Sergei Yakneen

Isomorphic Labs is an Alphabet digital biology company that has been spun out of Google DeepMind to reimagine drug discovery from first principles with AI. As part of the founding team I have contributed to building this company from the ground up. I'm responsible for leading all aspects of company computational Research and Development which includes groups focusing on Machine Learning Research, Computational Biology, Computational Physics, Product Management, Engineering, Data, Program Delivery, and Information Security. Together we are building an unprecedented AI platform for computational drug discovery. My role spans leading a diverse and multi-disciplinary organisation to build and deliver an incredibly ambitious scientific research program at the intersection of AI, physics, chemistry and biology, transform research outcomes into a comprehensive product vision, then engineer this vision into reality in a robust, secure, scalable, fit-for-purpose manner.

Senior member of the Executive Team, responsible for company Engineering, Product Management, PMO, Operations, IT, and Services. Managing a department of >100 technical staff. Leading the development and operation of a portfolio of cutting-edge products in the precision-medicine space, including a flagship globally distributed AI platform used to connect over 1000 healthcare institutions worldwide to provide genomic, imaging, and clinical analysis of profiles of over 1 million patients with cancer and rare disease. Defined product vision, led development and launched innovative AI-based Software as a Medical Device products in biopharma and clinical spaces. Developed, and executed multi-year technology strategy including large-scale machine learning, continuous delivery, infrastructure self-healing and serverless computing. Grew staff by over 130% across 5 locations in US, Switzerland, and France. Fostered a culture of innovation, technological and scientific excellence, continuous education and free exchange of ideas by launching a program of interconnected seminars, workshops, talks, hackathons, and off-sites to bring together employees with computational, life science, and other skillsets. Developed a strong and empowered senior management team centered around agency, accountability, operational excellence, and customer obsession. Developed and executed a comprehensive continuous improvement program built on a foundation of KPIs covering product, process and people and encouraging data-driven decision making within the organization. Collaborated on research projects with leading healthcare institutions worldwide. Ensured company operation and certification according to strict standards, including ISO 27001, ISO 13485, ISO 62304, CLIA.

Researcher in the Pan Cancer Analysis of Whole Genomes Germline Analysis Working Group. Focusing on the analysis of a large scale data set of normal tissue DNA from over 2800 cancer patients in order to assess relationship between germline genetic variation and various molecular phenotypes observed in cancer. Author of the Butler framework – a highly successful suite of tools for the analysis of large-scale scientific data sets in cloud computing environments. Used on over 10 different clouds to analyze multiple petabytes of genomic data. Manuscript in press at Nature Biotechnology. Author of the Rheos framework - a suite of bioinformatics algorithms for analysis of large-scale genomic data sets in cloud computing environments, including Amazon Web Services and OpenStack. The framework utilizes a previously unexplored stream-based approach for processing genomic read data in a manner that is optimized for application runtime and scalability on commodity hardware. Leader of the Life Sciences Demonstrator of the European Open Science Cloud Pilot project, bringing together distributed cloud infrastructures to deliver large-scale genomics analyses to improve personalized medicine in Europe.

Led the Technical Working Group of the Pan Cancer Analysis of Whole Genomes Project - world's largest cancer data analysis initiative. Liaised with stakeholders from over 20 research organizations to deliver the management and analysis of a 750 TB data set consisting of whole genome sequences of over 2700 cancer patients across 12 tumour types. Managed technical teams at 7 cloud and high performance computing environments throughout the globe through various stages of project delivery. Managed the development of the technical architecture for high performance large scale genomic data processing in computing environments such as the Amazon Web Services, Google Compute Engine, Openstack, and Sun Grid Engine. Oversaw the operational management of a globally distributed computing cluster with over 6000 cores, 14 TB RAM, and 5 PB of storage. Contributed to the development of pipelines for infrastructure management, data ingestion, quality control, genomic alignment, and germline and somatic variant calling.

Managed the building and operation of an Amazon Software Development Center in Mississauga, Ontario. Led the development of several large scale cloud-based distributed systems within the Amazon Fulfillment Technologies organization including a Lean Manufacturing platform, Labour Flow software, Stowing software, integration with Kiva Systems' Warehouse Management System, and Picking Optimization software.

Led the Product Development team through several releases of the BPS Enterprise Risk Management platform. Led the Professional Services team through several high profile engagements with world leading organizations (Canadian Pacific Railway, DTCC, Dominion Resources, Morgan Stanley)