A full-stack developer with two decades of industry experience, Jon Peck now focuses on bringing scalable, discoverable, and secure machine-learning microservices to developers across a wide variety of platforms via Algorithmia.com.
Rangan Sukumar is a Senior Analytics Architect in the CTO’s office at Cray Inc. His role is three-fold: (i) Analytics evangelist - Demonstrating what Big Data and HPC can do for data-centric organizations, (ii) Technology visionary - Designing the roadmap for analytic products through evaluation of customer requirements and aligning them with emerging hardware and software technologies, (iii) Solutions architect - Creating bleeding-edge solutions for scientific and enterprise problems in the long-tail of the Big Data market requiring scale and performance beyond what cloud computing offers. Before his role at Cray, he served as a group leader, data scientist and artificial intelligence/machine learning researcher scaling algorithms on unique super-computing infrastructures at the Oak Ridge National Laboratory. He has over 70 publications in areas of disparate data collection, organization, processing, integration, fusion, analysis and inference - applied to a wide variety of domains such as healthcare, social network analysis, electric grid modernization and public policy informatics.
Manager of AI Instruments
Chris came from a Physics background from Caltech and UCSC, and is now leading Stitch Fix's AI Instruments team. He has an avid interest in NLP, has dabbled in deep learning, variational methods, and Gaussian Processes. He's contributed to the Chainer Deep learning library (http://chainer.org/), the super-fast Barnes-Hut version of t-SNE to scikit-learn (http://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html) and written (one of the few!) sparse tensor factorization libraries in Python (https://github.com/stitchfix/ntflib).
Zhenliang Zhang is a staff engineer at Alibaba iDST. He is an adjunct professor in the Department of Electrical Engineering, Columbia University. Previously, he was a staff research scientist at Intel Labs. He was a senior engineer in Qualcomm Corporate R&D, New Jersey Reseach Center. He was a visiting professor in Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. Zhenliang Zhang's research interests are primarily in the areas of machine learning, signal processing, optimization, and network science. He has published over 30 peer-reviewed papers and held 6 US patents. He is an associate editor of IEEE Access.
Machine Learning Engineer
Arthur Juliani works at Unity Technologies as a Machine Learning Engineer and Scientist, leading the development of the ML-Agents toolkit.
Tencent AI Lab
Dr. Dong Yu is an IEEE Fellow and an ACM Distinguished Scientist. He currently serves as a distinguished scientist and vice general manager at Tencent AI Lab. Before joining Tencent, he was a principal researcher at Microsoft Research, where he joined in 1998. His research has been focusing on speech recognition and other applications of machine learning techniques. He has published two monographs and more than 160 papers in these areas and is the inventor/coinventor of 50+/10+ granted/pending patents. His works have been cited for 15k+ times with an h-index of 55+ per Google Scholar, and have been recognized by the prestigious IEEE Signal Processing Society 2013 and 2016 best paper award and the ACMSE 2005 best paper award.
Tech Lead at Twitter.
Nick studied computer science at Purdue University and the University of Southern California, and was a high performance computing consultant for Hewlett-Packard in Grenoble, France. He now specializes in machine learning and interacting with other data scientists of various communities, startups, and enterprises in order to help them succeed on IBM's data science platform.
Tony leads the reinforcement learning research within Didi Research, with applications to Didi’s core business areas. He holds a Ph.D. degree in Operations Research from Columbia University and B.Sc. in Computer Science and Statistics from UBC Vancouver.
Xiangang Li's main research area is speech recognition (especially acoustic modeling), deep learning and speech synthesis. In 2013, he led his team built the most natural speech synthesis system in the Blizzard Challenge. Before he join DIDI, he worked as the tech leader of BAIDU speech recognition, and help developing end-to-end speech recognition systems DeepSpeech 2. In DIDI, his and his team’s recently work includes helping in shipping the human-machine speech interaction system in vehicle, and developing the industry-scale attention-based end-to-end speech recognition system.
CTO of BlitzMetrics.
Principal AI Researcher
Liang Zhang is currently a Principal Staff AI Researcher at LinkedIn, who has led a lot of critical AI projects in the company to success and brought great improvements of experiences to the 500M+ professional users of LinkedIn through the cutting-edge AI technology. Liang obtained his Ph. D. degree at Department of Statistical Science, Duke University in 2008, worked at Yahoo! Labs as a Scientist from 2008 to 2012, and has been working at LinkedIn since 2012. Liang has published extensively in top-tier computer science conferences as well as statistics journals, and also coauthored 20+ AI-related patents. His research mainly focuses on bringing the cutting-edge AI technologies to user-facing products at scale. Liang also served as the Program Committee members for various data mining and machine learning venues.
Anusua Trivedi is a Data Scientist at Microsoft’s Cloud AI + Research Team. She works on developing advanced Deep Learning models & AI solutions. She’s an advanced trainer and conducts hands-on deep learning labs. Prior to joining Microsoft, Anusua has held positions with UT Austin and University of Utah. Anusua is a frequent speaker at machine learning and AI conferences.