Educator/Scientist/Entrepreneur

Pradeep R.

AWS

I bring hands-on experience with AWS cloud technologies through my work developing and deploying scalable systems for healthcare data analysis, including AI-based medical coding applications that processed thousands of records in real-time environments. As a technology leader, I've architected cloud solutions leveraging AWS services including EC2, S3, Lambda, DynamoDB, and various machine learning offerings to build scalable, secure, and cost-effective applications for both startup and enterprise environments. My expertise spans the full AWS implementation lifecycle—from initial architecture design and infrastructure-as-code deployment to performance optimization, security implementation, and cost management strategies for production workloads. I emphasize a practical approach to teaching AWS concepts, helping students understand not just individual services but how to integrate them into comprehensive cloud solutions that address real business needs while following AWS best practices and architectural patterns.

Biostatistics

My experience in biostatistics includes leading AI-based medical coding algorithm development for Alzheimer's research, where I designed statistical models that transformed data analysis workflows and supported research that secured $70 million in funding. As a computational scientist who worked at both USC's Alzheimer's Therapeutic Research Institute and The Scripps Research Institute, I've applied sophisticated statistical methods to analyze complex biomedical datasets, develop predictive models, and interpret clinical research findings across multiple therapeutic areas. My background in scientific software development includes creating tools for data analysis that have been published in peer-reviewed journals and presented at international conferences, demonstrating my ability to bridge statistical theory with practical applications in healthcare and life sciences. I excel at explaining complex statistical concepts through relevant biomedical examples, helping students understand not just the mathematical foundations but also the contextual interpretation of statistical results in clinical and research settings.

Business

I bring a unique blend of business leadership and technical expertise, having founded two companies, where I increased business valuation 8-fold in just two years through strategic planning and operational excellence. My MBA from UC San Diego's Rady School of Management complements my technical background, giving me a comprehensive understanding of business fundamentals from financial planning and market positioning to team leadership and organizational growth. As a Chief Executive Officer and former Chief Technology Officer, I've successfully secured significant funding, including a 1 million Euro grant, by developing compelling business cases and demonstrating clear value propositions to stakeholders and investors. My hands-on experience implementing Lean methodologies to streamline operations and leading multidisciplinary teams provides me with practical insights into business management that I translate into actionable strategies for students interested in entrepreneurship and business development.

Career Development

I combine my experience as a tech entrepreneur, CTO, and CEO with extensive expertise in leading diverse teams and navigating career transitions across multiple industries and roles. Having successfully built my own company and served in executive positions at several organizations, I bring practical insights on career advancement, leadership development, and professional growth strategies that go beyond theoretical concepts. My background in both technical disciplines (PhD in computational chemistry) and business management (MBA from UC San Diego) gives me a unique perspective on bridging technical expertise with business acumen to help professionals develop comprehensive career paths. I've mentored teams of engineers and scientists, helping them maximize their potential while developing the soft skills necessary for career advancement in competitive environments.

Computer Science

I bring extensive experience in computer science as both a practitioner and educator, having developed software tools like AutoSite and AutoDockFR that have garnered over 500 academic citations for computational applications. My technical background spans AI algorithm implementation, programming across multiple languages, and leading engineering teams that developed innovative solutions in autonomous vehicles and healthcare informatics. As the founder two companies, I combine theoretical knowledge from my PhD research with practical industry applications, allowing me to teach computer science concepts through relevant, real-world examples that demonstrate both the "how" and "why" of computational thinking. My teaching approach emphasizes problem decomposition, algorithm development, and programming fundamentals while connecting abstract concepts to tangible applications that have transformed industries.

Data Analysis

I bring extensive expertise in data analysis through my work at prestigious research institutions including USC's Alzheimer's Therapeutic Research Institute and The Scripps Research Institute, where I developed sophisticated analysis methodologies for complex biomedical datasets. My experience includes designing and implementing AI-based data analysis algorithms that transformed medical coding efficiency from days to hours, demonstrating my ability to extract actionable insights from large, complex datasets while ensuring statistical rigor and validity. As a computational scientist who has published and presented research findings at international conferences, I've developed and applied diverse analytical approaches—from statistical modeling and pattern recognition to predictive analytics and visualization techniques—across healthcare, pharmaceutical development, and technological domains. My teaching approach emphasizes not just technical analysis methods but also critical thinking about data quality, appropriate methodology selection, and effective communication of findings, ensuring students develop comprehensive data analysis capabilities applicable across industries.

Data Science

I bring extensive experience in data science through my work developing AI-based medical coding algorithms that transformed workflow efficiency and implementing sophisticated data analysis systems for Alzheimer's research that secured $70 million in grant funding. My academic background combines a PhD in computational science with a Master's in Informatics from the University of Edinburgh, specializing in artificial intelligence and machine learning techniques that I've applied across healthcare, pharmaceutical research, and autonomous vehicle domains. As a former CTO who led teams developing data-intensive calibration technologies, I excel at teaching the full data science pipeline—from data collection and preprocessing to model development, evaluation, and deployment—while emphasizing both the technical fundamentals and the strategic business applications of data science. My teaching approach bridges theory and practice, helping students develop the analytical thinking and programming skills needed to extract meaningful insights from complex datasets.

Information Technology

I bring comprehensive information technology expertise spanning infrastructure design, systems integration, and enterprise architecture, having led technical operations for organizations including USC's Alzheimer's Research Institute and my own technology venture. My experience includes developing and implementing electronic data capture systems and AI-based solutions that transformed healthcare data workflows, demonstrating my ability to architect end-to-end IT solutions that address complex business challenges. As a former CTO who oversaw IoT network development for sensor calibration technology, I've worked extensively with diverse IT systems from cloud infrastructure and database management to network design and information security protocols. My technical background combined with business leadership experience enables me to teach information technology concepts with an emphasis on both technical fundamentals and strategic business alignment, helping students understand how IT systems support organizational objectives across industries.

Machine Learning/ AI

I bring extensive expertise in machine learning and AI through both academic research and industry applications, having specialized in AI during my MSc at the University of Edinburgh and implemented advanced algorithms across healthcare, computational chemistry, and autonomous vehicle domains. As the former CTO of Curium, I led teams developing sophisticated AI-driven sensor calibration systems for autonomous vehicles that reduced processing time from hours to minutes, demonstrating my ability to apply theoretical ML concepts to solve complex real-world problems. My work in AI includes developing predictive algorithms for medical coding that achieved 60% adoption in their first year and creating computational tools that have been cited in over 500 scientific publications, giving me practical insights into the full ML development lifecycle from data preparation and model selection to deployment and evaluation. I excel at demystifying complex AI concepts through tangible examples, helping students understand both the mathematical foundations and practical implementation considerations that bridge the gap between theoretical machine learning and production-ready AI systems.

Python

I bring extensive experience in data science through my work developing AI-based medical coding algorithms that transformed workflow efficiency and implementing sophisticated data analysis systems for Alzheimer's research that secured $70 million in grant funding. My academic background combines a PhD in computational science with a Master's in Informatics from the University of Edinburgh, specializing in artificial intelligence and machine learning techniques that I've applied across healthcare, pharmaceutical research, and autonomous vehicle domains. As a former CTO who led teams developing data-intensive calibration technologies, I excel at teaching the full data science pipeline—from data collection and preprocessing to model development, evaluation, and deployment—while emphasizing both the technical fundamentals and the strategic business applications of data science. My teaching approach bridges theory and practice, helping students develop the analytical thinking and programming skills needed to extract meaningful insights from complex datasets.