Deep Learning World Las Vegas 2018
June 3-7, 2018 – Caesars Palace, Las Vegas
Vice President of Data Science
Halim is a high tech innovator who spearheaded world-class data science projects at game changing techs like eBay and Teradata. Formally educated in Machine Learning, his professional expertise span Information Retrieval, Natural Language Processing, and Big Data. Halim has a proven track record of applying state of the art data science techniques across industry verticals such as eCommerce, web & mobile services, airline, BioPharma, and the medical technology industry. He currently leads the Data Science team at Cognoa, a data driven behavioral healthcare startup in Palo Alto.
Halim Abbas is speaker of the following session:
Product Lead, Machine Learning Platform
Gil Arditi is speaker of the following session:
Staff Data Scientist
Dr. Chokor has developed and integrated emerging IIoT data-driven solutions in multiple industries. As a staff data scientist at Seagate Technology, Abbas unlocks the value of industrial and manufacturing data through leading edge science and mentors uprising data scientists. Before Seagate, Abbas was a lead data scientist on multiple predictive maintenance projects within First Solar, Siemens, and Schlumberger, for their complex assets, including solar panels, trains, and Oil & Gas surface machines. Abbas holds a Ph.D. from Arizona State University in Tempe, Arizona and has co-authored dozens of research publications. His research interests include developing state-of-the-art edge solutions in the field of predictive maintenance and online learning.
Abbas Chokor is speaker of the following session:
Emerging Technology Engineer
Cameron Cooke is an Emerging Technology Engineer for Qantas Airways in Sydney, Australia. He is responsible for developing cutting edge solutions to the airline's problems, helping to keep the worlds most experienced airline at the forefront of technology. Most recently, he is focusing on applying deep learning to novel business problems across the organisation.
Cameron has a strong background in machine learning, analytics & simulation. He has authored a number of patents, and holds a Bachelor of Engineering (Hons) degree from the University of New South Wales, majoring in Electrical Engineering.
Cameron Cooke is speaker of the following session:
Pranjal Daga is a Data Scientist focused on strategizing and developing Deep Learning Proof of Concepts at Cisco Services Machine Learning R&D. He graduated from Purdue University with a Masters in Computer Science, specializing in Deep Learning and NLP. In the past, Pranjal has worked with researchers at Adobe Research, University of Alberta, Northwestern University, IBM Research and MIT. He has spent the past few years exploring new technologies, hacking on the quirky side projects and bringing together his research and engineering experiences. To understand the practical aspects of identifying business ideas and moving them forward, Pranjal recently joined Stanford Graduate School of Business' Ignite program.
On a side for fun, Pranjal loves building new things from scratch, which is why he's been a regular participant in hackathons. He likes to travel and has recently developed a fascination with sunsets and the effects pollution has on their colors.
Pranjal Daga is speaker of the following session:
Assistant Professor of Finance and Statistics
Matthew Dixon is an Assistant Professor of Finance and Statistics at the Illinois Institute of Technology. His research in computational methods for finance is funded by Intel. Matthew began his career in structured credit trading at Lehman Brothers in London before pursuing academics and consulting for financial institutions in quantitative trading and risk modeling. He holds a Ph.D. in Applied Mathematics from Imperial College (2007) and has held postdoctoral and visiting professor appointments at Stanford University and UC Davis respectively. He has published over 20 peer reviewed publications on machine learning and financial modeling, has been cited in Bloomberg Markets and the Financial Times as an AI in fintech expert, and is a frequently invited speaker in Silicon Valley and on Wall Street. He has published R packages, served as a Google Summer of Code mentor and is the co-founder of the Thalesians.
Matthew Dixon is speaker of the following session:
John Elder chairs America's most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina and Washington DC. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia, and was named by President Bush to serve 5 years on a panel to guide technology for national security.
John Elder is speaker of the following session:
Director of Machine Learning
Rezsa is currently the Director of Machine Learning at Vevo. He is a Machine Learning leader and innovator with a background in computational engineering, data science, and AI. His ML experience spans across diverse applications, from developing deep learning recommender systems in the entertainment industry to oil well blowout risk prediction in the oil & gas industry.
Rezsa Farahani is speaker of the following session:
Emerging Technology Lead
Natalie Ganderton is the Emerging Tech Lead for Qantas Airways in Sydney, Australia. She is responsible for identifying & experimenting with key new technologies and guiding them through the maturation phase to enterprise adoption, with recent focus on an AI strategy for the Qantas Group. Natalie has over 15 years experience in advanced analytics, statistics, simulation, operations research and software development in a variety of industries on both sides of the vendor/client fence. She has spent time working in New Zealand, the UK, U.A.E. and Australia, and holds a Bachelor of Engineering (Hons) degree from the University of Auckland, majoring in Engineering Science (Operations Research).
Natalie Ganderton is speaker of the following session:
Research Analytics Consultant
Luba Gloukhova facilitates and accelerates advanced research projects at a major R&D hub of the Silicon Valley. She supports Stanford GSB faculty by conceiving and generating innovative solutions that drive their cutting edge research. Luba also serves as the founding program chair of Deep Learning World, the premier conference covering the commercial deployment of deep learning.
Luba received her master's in analytics from the University of San Francisco and her bachelors in both applied math and economics from Berkeley. Before her current position in academic research, she gained industry experience in analytics consulting, high frequency trading analysis, catastrophe risk modeling, and quantitative marketing. Luba also teaches yoga and enjoys an active lifestyle.
Luba Gloukhova is speaker of the following sessions:
Machine Learning Engineer
Kate Highnam has a background in Computer Science and Business, focusing on security, embedded devices, and accounting. At the University of Virginia, her thesis was a published industrial research paper containing an attack scenario and repair algorithm for drones deployed on missions with limited ground control contact. After joining Capital One as a Data Engineer, Kate has developed features within an internal DevOps Pipeline and Data Lake governance system. Currently, she builds machine learning models to assist cybersecurity experts and enhance defenses.
Kate Highnam is speaker of the following session:
Vishwa heads Advanced Analytics function at John Hancock Insurance. He is passionate about combining math and data to drive Business outcomes. Towards this end, he led several engagements that use ML and AI methods across 6 industries and in over a dozen F100 firms.
Vishwa is a thought leader and regularly speaks at conferences on a variety of topics - Analytics Architecture & Strategy, Internal and 3rd Party Data, Big Data Best Practices, Advanced Methods - opportunities & Pitfalls, AI-Led transformations, C[A, AI, D] O series - operating models, Underwriting Risk Analytics, Marketing Analytics and Mix Modeling, Fraud Analytics.
Vishwa received his MBA from Carnegie Mellon University, an MS from U. Denver and BS from BITS Pilani, India.
Vishwa Kolla is speaker of the following session:
Chris Labbe is a 20+ year veteran of the Hard Drive design industry with jobs in many areas throughout the company and is currently the Managing Technologist of Seagate's Data Science Analytics Development team.
He is now on a grand adventure to help Seagate build a world-class Predictive Analytics organization utilizing a strong background in programming, mathematics, statistics and organizational strategic leadership.
Chris Labbe is speaker of the following session:
Deep Reinforcement Learning Research Group
Ricky Loynd is a member of the reinforcement learning research group in the Microsoft Research AI labs in Redmond, Wash. He has 25 years of experience with neural networks, and 11 years of experience in reinforcement learning. Ricky is currently focused on creating deep RL agents with more general, human-like intelligence. As a lead mentor for the Microsoft AI School Advanced Projects course, Ricky has helped teams throughout the company incorporate deep learning systems into their work.
Ricky Loynd is speaker of the following session:
Senior Scientist Engineer
James McCaffrey works for Microsoft Research in Redmond, Wash. James explores applied deep machine learning and artificial intelligence. He has worked on several Microsoft products including Internet Explorer and Bing. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science.
James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.
James McCaffrey is speaker of the following sessions:
Senior Data Engineer
Marek Pietrzyk is a Senior Data Engineer at Northwestern Mutual. Throughout his career, he has held a number of academic and professional positions. Areas of his experience include market research, survey research, factory automation, software engineering, data warehousing, marketing, business intelligence, analytics, management, and systems engineering. Marek received his Ph.D. in Mathematics from Wrocław University of Science and Technology in Wrocław, Poland.
Marek Pietrzyk is speaker of the following session:
Analytics and IT Strategy Lead
Dr. Nalini Polavarapu has been with Monsanto for over ten years, and manages a global team of analytical and IT professionals, specialized in machine learning, operations research and cloud analytics to deliver better products to market faster through data science. Data science activities range from inventing cognitive systems to enhance decision making, predictive and prescriptive analytics to automate/augment decisions, geo-spatial and image analytics to realize precision farming, and analytics to increase operational efficiency.
Nalini also serves as the senior leader on the Data Science Center of Excellence Council partnering with other senior leaders enterprise wide to drive the efforts to realize the vision of transforming into a digital company through data science. Activities include implementing an enterprise wide talent and community development strategy, scalable technology platforms, best practices for development and deployment of analytical solutions and portfolio management.
Over the course of her career, Nalini held positions of increasing levels of leadership responsibilities managing teams operating across geographies in Americas, EMEA, Asia and Africa, and has successfully established and led an off-shore center in India. She also initiated multiple external partnerships and collaborations with start-ups, large corporations and universities. Being the first data scientist at Monsanto, Nalini played a key role in building a world-class global data science organization which is now at 100+ and growing through hiring and development of data scientists, data science leaders, as well as positions of seniority within the groups.
Nalini is the recipient of highest awards in technology for four consecutive years and a Fellow.
Nalini has a PhD and dual Masters in Computer Science and Bioinformatics from Georgia Institute of Technology in Atlanta, Georgia. Nalini has authored and co-authored several analytical patents, research articles in leading scientific journals and co-authored book chapters on high throughput data analysis and applications.
Nalini Polavarapu is speaker of the following session:
Machine Learning Engineer
Domenic Puzio is a Machine Learning Engineer with Capital One. He graduated from the University of Virginia with degrees in Mathematics and Computer Science. On his current project he is a core developer of a custom platform for ingesting, processing, and analyzing Capital One's cyber-security data sources. Built from open-source tools (NiFi, Kafka, Storm, Elasticsearch, Kibana), this framework processes hundreds of millions of events per hour. Currently, his focus is on the creation and productionization of machine learning models to detect malware and phishing. He is a contributor to two Apache projects.
Domenic Puzio is speaker of the following session:
Nitin Sharma is currently working as a Distinguished Data Scientist in the Large Scale Machine Learning and AI group in PayPal Risk Sciences.
Nitin Sharma is speaker of the following session:
Head of Data Science, Advanced Technologies Group
Mike serves as Head of Data Science at Uber ATG, UC Berkeley Data Science faculty, and head of Skymind Labs the Machine Learning research lab affiliated with DeepLearning4J. He has led teams of Data Scientists in the bay area as Chief Data Scientist for InterTrust, Director of Data Sciences for MetaScale/Sears, and CSO for Galvanize where he founded the galvanizeU-UNH accredited Masters of Science in Data Science degree and oversaw the company's transformation from co-working space to Data Science organization. Mike began his career in academia serving as a mathematics teaching fellow for Columbia University before teaching at the University of Pittsburgh. His early research focused on developing the epsilon-anchor methodology for resolving both an inconsistency he highlighted in the dynamics of Einstein’s general relativity theory and the convergence of “large N” Monte Carlo simulations in Statistical Mechanics’ universality models of criticality phenomena.
Michael Tamir is speaker of the following session:
Decision Sciences Technology Lead
David Walechka is the Decision Sciences Technology Lead at Northwestern Mutual. He is responsible for team of data scientists and technologists working on complex, large scale machine learning problems. He pioneered some of the first machine learning models at Northwestern Mutual and implemented the first set of algorithmic underwriting models. He has 15 years experience working with data and analytics technologies having previously held roles as Senior Information Architect and BI Consultant.
David Walechka is speaker of the following session:
Chief Product Officer
Nathan is the Chief Product Officer of Entropix, providing product definition and strategic business planning and market development. Ten years of hardware/software design and innovations in the enterprise HD surveillance market helped Nathan shape the current Entropix software product. He is also the Founder and Chairman of Network Optix, an enterprise video management software company listed as the 7th fastest growing software company in the US. (2016, Inc. 5000). Earlier served as a Director of Sales at Arecont Vision leading the company to record sales.
Nathan Wheeler is speaker of the following session: