Simplilearn
Leadership Council

Vijayanand Rajandram is a data and AI leader with over 25 years of experience in digital transformation and data strategy across Fortune 500 companies, startups, and consulting firms. Recognized among North America’s Top 100 leaders in Data and AI, he has held multiple Chief Data and Analytics Officer roles and is currently the Chief Data Officer at Northern Trust Asset Management. He is also engaged in education through Data That Matters LLC and serves on the advisory board of the STEM Academy of Innovation and Leadership. He holds a Ph.D. from Queen Mary College, University of London.

Chester Ismay is a data science and AI expert with experience across academia and industry. He has served as visiting faculty at leading universities in the U.S. and Canada and led enterprise AI initiatives as an ML Evangelist at DataRobot, with prior experience as a business analytics consultant at Promontory Financial Group (IBM). He is the co-author of Statistical Inference via Data Science (ModernDive), a contributor to the widely used infer R package, and a former Board Member of the R Consortium. His work focuses on Generative AI, large language models, and MLOps, with an emphasis on scalable, real-world applications. He holds a Ph.D. from Arizona State University.

Brandon Keith Vaughn is an AI and data science expert with over 22 years of consulting experience across industries. He has held hands-on roles at organizations including Dell Technologies and has served as an Assistant Professor at the University of Texas. He currently leads AI and machine learning initiatives as a Senior Data Scientist, supporting large-scale analytics programs. He holds Ph.D. degrees from Florida State University and the University of West Florida.

David Pazmino is a Machine Learning Engineer and AI specialist with experience across leading financial institutions, including JPMorgan, BNY Mellon, Genpact, Invesco, and Goldman Sachs. He has designed and implemented enterprise-scale AI solutions, including generative AI models, NLP systems, federated learning frameworks, and anomaly detection platforms. As a course advisor, he brings deep expertise on applied AI and scalable machine learning systems to shape practical, industry-relevant learning. He holds advanced degrees from Duke University’s Fuqua School of Business and Northwestern University in predictive analytics.

Lisa Stuart is a Data Scientist at Thermo Fisher Scientific, with prior experience at Amazon, building data-driven solutions at scale. She specializes in predictive analytics, machine learning, and business intelligence. Her expertise spans Python, R, SQL, and cloud platforms such as Azure and Databricks, with a focus on data visualization, ETL processes, and advanced analytics. She holds a certification in Data Science and Big Data Analytics from the Massachusetts Institute of Technology (MIT) and is passionate about helping learners translate predictive analytics into actionable insights for data-driven decision-making.

Nikunj Nirmal is Head of Engineering for International Expansions at Amazon, where he leads global initiatives to launch Amazon in new markets, driving product strategy, technology roadmaps, and AI-led innovation. With leadership experience as a CTO and Head of Digital Transformation, he has built scalable AI and GenAI solutions to enhance customer experience and operational efficiency. He holds an MBA and MS from The University of Texas at Dallas and has a certification in Applied Generative AI for Digital Transformation from MIT. He is an active member of the industry and academia, including the Linux Foundation, Forbes, University of Texas at Dallas, and WingsForGrowth, where he contributes to discussions on technology innovation, aligning with his expertise in product lifecycle management and mentoring leaders.

Omesh Tickoo, a Senior Principal Engineer (AI) and Senior Director at Intel, leads AI strategy and technology initiatives and focuses on developing generative and agentic AI solutions at scale. He has over 60 patents and publications and has co-authored Making Sense of Sensors. He is an Adjunct Professor at Portland State University and collaborates with global universities, including MIT, Oxford, UCLA, Duke, and KU Leuven. He has also served as Chair of the Semiconductor Research Corporation's AI Hardware initiative. He equips learners with a deep understanding of the future of AI systems, enterprise AI platforms, and responsible AI governance.

Ginger Grant is a Microsoft Data Platform MVP, Microsoft Certified Trainer (MCT), and Principal Consultant at Desert Isle Group. A globally recognized keynote speaker and thought leader, she has trained professionals worldwide and helped organizations leverage AI-driven technologies to address complex business challenges and data-informed decision-making. Her expertise spans machine learning, Microsoft Fabric, Power BI, Azure Synapse Analytics, Python, analytics automation, cloud data architecture, and helping learners build practical skills through real-world AI and data applications.