Venkat Ramesh

Venkat Ramesh is a Hardware Systems Engineer in Meta's Infrastructure Org. 

As a Technical Lead in the Release-to-Production team, Venkat has been at the helm of pivotal initiatives aimed at bringing various AI/ML Accelerator, Compute and Storage platforms into the Meta fleet. His multifaceted technical background spans roles across software development, performance engineering, NPI and hardware health telemetry across hyper-scalers and hardware providers.

Deeply passionate about the topic of AI hardware resiliency, Venkat's current focus is on building tools and methodologies to enhance hardware reliability, performance and efficiencies for the rapidly evolving AI workloads and technologies.

Paolo Faraboschi

Paolo Faraboschi is a Vice President and HPE Fellow and directs the Artificial Intelligence Research Lab at Hewlett Packard Labs. Paolo has been at HP/HPE for three decades, and worked on a broad range of technologies, from embedded printer processors to exascale supercomputers. He previously led exascale computing research (2017-2020), and the hardware architecture of “The Machine” project (2014-2016), pioneered low-energy servers with HP’s project Moonshot (2010-2014), drove scalable system-level simulation research (2004-2009), and was the principal architect of a family of embedded VLIW cores (1994-2003), widely used in video SoCs and HP’s printers. Paolo is an IEEE Fellow (2014) for “contributions to embedded processor architecture and system-on-chip technology”, author of over 100 publications, 70 granted patents, and the book “Embedded Computing: a VLIW approach”. He received a Ph.D. in EECS from the University of Genoa, Italy.

Zairah Mustahsan

Zairah Mustahsan is a Staff Data Scientist at You.com, an AI chatbot for search, where she leverages her expertise in statistical and machine-learning techniques to build analytics and experimentation platforms. Previously, Zairah was a Data Scientist at IBM Research, researching Natural Language Processing (NLP) and AI Fairness topics. Zairah obtained her M.S. in Computer Science from the University of Pennsylvania, where she researched scikit-learn model performance. Her findings have since been used as guidelines for machine learning. Zairah is a regular speaker at AI conferences such as NeurIPS, AI4, AI Hardware & Edge AI Summit, and ODSC. Zairah has published her work in top AI conferences such AAAI and has over 300 citations. Aside from work, Zairah enjoys adventure sports and poetry.

Selcuk Kopru

Selcuk Kopru is Head of ML & NLP at eBay and is an experienced AI leader with proven expertise in creating and deploying cutting edge NLP and AI technologies and systems. He is experienced in developing scalable Machine Learning solutions to solve big data problems that involve text and multimodal data. He is also skilled in Python, Java, C++, Machine Translation and Pattern Recognition. Selcuk is also a strong research professional with a Doctor of Philosophy (PhD) in NLP in Computer Science from Middle East Technical University.

David Kanter

David co-founded and is the Head of MLPerf for MLCommons, the world leader in building benchmarks for AI. MLCommons is an open engineering consortium with a mission to make AI better for everyone through benchmarks and data. The foundation for MLCommons began with the MLPerf benchmarks in 2018, which rapidly scaled as a set of industry metrics to measure machine learning performance and promote transparency of machine learning techniques. In collaboration with its 125+ members, global technology providers, academics, and researchers, MLCommons is focused on collaborative engineering work that builds tools for the entire AI industry through benchmarks and metrics, public datasets, and measurements for AI Safety. Our software projects are generally available under the Apache 2.0 license and our datasets generally use CC-BY 4.0.

Nuwan Jayasena

Nuwan Jayasena is a Fellow at AMD Research, and leads a team exploring hardware support, software enablement, and application adaptation for processing in memory. His broader interests include memory system architecture, accelerator-based computing, and machine learning. Nuwan holds an M.S. and a Ph.D. in Electrical Engineering from Stanford University and a B.S. from the University of Southern California. He is an inventor of over 70 US patents, an author of over 30 peer-reviewed publications, and a Senior Member of the IEEE. Prior to AMD, Nuwan was a processor architect at Nvidia Corp. and at Stream Processors, Inc.

Lisa Cohen

Lisa Cohen is Director of Data Science for Gemini (formerly "Bard"), Google Assistant, and Search Platforms. She leads an organization of data scientists at Google, responsible for using data to create excellent user experiences across these products, and partnering closely with Product, Engineering, and User Experience Research. Formerly, Lisa was Head of Data Science and Engineering for Twitter, helping drive the strategy and direction of the Twitter product, through machine learning, metric development, experimentation and causal analyses. Before Twitter, Lisa led the Azure Customer Growth Analytics organization as part of Microsoft Cloud Data sciences. Her team was responsible for analyzing OKRs, informing data-driven decisions, and developing data science models to help customers be successful on Azure. Lisa worked at Microsoft for 17yrs, and also helped develop multiple versions of Visual Studio. She holds Bachelor and Masters degrees from Harvard in Applied Mathematics. You can follow Lisa on LinkedIn and Medium.

Helen Byrne

Helen leads the Solution Architects team at Graphcore, helping innovators build their AI solutions using Graphcore’s Intelligence Processing Units (IPUs). She has been at Graphcore for more than 5 years, previously leading AI Field Engineering and working in AI Research, working on problems in Distributed Machine Learning. Before landing in the technology industry, she worked in Investment Banking. Her background is in Mathematics and she has a MSc in Artificial Intelligence.