate, and trailblazer in creating pathways for underrepresented scholars in AI and data science.

Dr. Nyarko also directs the Data Engineering and Predictive Analytics (DEPA) Research Lab, where his research spans computer vision, neurosymbolic machine learning, multimodal AI, and generative models. His work bridges fundamental research and real-world application, including the use of AI in unmanned aerial and ground systems for remote sensing, autonomous navigation, infrastructure monitoring, and traffic coordination. He has also contributed to advancements in visible light communication and biologically inspired optimization, earning three U.S. patents in those areas.

A core aspect of Dr. Nyarko’s research portfolio is developing AI tools that enhance decision-making under uncertainty. He is currently advancing efforts in neurosymbolic AI frameworks that integrate probabilistic reasoning with symbolic representations to support robotic autonomy, explainability, and real-time response in dynamic environments. He also leads or contributes to projects funded by NSF, NIH, and DoD, including efforts to assess AI fairness, measure cultural representation in foundation models, and evaluate responsible AI integration in digital infrastructure for underserved communities.

Gabriella Waters is an artificial intelligence and machine learning researcher who serves as the Director of Operations and the Director of the Cognitive and Neurodiversity AI Lab (CoNA) at the Center for Equitable AI & Machine Learning Systems at Morgan State University in Baltimore, MD. She is a founding member of the Maryland Responsible AI Council and an AI policy advisor at state, federal, and international levels. Gabriella has served as a research associate at NIST in the AI Innovation Lab, where she led AI testing and evaluation efforts for the ARIA project.

Gabriella is committed to increasing the diversity of thought in technology and advocates for interdisciplinary collaborations to advance innovation, responsibility, explainability, transparency, and ethics in AI development and application. Her research explores the intersections of human neurobiology & learning, the quantification of ethics in AI/ML systems, neuro-symbolic architectures, and the design of intelligent systems that leverage these foundations for enhanced human-computer synergy. She is especially focused on developing technological innovations that support neurodiverse populations.

Tim Finin is the Willard and Lillian Hackerman Chair in Engineering, the Director of the UMBC Center for Artificial Intelligence, and a Computer Science and Electrical Engineering professor at the University of Maryland, Baltimore County (UMBC). He has over 50 years of experience applying AI to problems in information systems and language understanding. His current research focuses on representing and reasoning with knowledge graphs, analyzing and extracting information from text, and enhancing security and privacy in information systems. He is an ACM fellow, an AAAI fellow, and an IEEE technical achievement award recipient. He was selected as the UMBC Presidential Research Professor in 2012. Finin received an S.B. degree in Electrical Engineering from MIT and a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. He has held positions at UMBC, Unisys, the University of Pennsylvania, Johns Hopkins University, and the MIT AI Laboratory. He has chaired the UMBC Computer Science department, served on the Computing Research Association board of directors, been a AAAI councilor, and chaired many major research conferences. He is a former editor-in-chief of the Elsevier Journal of Web Semantics.

Julia is a Professor Emerita at New York University’s NYU Wagner Graduate School of Public Service. She is known for creating or co-founding a number of public data infrastructures. She initiated and co-founded the Census Bureau’s Longitudinal Employer-Household Dynamics program, as well as the STAR METRICS/UMETRICS program at the Institute for Research on Innovation and Science , Statistics New Zealand’s Integrated Data Infrastructure, USPTO’s Patentsview. She founded the not for profit company, the Coleridge Initiative. She also has created data access infrastructures: the Remote Data Access Enclave at NORC at the University of Chicago, the Administrative Data Research Facility at NYU and then the Coleridge Initiative. She developed the Applied Data Analytics training program at the Coleridge Initiative and the Executive Certificate in Data Literacy and Evidence Building at NYU and the University of Maryland. She is currently working with a number of scientific and statistical agencies on the Democratizing Data project. She has authored over 80 scientific publications, edited or coauthored 13 books, and received over $180 million in grants and contracts from national and international agencies and foundations.

Public Service

Julia was a senior advisor in the Office of the Federal CIO at the White House, supporting the implementation of the Federal Data Strategy. She recently served on the Advisory Committee on Data for Evidence Building and the National AI Research Resources Task Force. Julia currently serves on the Secretary of Labor’s Workforce Innovation Advisory Committee and the National Science Foundation’s Advisory Committee on Cyberinfrastructure.

She holds a PhD in Economics and an MA in Statistics.

Awards

Julia is an elected fellow of the National Academy of Public Administration, the American Association for the Advancement of Science, the International Statistical Institute and the American Statistical Association. She is the recipient of the 2004 Vladimir Chavrid award from the National Association of State Workforce Agencies as well the 2014 Julius Shiskin award and the 2014 Roger Herriot award from the American Statistical Association and the 2019 LEHD Founders award from the Census Bureau for establishing the LEHD program. She is also the recipient of the 2017 Warren E. Miller Award and the 2019 Distinguished Fellow award from the New Zealand Association of Economists.

Dr. Peter Viechnicki is a pioneer in the development of capabilities and the management of personnel in the areas of natural language processing, machine learning, and data science techniques. Dr. Viechnicki began his career in the Federal Government, where he helped government agencies solve some of their hardest human language technology problems. During his stint in the private sector, Dr. Viechnicki built NLP systems and managed the efforts of the research teams and system integration. Some of his notable projects include applying text classification to 1.5 billion emails to enable highly efficient response to information requests and developing a multilingual fuzzy biographic search tool for decision support. Dr. Viechnicki has received numerous citations during his career, including the Distinguished Civilian Service Award. Peter received his doctorate in Linguistics from the University of Chicago, specializing in Phonetics and Phonology under Howard Nusbaum, Karen Landahl, and Ken De Jong. His dissertation demonstrated a new experimental paradigm for measuring flexibility during vowel production.

Kevin T. Wynne, Ph.D., is an Associate Professor of Management in the Merrick School of Business at the University of Baltimore. Dr. Wynne teaches university courses on organizational behavior, leadership, HR, and AI. He also conducts research relating to various workplace phenomena. The overarching goal of his research is to enhance employee well-being and effectiveness. His interests fall into three primary domains: a) human-AI collaboration, b) supportive leadership, and c) the work-nonwork interface.

Previously, Dr. Wynne was a postdoctoral research fellow at the U.S. Air Force Research Laboratory in Dayton, OH (Wright-Patterson Air Force Base), serving the Human Insight & Trust Team, RXHS (Human Interaction & Trust) Branch (Airman Systems Directorate, 711 Human Performance Wing), where he conducted research on human-machine teaming. He has prior industry and external consulting experience, particularly in the areas of assessment, selection, data analysis, applied research, and talent management. Dr. Wynne conducted applied research and developed interactive assessments in Testing and Assessment Design (R&D) at Development Dimensions International (DDI) in Pittsburgh, and then subsequently was an HR selection/testing consultant with APTMetrics at their Chicago field office. Prior to joining DDI, Dr. Wynne worked in Talent Development at Sodexo North America, and in Organization and Leadership Development at Lockheed Martin Aeronautics in Fort Worth, TX. Dr. Wynne earned his PhD in industrial/organizational psychology from Wayne State University.

Dr. Wynne earned his PhD in industrial/organizational psychology from Wayne State University. Dr. Wynne graduated Cum Laude with a BA in psychology from The Ohio State University, and he holds master’s degrees from Wayne State University and Mays Business School at Texas A&M University.

Sherif Elsafty is the Founder and CEO of VisionEighty Consulting LLC, specializing in AI and machine learning implementations across industries. With a M.S. in Engineering Management from the University of Maryland, Baltimore County, and executive education from MIT Sloan School of Management, he brings extensive experience in AI, data science, systems engineering, strategy, and project management.

His work spans the AI implementation lifecycle—from strategy to delivery—helping organizations integrate AI while maintaining responsible practices. He is particularly interested in developing practical responsible AI frameworks and robust AI governance models that can be applied across sectors.

He is an Adjunct Professor at Capitol Technology University and University of Maryland, Baltimore County. On the Maryland Responsible AI Council, he contributes expertise to help shape Maryland’s responsible AI future.

A results-driven seasoned IT professional with extensive experience across various industries, delivering high-performance infrastructures and innovative solutions at leading organizations. Expertise in designing and implementing cost-effective, scalable IT architectures and applications to solve complex business challenges. Proven track record in developing policies, overseeing the complete project lifecycle—from feasibility and conceptual design to deployment, user training, and continuous improvement.

Currently serving as Department Chair and Adjunct Professor in Computer and Data Science, bringing industry knowledge into academia to shape future leaders in technology. Actively involved in curriculum development, leading academic programs, and mentoring students in AI, data science, and computer science.

A dynamic leader with strong global project management expertise, adept at building, transforming, and leading creative, highly organized teams. Known for delivering projects on time and within budget while driving innovation and operational excellence.

Specialties:
– Ph.D. in Business Analytics & Decision Sciences, MS in Computer Science, MBA, and MIM
– Certified Project Management Professional (PMP)
– Certified Information Systems Auditor (CISA)
– Six Sigma Green Belt Certification
– IT Organization & Management
– Technical Project & Operations Management
– IT Architecture & Integration
– Academic Leadership & Curriculum Development
– Mentorship and Student Development in AI and Data Science

Dr. Raff is the Director of Emerging AI at Booz Allen Hamilton, where he leads the firm’s machine learning research group. His work involves government and commercial needs that cannot be satisfied by existing solutions, requiring domain understanding combined with technical insight and invention. Dealing with problems in healthcare, finance, cybersecurity, and national security, these issues often involve active and motivated adversaries who seek to subvert or compromise solutions, making robustness and security in solutions a requirement for efficacy. Dr. Raff’s work has led to over 125 peer-reviewed articles, six Best Paper awards, and elevation to Senior Member status in the IEEE and AAAI professional communities.