Rulai is an Enterprise Conversational Computing Platform provider. Rooted in academia, the founding team has a combined 200 years experience in AI research, published over 400 research papers and filed over 80 patents in AI. Its SaaS platform enables companies to build automated virtual assistants (VAs) for customer service, marketing, sales, logistics, and HR use cases and has been deployed across a wide variety of industries.
Rulai-powered VAs help companies automate many human-centered processes to create a fast and frictionless experience for employees and customers. Its self-serve platform allows business users to create and evolve bots with minimal use of precious IT resources. Rulai was recently recognized by Gartner, Forrester, and Bloomberg.
The team of Rulai is made up of industry veterans, researchers and engineers who each have a depth of experience not typically seen in an early stage company. The team brings to the table backgrounds in artificial intelligence, machine learning, natural language processing, recommendation systems and customer service and engagement strategies.
Marc is Chief Executive Officer of Rulai. Prior to joining Rulai, Marc was Chief Marketing Officer at Medallia. Previously, he spent nearly a decade at Google. He served as Vice President of Marketing for Access and Energy and Advisor to Google Capital. He led marketing for Android, Google Play and Google’s hardware and retail organizations and developed some of the most widely recognized brands in the world, turning Android from a novelty into the world’s most popular mobile operating system. Marc received his M.B.A from Stanford University and an M.S. degree in engineering from the University of Ghent, Belgium.
Dr. Zhang is a full Professor at University of California, Santa Cruz. She has more than 20 years of experience in AI. She has been a technical adviser for several startups and consultants for companies (HP, Toyota, Alibaba etc.) in industries including AI, security, healthcare, financial, e-commerce and automotive. She has received the U.S. National Science Foundation Faculty Career Award, Best Paper Awards from ACM SIGIR, and research awards/grants from companies, including Google, Microsoft, Ebay, Yahoo, NEC, Nokia and IBM. She has served as program chair, area chair and PC member for top international conferences. Dr. Zhang received her Ph.D. from School of Computer Science at Carnegie Mellon University.
Dr. Truong has over 20 years experience in transforming service platforms and service delivery experiences through AI innovation. As Chief Technology Officer of TTEC he drove the strategy and implementation of Virtual Assistant technologies to augment human agent capabilities, increase call center productivity, and deliver better customer experiences. He has received 15 patents and numerous service industry awards resulting from the development of differentiated and technology-enabled customer care operations. Dr. Truong has a Ph.D. in EE and CS from UC Berkeley, and a M.Sc., EE from University of Calgary.
Jim is a visionary, hands on, leader known for taking innovative ideas that pair deep learning and natural language processing with differentiated data sets, and turning them into game-changing businesses to generate rising revenue, profits and shareholder ROI. Zero to $300m+ revenues with profitability through IPOs and multi-billion dollar exits more than once. Previously at Excite, Ask Jeeves, Turn, Affine, Shotzoom, Attune.
Prior to joining Rulai, Joey was the SVP of Engineering and Data Science of Affinity Solutions, a Fintech company working with many large banks and FI’s in the US. Before Affinity Solutions, he worked as Head of Data Science for Tapjoy, a leading mobile ad tech company. Before that he was one of the founding engineers of Rocket Fuel, a company pioneering programmatic ad bidding leveraging AI, IPO’d in 2013. His strong passion is to make AI work for the real world.
Jamie Callan is a Professor at the Language Technologies Institute, a graduate department in Carnegie Mellon’s School of Computer Science. His research and teaching focus on text-based information retrieval, large-scale distributed search, federated search, adaptive information filtering, and a variety of text analysis/mining/analytics methods. Jamie has published more than 200 research papers on these and related subjects. Jamie is a past Chair of SIGIR, the international professional society for Information Retrieval research, a co-founding Editor-in-Chief of Foundations and Trends in Information Retrieval, and a past Editor-in-Chief of ACM’s Transactions on Information Systems (TOIS). Jamie is an organizer of 2019 Conversational Assistance Track for Evaluating Conversational Dialogues at TREC.NIST.GOV conducted by National Institute of Standards and Technology.
Wei is a researcher and pioneer in general artificial intelligence. He was named one of the 20 leading technologists driving China’s AI revolution by Forbes. Wei has more than 20 years’ research experience in AI. In the late 90s, he lead the Communicator Dialog System at Carnegie Mellon University and published the first paper on neural network (i.e. deep learning) for language models in 2000. He was a Distinguished Scientist at Baidu Research, a scientist of Facebook, and a researcher at NEC Laboratories USA. He started and lead the open source deep learning framework PaddlePaddle. He also has developed deep learning visual understanding technologies, and deployed them to the surveillance systems of many US airports around 2005.
Sri Kurniawan is a professor in the Computational Media Department at the University of California, Santa Cruz. She was a lecturer at the University of Manchester. Her research is focusing on human–computer interaction, human factors and ergonomics, accessibility, assistive technology, usability, empirical studies, and human-centered design. She has served as general chair and program chair for the International ACM SIGACCESS Conference on Computers & Accessibility.
Dr. Hsieh is an Associate Professor in the Department of Human Centered Design & Engineering (HCDE) and an Adjunct Associate Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. His research focuses on human–computer interaction, social computing, behavior change and related topics. Dr. Hsieh has served as Associate Chair for ACM CHI and Program co-Chair for HCI Consortium. He has received research grants from the National Science Foundation, the National Institute of Health, the Center for Disease Control and Prevention, Nokia, and Intel. Gary received his PhD in Human–Computer Interaction from the School of Computer Science at Carnegie Mellon University.