Tanping Wang

𝐀𝐈 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐚𝐧𝐝 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 • Establish enterprise-wide AI governance and compliance strategy, unifying governance, observability and risk management into a single operating framework adopted across business units and regions. • Build oversight of AI observability, instituting production monitoring for model drift, bias, and performance degradation, ensuring resilient and trustworthy AI systems at scale. • Direct global regulatory alignment efforts, embedding controls to meet GDPR, CCPA, and anticipated AI Act requirements, positioning the organization as an industry leader in responsible AI. • Champion automation through GenAI and intelligent agents, building enterprise workflows that integrate fragmented compliance information into a centralized system, significantly reducing review cycles and increasing audit readiness. • Direct high-performing engineering teams, providing transformational leadership, ensuring timely delivery, and instilling a culture of innovation and accountability. 𝐌𝐋 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 • Established an enterprise-wide automated model deployment process for Visa Consulting Services, standardizing and streamlining the end-to-end ML lifecycle—from training to production—across business units and regions, reducing fragmentation and enabling faster, more reliable AI delivery at scale. • Leveraged open-source technologies to architect a fully open-source ML platform at a global scale, supporting thousands of models across regions with cost-effective, reliable infrastructure.

• Collaborating on the quorum which developed Hadoop to a large-scale Open Source project from infancy. • Serving as one of the earliest contributors to Hadoop catalog manager, which evolved to become today’s Hive Metastore.

𝐈𝐁𝐌 𝐍𝐞𝐱𝐭 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐃𝐚𝐭𝐚 𝐋𝐚𝐤𝐞 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧, 2020 • Spearheaded, designed, and developed next-generation Data Lake solution for IBM Hybrid Cloud. • Liaised with the executive management team to define the overall product strategy for Data Lake enterprise, a strategic priority and key initiative for the IBM organization. 𝐈𝐁𝐌 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞 (𝐃𝐚𝐭𝐚𝐒𝐭𝐚𝐠𝐞), 𝐈𝐁𝐌 𝐈𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐒𝐞𝐫𝐯𝐞𝐫 𝐏𝐫𝐨𝐝𝐮𝐜𝐭, 2018 𝐭𝐨 2020 • Managed development teams across multiple product lines centered around IBM Data Engine, also known as the IBM Information Server product, part of a million dollars’ business. • Maintained responsibility for the modernization and conversion of a 20-year-old legacy data engine to a container-based engine on the IBM Hybrid Cloud data platform, including defining scope, benefits strategy, and revenue outcomes. • Supervised product strategy, architectural roadmap, project management, and product releases. • Accountable for shipping three major releases each year, in addition to monthly minor releases. • Augmented performance of development team by leading and mentoring engineers and managers. 𝐈𝐁𝐌 𝐎𝐩𝐞𝐧 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐨𝐟 𝐇𝐚𝐝𝐨𝐨𝐩 𝐚𝐧𝐝 𝐒𝐩𝐚𝐫𝐤 (𝐈𝐎𝐏), 𝐈𝐁𝐌 𝐁𝐢𝐠𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 𝐏𝐫𝐨𝐝𝐮𝐜𝐭, 2014 𝐭𝐨 2018 • Administered product delivery schedules, specification reviews, planning, budgeting, and resource allocation. • Functioned as IBM representative in ODPi (www.odpi.org), an open community under the Linux Foundation, to form standardizations for an Open Source ecosystem. • Championed the development team in contributing to Open Source projects, in addition to having mentored multiple developers from IBM to become Apache Open Source committers.

• Guided a team of developers in both US and China in building a data platform with the ability to serve segmented audiences by feeding data into Yahoo’s advertising pipeline, which fully leveraged the entire Hadoop ecosystem. • Played a key role in establishing the data platform as the primary analytics tool used by the Yahoo CEO office to analyze high-volume live events, such as presidential campaigns, the Super Bowl, and the World Cup. • Designed HDFS Data Node storage to support Hadoop 2.0 release, a complete revamp from previous Hadoop releases. • Fulfilled the design and maintenance of the Yahoo in-house Data Warehouse solution (AWACS) before Hadoop, which managed multiple petabytes of data activity daily. • Helped lead the design and implementation of a user personalization service (UPS) within Yahoo's data advertising pipeline to provide personalized data for advertisement serving.

Contributed heavily to the Microsoft Mediaroom product

Developed financial services software that processed non-exchange based trading operations for financial institutions on Wall Street and banks.

Research was focused on the methodology of streaming application that can be matched onto Intel’s dual-core and multi- core processor architecture. Developed event-driven simulations to explore the necessity of building direct hardware channel between cores on the Intel’s dual/multi-core architecture.

As part of my research work in the Ph.D. program, published adacademic conference papers on an innovative flexible parallel run-time execution model on simultaneously multithreading platform for numerical scientific applications. The run time model lies between application and OS layers. Use a programming analysis methodology to optimize the performance of the applications. Using profiling based speculative prefetching technique to maximize the best performance for scientific applications.

Built a user level Distributed Shared Memory library, DSMLib, through Java Objects. The distributed shared memory (DSM) system supports the strict consistency model and sequential consistency model.