Prior to co-founding XOKind, Arjun was a vice president in the Artificial Intelligence Products Group at Intel where he led a large AI software and research effort that spanned the United States, Israel and Poland. Arjun joined Intel after the acquisition of Nervana Systems, a company he co-founded. Nervana developed a new computational paradigm consisting of a cloud to silicon stack designed for deep learning. Nervana helped enterprises make sense of big data at scale. Arjun oversaw development of Nervana's software framework and led engagements across vertical industries, including agriculture, automotive, energy, finance, government and online services.

Before founding Nervana in 2014, Arjun worked at Qualcomm on brain-inspired computing for robotics and mobile applications. Earlier in his career, he was a postdoctoral research fellow in neurology at Harvard Medical School and Children's Hospital, focusing on cognitive experiments, computational modeling and quantitative analysis of large neurological data sets.

Arjun holds a bachelor's degree in computer science from Caltech and a Ph.D. in neuroscience from Brown. He has written more than a dozen published works on topics related to brain-machine interfaces, machine learning applied to computational neuroscience, deep learning and AI. Arjun was recently chosen as a 40 under 40 by Fortune magazine. Arjun has been invited to share his thoughts on AI and its implications for humankind at several conferences in the US, Europe and China, including Fortune Brainstorm Tech, O’Reilly AI, Re.Work, Stanford Future Fest and WebSummit, as well as Forbes publication and the Simulation show. In his free time, Arjun enjoys travel (27 countries, 25 states plus D.C. and counting!), tennis, yoga and family time in the San Diego outdoors.

Yinyin is responsible for designing and building the technology roadmap to achieve the business and technology goals of XOKind. Through her years of experience in the machine learning domain, Yinyin has collaborated with CSPs and enterprises in various verticals to apply AI/Data Science to build/deploy AI systems and services, and has always been passionate about designing and packaging the right AI algorithms to solve problems for enterprises and end-users.

Previously, Yinyin was the Head of Data Science in the Artificial Intelligence Products Group at Intel where she led a global team of deep learning researchers and data scientists that is engaged in in-depth data science for AI product engineering, as well as Natural Language Processing (NLP) and Reinforcement Learning (RL) research. She was responsible for setting the strategy and leading the execution of connecting data science and AI research with AI hardware, enabling AI use cases through open-source data science tools in NLP, RL, model compression, and working with Intel partners and customers on innovative AI solutions across industry domains. Yinyin has also driven algorithmic design for the Intel Nervana NNP-L, one of the first Deep learning training ASICs, and contributed to neon (open source DL framework) and nGraph (open source DL compiler). Yinyin represented Intel at the Partnership on AI, a multi-stakeholder organization that brings together around 100 academic, industry, and civil society organizations working on making AI beneficial for people and society. Prior to working at Intel, Yinyin was a Principal Data Scientist at Nervana Systems (acquired by Intel in 2016), where she was responsible for developing deep learning algorithms and frameworks, and AI solutions for enterprises. She also previously worked at Qualcomm Research as a ML/neuroscience researcher working on Deep Learning, Robotics and Neuromorphic computing.

Yinyin was named one of the 9 women in Silicon Valley to watch who are leading in AI by Silicon Valley Business Journal, and one of the top 30 Women in AI in US by RE.WORK. She has a Bachelor’s degree in Electrical Engineering from Northeastern University, China, and a Ph.D. focused in Machine Learning from Ohio University.

Scott has over twelve years experience creating machine learning based solutions to solve large-scale, real-world problems. Prior to co-founding XOKind, Scott was a Principal Engineer in the Artificial Intelligence Products Group at Intel where he led and managed teams building systems to support deep learning on specialized hardware. Scott joined Intel via the acquisition of Nervana Systems, where he was an early employee. At Nervana, Scott led initial architecture design and was a core contributor to Nervana’s deep learning framework neon. Scott also kicked off Nervana’s cloud efforts, building one of the world’s first deep learning as a service offerings.

Over his career, Scott has contributed award-winning models, analysis and software to support automated house price valuation, securitized asset rating, and credit card fraud detection. He's had multiple top ten finishes in the KDD Cup and Kaggle competitions on tasks ranging from author disambiguation to music preference rating. Scott is a former member of the Machine Learning group at the University of Toronto. Supervised by Sam Roweis, his research focused on ways to improve optical character recognition by exploiting contextual and language-based cues.

Outside the office, Scott enjoys travelling to far-flung destinations (21 countries so far), long distance running, and craft beer.

Sarah is passionate about positively impacting the role technology has in shaping how we live, work, think and feel. Her experience in the tech sector encompasses product management, partnerships and marketing at companies including Apple, where she focused on consumer apps on iOS, macOS and tvOS, and at HP, where she focused on enterprise hardware. Sarah holds an MBA from the Kellogg School of Management, a PhD in Media Studies from the University of California, Santa Barbara, and a bachelor’s degree in Radio, TV and Film and International Studies from Northwestern University. During her PhD and postdoctoral fellowship, she conducted Fullbright-funded international research on Internet users’ attitudes and behaviors, and investigated how online culture is shaped by industries, governments and social networks in the offline world. Her analyses have been published in blogs, journals and publications including Signal Traffic: Critical Studies of Media Infrastructure (2015). Prior to her PhD, Sarah served in the Teach for America program, teaching in the Bronx and Chicago. She also has experience in radio production and documentary filmmaking, and she’s lived and worked abroad in Turkey and Bolivia where she picked up Turkish and Spanish. In her spare time, Sarah enjoys exploring new hikes, San Diego’s beaches, music and film, and spending time with family and friends.

Prior to joining XOKind, Gabriel founded Indigo, a startup using recent advances in machine learning and neuroscience to improve education. Before that Gabriel worked at Google DeepMind as a research scientist and Google Brain as a research resident. At DeepMind, Gabriel was part of the neuroscience team where he explored ways to use artificial intelligence to augment human intelligence. At Google Brain, Gabriel was advised by Geoffrey Hinton with whom he researched methods for scaling and improving deep learning systems for vision and natural language. The research led to publications on large scale distributed neural network training and regularizations. Before joining Google, Gabriel was a researcher at the University of Montreal's LISA Lab working with Yoshua Bengio, and created one of the first batch-normalization methods for recurrent neural networks.

Gabriel holds a bachelor's degree in computer science and business from the University of Southern California. Before university, Gabriel played soccer professionally for a year with Cruzeiro’s U18 and U20 teams.

Annie is a UI/UX designer whose work spans the entire user-centered design process, from the earliest stages of user research to polished visual designs. She creates intuitive, engaging experiences that are firmly rooted in user needs.

Originally from the marketing and advertising world, Annie transitioned into the tech sector through a programming apprenticeship at a startup in Detroit, where she developed web and mobile products for small independent brands and large corporations like General Motors. While closely collaborating with designers, she built her own design acumen and perspective, and she has been working as a designer ever since, most recently at Designlab—an online design education company—and PINT, a web development agency in San Diego. Whether sketching a prototype, conducting usability tests, or honing a wireframe, she loves the collaborative and iterative process of developing impactful, elegant design solutions.

Annie holds a bachelor’s degree in Communication & Media from the University of Michigan, where she focused on cognitive science and marketing while serving as a research assistant across a variety of departments, including neuroscience, sociology and linguistics.

When she’s not designing, Annie loves traveling (16 countries so far!), baking, drawing, and exploring new restaurants and hiking spots.

Marcus is a mobile app developer who is passionate about making people’s lives easier and more productive through technology. He founded Amarok Technologies during his sophomore year at Stuyvesant High School in New York. Since then, he has developed and shipped highly rated iOS and Android apps for Amarok. Marcus also teaches mobile app development to thousands of students and professionals online and continues to expand and deliver new content. As an intern at WeWork Labs, Marcus designed, built, and deployed key consumer products and internal tools while also mentoring early stage startups on bringing their products to market. Marcus studied Computer Science at the Macaulay Honors College at Hunter College in New York. When he’s not programming, Marcus enjoys listening to audiobooks on entrepreneurship and personal growth, playing competitive video games, and exploring new neighborhoods with his dog.