Rashan Jibowu, tellic

Rashan Jibowu Rashan is a 15 year veteran of building and growing businesses by designing, building, shipping, and iterating on software products for B2C and B2B markets. Rashan is currently the Head of Product at tellic, which delivers data science technologies that drive strategic decision-making for pharma companies. Before tellic, Rashan worked in financial services where he led product strategy and execution for a new breed of intelligent consumer products. Throughout his career, he has built and led cross-functional teams of product managers, data scientists, engineers, and designers to re-imagine the future of financial services, music, social networking, and impact investing.

Rashan brings a human-centered approach to product design and leverages his business background and data science and software engineering skills to ensure that his teams are delivering the right product to solve important customer problems.


4:30 PM - 5:00 PM

Innovation Spotlight ChangeMaker Presentations

How much can you learn in five minutes? Quite a bit. Hear quick hitting presentations on the latest products, new releases, exciting innovations, and more. Each presenter will speak for 5 minutes and then will be available to answer questions during the reception.

David Wild, Ph.D. — Knowledge Graphs: A Transformative New Approach for Drug Discovery
  • Knowledge Graphs (KGs) are a transformative new way to think about drug discovery data
  • KG-based tools open up powerful new scientific and decision-making capabilities
Paul Courtney — Applications of Machine Learning in Clinical Data Management

Rashan Jibowu — Driving Strategic Decisions with Machine Learning

Leila Pirhaji, Ph.D. — AI-Driven Drug Discovery via Metabolomics
  • Metabolomics, or studying small molecules, are essential for discovering the right therapeutics for the right patients
  • How AI can contribute to characterizing a large number of metabolites, or small molecules, inexpensively and fast
Wayne R. Danter, MD — DeepNEU: Cellular Reprograming Comes of Age–a Machine Learning Platform with Application to Rare Diseases Research
  • Stem cell research will inevitably be transformed by computer technologies. The results of the initial DeepNEU project indicate that currently available stem cell data, computer software and hardware are sufficient to generate basic artificially induced pluripotent stem cells (aiPSC)
  • The application of this computer technology to generate disease specific aiPSCs has the potential to improve 1. disease modeling, 2. rapid prototyping of wet lab experiments, 3. grant application writing and 4. specific biomarker identification in a highly cost-effective manner



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