Sam Altman is the president of Y Combinator and the co-chair of OpenAI. He was co-founder and CEO of Loopt, which was funded by Y Combinator in 2005 and acquired by Green Dot in 2012. At Green Dot, he was the CTO and is now on the Board of Directors. Sam also founded Hydrazine Capital. He studied computer science at Stanford, and while there worked in the AI lab.
Yoshua Bengio is the author of three books and over 200 publications, and heads up the Montreal Institute for Learning Algorithms (MILA), currently the largest academic research group on deep learning. He is on the board of the NIPS foundation and has been program chair and general chair for NIPS. His current interests are centered around a quest for AI through machine learning, and include fundamental questions on deep learning and representation learning, the geometry of generalization in high-dimensional spaces, generative models, biologically inspired learning algorithms, natural language understanding and other challenging applications of machine learning.
Ian Goodfellow is a staff research scientist at Google Brain. He is the lead author of the MIT Press textbook Deep Learning (www.deeplearningbook.org) and the inventor of generative adversarial networks. He is generally interested in all things deep learning, and usually focuses on generative models, machine learning security, and differential privacy.
Aerin is the CEO and Founder of BYOR, a company whose products combine techniques from Natural Language Processing and Deep Learning - a focus on meaning and context - to bring intuitive and insightful suggestions/predictions to the given text data. Aerin is a data scientist and engineer, aka Unapologetic Abuser of Machines for the merciless amount of data that she processes on the machine. Before BYOR, she has priced structured products for financial institutions and built ad optimization engines for marketers.
Dennis is the CEO and Founder of x.ai. He’s a pioneer and expert in leveraging Data and a serial entrepreneur who has successfully delivered a number of company exits on that theme. Dennis’s long term vision of killing the inbox triggered the formation of x.ai and the creation of an artificial intelligence personal assistant to schedule meetings. He’s an accredited Associate Analytics Instructor at the University of British Columbia, the Author of Data Driven Insights from Wiley and a frequent speaker on the subject of AI, intelligent agents, and the future of work. A native of Denmark, Mortensen currently calls New York City his home.
Dr. Kirk Borne is the Principal Data Scientist at Booz Allen Hamilton (since 2015). He previously spent 12 years as Professor of Astrophysics and Computational Science at George Mason University where he taught and advised students in the Data Science degree programs. Before that, he worked 18 years supporting NASA projects in various roles, including Data Archive Project Scientist for the Hubble Space Telescope. He is an active contributor on social media, where he has been named consistently the #1 worldwide influencer in big data and data science since 2013, and he was named #2 influencer in AI and machine learning in 2016. In 2016 he was named Fellow of the International Astrostatistics Association.
Yi Wang is the tech lead of AI Platform at Baidu. The team is a primary contributor of PaddlePaddle, the open source deep learning platform originally developed in Baidu. Before Baidu, he was a founding member of ScaledInference, a Palo Alto-based AI startup company. Before that, he was a senior staff at LinkedIn, engineering director of advertising system at Tencent, and researcher at Google.
Christian Guttmann (Phd/MSc) is an Adj. Assoc. Professor at the University of New South Wales, a Research Fellow at the Karolinska Institute and the CEO of HealthiHabits. His expertise and activities are firmly grounded in the intersection of AI and Health. He is an entrepreneurially driven technology leader with over 20 years of experience in industry and research. At BT, IBM, HP, successful startups and scientific projects, he led innovation teams using AI, data science and analytics, social/mobile/IoT technology with health authorities, hospitals, pharma/medical device industry, patient associations and primary health care. He is in international steering and program committees of leading conferences in AI and Health Care innovation. He co-authored and co-edited over 50 international peer reviewed publications and has 8 patent disclosures in his field. He completed his PhD in Distributed AI at Monash University. He received two CS Master degrees and a Psychology degree from Swedish and German Universities. HealthiHabits.com is a social network company using AI to connect patients with a chronic condition aiming to sustain "healthy habits" over time. To contact, follow his twitter or email him at email@example.com.
Danko Nikolić received a degree in Psychology and a degree in Civil Engineering from the University of Zagreb. He received a Master’s degree and a Ph.D. in Cognitive Psychology from at the OU. In 2010 he received a Private Docent title from the University of Zagreb, as well as an Associate Professor title in 2014. He is now associated with FIAS and works at CSC in the field of AI and data science. He has a keen interest in addressing the explanatory gap between the brain and the mind. His interest is in how the physical world of neuronal activity produces the mental world of perception and cognition. For many years he headed an electrophysiological lab at MPI Brain. He approached the problem of explanatory gap from both sides, bottom-up and top-down led him to develop a theory: The work on behavior and experiences led to the discovery of the phenomenon of ideasthesia (meaning "sensing concepts"). The work on physiology resulted in the theory of practopoiesis (meaning "creation of actions").
Dr. Gerald Friedland is Principal Data Scientist at Lawrence Livermore National Lab and is also teaching as an adjunct professor at the Electrical Engineering and Computer Science department of UC Berkeley. He mostly focusses on large scale machine learning problems, such as searching in the 100M images or 1M videos of the YFCC100M dataset that he co-initiated. Dr. Friedland has published more than 200 peer-reviewed articles in conferences, journals, and books. He also authored a new textbook on multimedia computing together with Dr. Ramesh Jain. He is associate editor for ACM Transactions on Multimedia and IEEE Multimedia Magazine and regularly reviews for IEEE Transactions on Acoustics, Speech, and Language Processing; IEEE Transaction on Multimedia; Springer's Machine Vision and Application; and other journals. He is the recipient of several research and industry recognitions, among them the European Academic Software Award and the Multimedia Entrepreneur Award by the German Federal Department of Economics. Dr. Friedland received his doctorate (summa cum laude) and master's degree in computer science from Freie Universitaet Berlin, Germany, in 2002 and 2006, respectively.
Patrick McDaniel is a Distinguished Professor in the School of Electrical Engineering and Computer Science and Director of the Institute for Networking and Security Research at the Pennsylvania State University. Professor McDaniel is a Fellow of the IEEE and ACM and program manager and lead scientist for the Army Research Laboratory's Cyber-Security Collaborative Research Alliance. Patrick’s research centrally focuses on a wide range of topics in security and technical public policy. Prior to joining Penn State in 2004, he was a senior research staff member at AT&T Labs-Research.
Nicolas Papernot is a PhD student in Computer Science and Engineering advised by Dr. Patrick McDaniel at the Pennsylvania State University. His research interests lie at the intersection of computer security and deep learning. He is supported by a Google PhD Fellowship in Security. In 2016, he received his MS in Computer Science and Engineering from the Pennsylvania State University and his MS in Engineering Sciences from the École Centrale de Lyon.
I’m a Machine Intelligence researcher architecting, analyzing, and implementing intelligent industrial systems based on simulation-driven multi-objective optimization technologies at Ericsson Research, since 2015. Before joining Ericsson, I served as a Postdoc at the University of Campinas, Brazil. My PhD thesis on anticipatory multi-objective ML was awarded in 2014 the Thesis National Prize in the area of Electrical, Computing, and Automation Engineering, by the Brazilian Ministry of Education. My problem-solving experience includes developing Bayesian, neural, and evolutionary-inspired computational tools for a range of applications such as financial decision support, predictive analytics, supply chain and logistics optimization, data clustering, pattern classification, and data compression. I also took part in the 2010 Global Solutions Program of Singularity University at NASA Ames Research Park, where I was engaged in the subgroup which investigated how to augment robotic autonomy for space exploration through AI.
Francisco J. Martin, Ph.D. CEO, BigML, Inc Francisco is the CEO at BigML, Inc where he helps conceptualize, design, architect, and implement BigML's distributed Machine Learning platform. Formerly, Francisco founded and led Strands, Inc, a company that pioneered Behavior-based Recommender Systems. Previously, he founded and led Intelligent Software Components, SA (iSOCO), the first spin-off of the Spanish National Research Council (CSIC). He holds a 5-year degree in Computer Science, a Ph.D. in Artificial Intelligence, and a post-doc in Machine Learning. He is the holder of 20+ patents in the areas of Recommender Systems and Distributed Machine Learning.
As Chief Technology Officer and co-founder of KONUX, Vlad Lata is in charge of product development with focus on AI and Big Data. Lata and the engineering department at KONUX create customized sensor and analytics solutions to increase asset availability and network capacity in the rail sector.
Natalie is a 4th year PhD student in the bioinformatics and computational biology (BCB) program at UNC Chapel Hill. Her research is focused on the development of probabilistic models for community structure in networks as well as methods for network compression to enable more tractable community detection. She enjoys collaborating on clustering and classification problems with biologists.
Mohammed was the lead product manager at Siri. He is a former product manager at Google, Apple and Misfit (acquired by Fossil) and previously worked at GoButler building an on-demand messaging service. He has now founded a company building an AI-driven simulator in WhatsApp to train workers in acquiring soft-skills.
Moataz Rashad is currently founder & CEO/CTO of DeepVu (pka Vufind Inc) a deep-learning SaaS startup focused on cognitive supply chains and maximizing margins for manufacturers. Moataz had a career of 20+ years in the IT and consumer electronics sectors. He built products and led teams at several industry leaders including SonyEricsson, Conexant/Mindspeed/Rockwell, Samsung, Exponential, MIPS, and Silicon Graphics. Moataz led and was key principal engineer/architect on products ranging from cloud services/APIs, Xperia mobile phones and tablets, wireless cameras, mobile apps and games, and networking and wireless silicon components. Moataz Led Conexant’s investment in Tensilica (acquired by Cadence in 2012). He is an inventor on 20 issued US and International patents in the fields of computer vision, deep-learning, microprocessors, GPU/DSP architectures, and simulation. Moataz holds an MSEE from Stanford, and an MSCS from the University of Oregon, and a B.Sc. with Distinction & Honors in Computer Engineering and Control Systems from Alexandria University. He was a PhD student in Information Systems Lab of the EE department at Stanford before he dropped out in 1996 to pursue his industry career. Moataz has been obsessed with AI since his undergraduate years and studied it in graduate school at both Oregon and Stanford yet changed direction since it wasn’t ready for commercial real-world applications at the time. Moataz has over 8 technical academic publications and gave invited talks at industry conferences and major research universities.
Konstantina Christakopoulou (Diploma University of Patras, Greece 2013; MS University of Minnesota 2015) is a fourth-year PhD student in the Computer Science & Engineering Department at the University of Minnesota. The broader area of her research is machine learning, with a particular focus on recommendation systems. She has interned with Google and Microsoft Research and has published her research in top-tier conferences.
Anna is a PhD candidate at Utah State University (USU). Her research is in improving Random Forests.
Behnaz got her PhD in Computer Engineering in 2015. She is currently working as a machine learning engineer in a startup company Gen-9 Inc, working on developing machine learning algorithms on wearable devices. During her PhD studies she worked as an intern in Genscape and she developed a new algorithm on refinery images to predict and detect anomalies using computer vision and machine learning. Behnaz has focus on developing machine learning algorithms in different domain such as healthcare, wearable devices and images.
Bruno Gonçalves is currently a Moore-Sloan Fellow at NYU's Center for Data Science. With a background in Physics and Computer Science his career has revolved around the use of datasets from sources as diverse as Apache web logs, Wikipedia edits, Twitter posts epidemiological reports and Census data to analyze and model Human Behavior and Mobility. More recently he has focused on the application of machine learning and neural network techniques to analyze large geolocated datasets. He is the editor of "Social Phenomena: From Data Analysis to Models" (Springer, 2015) and a co-author of the forthcoming "Twitterology: The Social Science of Twitter" (Springer, 2018).
Eyal Amir is co-founder and CEO of Ai Incube (Parknav) and Adjunct Associate Professor of Computer Science at the University of Illinois Urbana-Champaign. His company creates AI and analytics for IoT sensors, primarily focusing on automobile and mobility needs. In his scientific research Eyal focuses on merging common sense reasoning and AI with machine learning and probabilistic reasoning. He is the winner of a number of awards from Stanford University, IEEE, and the National Science Foundation. He shares his time between San Francisco, California and Munich, Germany.
Matt manages Numenta's open source projects, helps the HTM Community, and produces educational videos about HTM.
Deepak Agarwal is a vice president of engineering at LinkedIn where he is responsible for all AI efforts across the company. He is well known for his work on recommender systems and has published a book on the topic. He has published extensively in top-tier computer science conferences and has coauthored several patents. He is a Fellow of the American Statistical Association and has served on the Executive Committee of Knowledge Discovery and Data Mining (KDD). Deepak regularly serves on program committees of various conferences in the field of AI and computer science. He is also an associate editor of two flagship statistics journals.
Co-founder of Deckard.ai. Product-oriented software engineer & ML hacker enabling machines to learn how to boost software teams.
Dawn Song is a Professor in the Department of Electrical Engineering and CS at UC Berkeley. Her research interest lies in deep learning and security. She has studied diverse security and privacy issues in computer systems and networks, including areas ranging from software security, networking security, database security, distributed systems security, applied cryptography, to the intersection of ML and security. She is the recipient of various awards including the MacArthur Fellowship, the Guggenheim Fellowship, the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review TR-35 Award, the George Tallman Ladd Research Award, the Okawa Foundation Research Award, the Li Ka Shing Foundation Women in Science Distinguished Lecture Series Award, the Faculty Research Award from IBM, Google and other major tech companies, and Best Paper Awards from top conferences. She obtained her Ph.D. degree from Cal. Prior to joining Cal, as a faculty, she was an Assistant Professor at CMU from 2002 to 2007.
John has been building business-critical machine learning pipelines for the past 5 years, first at Criteo, and now at Liftoff where he currently leads the machine learning team. He holds a PhD in Computer Science from the Sorbonne University in Paris.
Adji is a PhD candidate in the department of Statistics at Columbia University where she is being advised by David Blei and John Paisley. Her research focus is on machine and deep learning, probabilistic modeling, and variational methods with applications to natural language processing. She holds a double degree from Telecom ParisTech in France and Cornell University. Learn more on her homepage http://stat.columbia.edu/~diengadji/
Bhawna Shiwani is a Research Engineer at Delsys Inc. She received her B.E. in Electronics and Communication Engineering from National Institute of Technology, Jalandhar, India in 2012 and she is currently pursuing her M.S. in Robotics Engineering at Worcester Polytechnic Institute, Worcester, MA. She was previously employed by Cadence Design Systems, Noida, India where she worked as a Member of Technical Staff. Her current research interests include Robotics, Artificial Intelligence and Machine Learning.
Charles Ollion is the co-founder and head of Research at Heuritech, a company focusing on image and text analysis on Fashion posts for product and trend detection. Charles also holds a PhD in Machine Learning and is a lecturer in Deep Learning at Ecole Polytechnique Master 2 program, Paris Saclay Datascience. Charles will present with Hedi Ben Younes, PhD in Machine Learning at LIP6/Heuritech.
Pedro has experience in predicting, analyzing and visualizing data in the fields of: genomics, gene networks, cancer metastasis, insurance fraud/costs, hospital readmissions, soccer strategies, joint injuries, social graphs, human attraction, spam detection, topic modeling and computer vision among others. Pedro is incredibly passionate about all aspects of data science and is constantly creating new techniques and algorithms to suit the problems at hand. Pedro also has a strong attraction to the basics, which can be forgotten easily these days, such as the scientific method and just looking at the data. Recently his efforts were geared towards detecting and interpreting everything that is happening in the world in real-time, from major concerts and sporting events to major and minor news using deep learning. Currently Pedro has decided to begin a startup with the main goal of helping machine learning deliver on its promises.
Karmel Allison is an Engineering Manager at Quora, and has spent the last decade working with big data and machine learning. She received her PhD in Bioinformatics from the University of California, San Diego, and previously worked to design algorithms for DNA sequencing.
Oriol Vinyals is a Research Scientist at Deepmind. Previously he was a member of the Google Brain team. He holds a Ph.D. in EECS from University of California, Berkeley, and a Masters degree from the University of California, San Diego.
Ciprian Chelba is a research scientist at Google. Previously he worked as a researcher in the speech technology group at Microsoft. His research interests are in statistical modeling of natural language and speech. Ciprian got his Phd in Electrical and Computer Engineering from The Johns Hopkins University.
Holder of a PhD in computer science with focus on machine learning and data mining from Michigan State University, Hamed Valizadegan joined NASA Ames Research Center (UARC) as a machine learning research scientist in 2013. At Ames, he has been involved with multiple projects including Hubble Space Telescope, Kepler mission and ASRS aviation safety reports! Before joining NASA Ames, he spent three years at University of Pittsburgh conducting research in Medical Informatics. He has published in prestigious venues such as International Conference on Neural Information Processing Systems (NIPS), ACM SIGKDD conference on Knowledge discovery and Data Mining (KDD), and Artificial Intelligence and Statistics (AISTATS).
After graduating from Ecole 42 in Paris Pierre-Edouard joined Recast.AI in 2015 and is now managing partnerships. Building your bot in one hour with Recast.AI 101. This workshop will teach you how to use the Recast.AI platform and the basics of chatbot building. You will also learn how to connect your bot to a messaging platform using the bot connector.
Kamelia Aryafar, Ph.D. is a senior data scientist with Etsy's Data Science team since 2013. She works on building scalable machine learning and computer vision tools to curate a personalized experience for Etsy users. Prior to Etsy she was doing a Ph.D. in computer science and machine learning in Drexel University, building large-scale music classification models.
Jaya Kawale is a senior research scientist at Netflix working on various problems related to recommendation and targeting. Before that she was a senior research scientist at Adobe Research and did her PhD in Computer Science from University of Minnesota
Dr. Vikas Agrawal works as a Senior Principal Data Scientist in the area of Cognitive Computing for Advanced Analytics for Oracle Corporation. Vikas has created activity context-aware Virtual Personal Assistants for insurance, pharma, retail and investment banks, Real-Time Asset Management systems for Internet of Things (IoT) in mining and production systems, Reliability Risk Management and Predictive Maintenance systems while at Intel Corporation, Infosys Limited and Oracle Corporation. Vikas received a BTech in Electrical Engineering from the Indian Institute of Technology, New Delhi, an MS in Computer Science and a PhD in Computational Modeling from University of Delaware (Newark, DE), and conducted post-doctoral research at California Institute of Technology (CalTech, Pasadena, CA) in PDE-based modeling of population development and differentiation with researchers from NASA's Jet Propulsion Labs (JPL) for NSF's FIBR.
I am a Ph.D. research assistant at the Knowledge Discovery and Web Mining Lab, University of Louisville. My research has been mainly on personalization systems and techniques that incorporate large amounts of data available on the internet, such as user actives on social networks and user reviews for items on e-commerce websites. In addition to working on my Ph.D., in 2015 I joined a start-up company Gen-9 as a Machine Learning Software Engineer Intern, where I helped build multiple data products and applications (including mobile) to study user patterns of varying time frames using wearables. Also, I was a graduate research assistant at the BioImaging Lab, University of Louisville, where I worked on machine learning techniques for image segmentation of lung/chest regions in medical CT images using Parallel Programming and GPU computing. I studied Software Engineering at University of Tehran and graduated in June 2009.
Andres Rodriguez is a senior technical lead with Intel Nervana where he designs deep learning solutions for Intel’s customers and provides technical leadership across Intel for deep learning products. He has 13 years of experience working in artificial intelligence. Andres received his Ph.D. from Carnegie Mellon University for his research in machine learning, and prior to joining Intel, he was a research scientist and principal investigator for deep learning with the Air Force Research Laboratory and adjunct professor at Wright State University. He holds over 20 peers-reviewed publications in journals and conferences and a book chapter on machine learning.
Mark Schmidt has been an assistant professor in the Department of Computer Science at the University of British Columbia since 2014, and a Canada Research Chair since 2016. His research focuses on developing faster algorithms for large-scale machine learning, with an emphasis on methods with provable convergence rates and that can be applied to structured prediction problems. From 2011 through 2013 he worked at the cole normale supÈrieure in Paris on inexact and stochastic convex optimization methods. He finished his M.Sc. in 2005 at the University of Alberta working as part of the Brain Tumor Analysis Project, and his Ph.D. in 2010 at the University of British Columbia working on graphical model structure learning with L1-regularization. He has also worked at Siemens Medical Solutions on heart motion abnormality detection, with Michael Friedlander in the Scientific Computing Laboratory at the University of British Columbia on semi-stochastic optimization methods, and with Anoop Sarkar at Simon Fraser University on large-scale training of natural language models.
PI for AHRQ research on health IT, former Principle Research Scientist at University of Washington, Director of Future Products & Architecture at Microsoft Global Services Automation, Technical Fellow for human-computer interaction in Boeing Math & Computing Technology, and lead author of the ISO standard for usability now adapted for Federal certification of electronic medical record systems. He also serves on NASA's standing research review panel for the Orion Project, and as Univ of WA representative to the Object Management Group.
Data Scientist, Bestselling Author, Youtube Star
Dimitri Kanevsky is a Research Scientist at Google, developing a YouTube speech recognition system. Prior to Google, Dimitri was a research staff member in the Speech and Language Algorithms Department at IBM Watson Research Center. Dimitri was responsible for developing the first Russian automatic speech recognition system, as well as key projects for embedding speech recognition in automobiles and broadcast transcription systems. Dimitri was an invited scientist at top math centers, including Weizmann Institute of Science, Max Planck Institute and the IAS. He currently holds 257 US patents and was granted the title of Master Inventor at IBM in 2002, 2005 and 2010. His conversational biometrics based security patent was recognized by MIT Tech Review, as one of five most influential patents for 2003. His contributions on Extended Baum-Welch algorithms for speech, embedding speech recognition in automobiles and his work on conversational biometrics were recognized as science accomplishments in 2002, 2004 and 2008 by the Director of Research at IBM. In 2005 Dimitri Kanevsky received an Honorary Degree (Doctor of Laws, honoris causa) from CBU. He was elected as a member of the WTN in 2004 and was a Chairperson of the IT Software Technology session at the WTN Summit, 2005, SF. In 2012, he organized a special session on Large Scale Optimization at ICASSP, organized a NIPS workshop on log-linear models, was honored at the White House as a Champion of Change for his efforts to advance access to STEM, and received the Tan Chin Tuan Exchange Fellowship award from NTU Singapore for development of sparse optimization methods and its application in speech. In 2003, he was the lead guest editor for the Special Issue on Large-Scale Optimization for IEEE Trans. ASLP.
Dr. Olaf Witkowski, Research Scientist at the Earth-Life Science Institute in Tokyo, Visiting Member at the Institute for Advanced Study in Princeton and Chief Architect at YHouse Inc. in New York.
Michael Galvin is the Executive Director of Data Science at Metis. He came to Metis from General Electric where he worked to establish their data science strategy and capabilities for field services and to build solutions supporting Global operations, risk, engineering, sales, and marketing. Prior to GE, Michael spent several years as a data scientist working on problems in credit modeling at Kabbage and corporate travel and procurement at TRX. Michael holds a Bachelor's degree in Mathematics and a Master's degree in Computational Science and Engineering from the Georgia Institute of Technology where he also spent 3 years working on machine learning research problems related to computational biology and bioinformatics. Additionally, Michael spent 12 years in the United States Marine Corps where he held various leadership roles within aviation, logistics, and training units.
Peter A. Gloor is a Research Scientist at the Center for Collective Intelligence at MIT's Sloan School of Management where he leads a project exploring Collaborative Innovation Networks. He is also Founder and Chief Creative Officer of software company galaxyadvisors, a Honorary Professor at University of Cologne, Distinguished Visiting Professor at P. Universidad Católica de Chile and Honorary Professor at Jilin University, Changchun, China. Earlier he was a partner with Deloitte and PwC, and a manager at UBS. He got his Ph.D in computer science from the University of Zurich and was a Post-Doc at the MIT Lab for Computer Science.
As an Ex-Googler, Ilker is the co-founder & CEO of Botanalytics which is a conversational analytics & engagement tool for bots based in San Francisco. Botanalytics helps bot makers to enhance the human-bot communication on their bots. Also, Botanalytics is backed by 500 Startups. Ilker has a BSc in Computer Science and an MBA degree. He exited his first startup while studying at college. He’s a doer and professional tennis player.
Founder of Keotic, a Core AI company. Roni blends his 15 years of experience in building complex systems and algorithms, with a business oriented strategic state of mind. As a former AOL employee, he explored new ways to tackle real life disambiguation problems, which eventually led to AOL’s entity resolver. Roni’s areas of interest include: Deep Learning, Artificial Intelligence, Cognitive Science, Economic Science, Natural Language Processing, Machine Learning and Data Science. Alongside his role at Keotic, he is serving as an advisor to various companies in these fields.
Jason Yosinski is a machine learning researcher and founding member of Uber AI Labs, where he uses neural networks and machine learning to build more capable and more understandable AI. He suspects scientists and engineers will build increasingly powerful AI systems faster than we can understand them, motivating much of his work on what has been called "AI Neuroscience" -- an emerging field that may become increasingly important in the next several years. Mr. Yosinski was previously a PhD student and NASA Space Technology Research Fellow working at the Cornell Creative Machines Lab, the University of Montreal, the Caltech Jet Propulsion Laboratory, and Google DeepMind. His work on AI has been featured on NPR, Fast Company, the Economist, TEDx, and on the BBC.
Daniel Krasner is the Founder/CEO of Merriam Tech, which focuses on intelligent, AI driven document management systems solutions, and the Director of Data Science in eDiscovery at Paul Hastings, where he brings the latest developments in statistical engineering to the legal world. In addition, he is the co-Founder of KFit Solutions, a data science consulting firm, that has created data science solutions across various sectors (financial, commerce, media, news, startup, legal). Over the past year Daniel has also been the technology lead with the Columbia University History Lab which focuses on building archival document management systems and analyzing large collections of textual data. His current interests and work focus on high performance statistical solutions in text and natural language processing. Previously, Daniel was the chief data scientist at Sailthru, an email and behavioral analytics platform, a senior researcher at Johnson Research Labs, a lecturer at the London School of Economics and a professor at Columbia University statistics department. Prior to entering the world of data science, Daniel Krasner was a researcher at the Mathematical Sciences Research Institute in Berkeley and an assistant professor of mathematics at UCLA. He holds a PhD in mathematics from Columbia University.
Assistant professor Markus Schatten got his masters degree at the Faculty of organization and informatics in 2008. and his doctoral degree at the same faculty in 2010. He has been working at the Faculty of organization and informatics from 2006. He has been teaching several courses related to database systems, programming and artificial intelligence at doctoral, graduate, undergraduate and professional level at the Faculty of Organization and Informatics in Varazdin, at the Faculty of Information Studies in Novo Mesto in Slovenia and at the University of the People, USA. He launched, and is currently the head of the Laboratory for Artificial Intelligence at the Faculty of organization and informatics. From 2009. to 2014. was a board member of MLAZ (Network of Young Scientists), and from 2014 to today is a board member of ITS (Intelligent Transport Systems). Assistant professor Markus Schatten, PhD is the author and co-author of many scientific and professional articles (over 80). He is a mentor of a number of undergraduate and graduate theses (over 50) and a mentor or co-mentor of 5 doctoral dissertations.
Andreea Bodnari is a machine learning consultant and technology entrepreneur. She consults nationally and internationally for companies tackling innovative ideas in Healthcare Informatics and Artificial Intelligence. Andreea received her PhD from the MIT Computer Science and Artificial Intelligence Lab, focused on Natural Language Processing and Healthcare Informatics. Throughout her research, she investigated how artificial intelligence can be used to improve healthcare outcomes and decipher the mechanisms behind the human language. Her work has been published at prominent American and European conferences and she is a frequent speaker on machine learning industrial panels.
Nathan Wilson is a scientist and entrepreneur who is focused on actualizing powerful new models of brain-based computation. After many years at MIT working on the mathematical logic of neural circuits, Nathan co-founded Nara Logics, a Cambridge, MA artificial intelligence company building a novel type of neural network that automatically finds and refines connections in raw data for large enterprises to guide decisions. Nara Logics exemplifies how breakthroughs in neuroscience are poised to transform computer science. Nathan holds many patents in AI and his research has been featured in top journals including Nature, Science, Proceedings of the National Academy of Sciences, Neuron, and the MIT Press. An enthusiastic writer and teacher who routinely appears in the popular press on current topics in AI, Nathan now works to guide advancements at Nara Logics as CTO.
Dr. Eli David is an expert in the field of computational intelligence, specializing in deep learning (neural networks) and evolutionary computation. He has published more than thirty papers in leading artificial intelligence journals and conferences, mostly focusing on applications of deep learning and genetic algorithms in various real-world domains. For the past ten years, he has been teaching courses on deep learning and evolutionary computation at Bar-Ilan University, in addition to supervising the research of graduate students in these fields. Dr. David has also served in numerous capacities successfully designing, implementing, and leading deep learning based projects in real-world environments. Dr. David is the developer of Falcon, a grandmaster-level chess playing program, which automatically learns by processing datasets of chess games. The program reached the second place in World Computer Speed Chess Championship 2008 relying solely on machine learning for its performance. Dr. David received the Best Paper Award in 2008 Genetic and Evolutionary Computation Conference, the Gold Award in the prestigious "Humies" Awards for Human-Competitive Results in 2014, and recently the Best Paper Award in 2016 International Conference on Artificial Neural Networks.
Satya Gautam Vadlamudi received the B.Tech.(Hons.) and Ph.D. degrees in Computer Science and Engineering from the Indian Institute of Technology Kharagpur (IIT), Kharagpur, India, in 2008 and 2014, respectively. He is currently a Principal Data Scientist at Capillary Technologies, Bengaluru. Prior to Capillary, he has spent time as a researcher at ASU, Intel Labs, IIT Kharagpur (working in collaboration with General Motors India Science Lab and with Xerox Research Centre India), Google and Georgia Tech, predominantly working on various AI related technologies among other things. Dr. Vadlamudi was the recipient of several honors, including the Pratibha Award from the Government of Andhra Pradesh and SAP Labs Doctoral Fellowship.
Luka Bradesko is a computer science PhD candidate from Artificial Intelligence Lab at Jozef Stefan Institute, Slovenia. His research interests and PhD topic are in Natural Language Processing, Logical Inference and Knowledge Extraction. From 2008 to 2013 he also worked as a principal software engineer for Cycorp Europe, which was at the time an EU branch of the American AI company Cyc Inc. During these years, he worked on an EU project developing distributed large scale inference engine (LarKC), and also on an AI assistant startup build on top of Cyc (Curious Cat). The AI assistant that was part of the startup is core of his PhD topic: Knowledge Acquisition through Natural Language Conversation and Crowdsourcing, which is at the moment being under minor revision review in the Transactions on Information Systems Journal. After 2013, when the startup was not succeeding Luka continued his PhD research activities and also other research projects. Some of the recent projects include a concept of an intelligent motorhome (reasoning engine software interacting with sensors and actuators) for a European motorhome producer (Adria Mobil) and Named Entity Disambiguation algorithm which is a work in progress in a collaboration with US Company Bloomberg L.P.
Jeremy Howard is an entrepreneur, business strategist, developer, and educator. Jeremy is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible. He is also a Distinguished Research Scientist at the University of San Francisco, a faculty member at Singularity University, and a Young Global Leader with the World Economic Forum. Jeremy’s most recent startup, Enlitic, was the first company to apply deep learning to medicine, and has been selected one of the world’s top 50 smartest companies by MIT Tech Review two years running. He was previously the President and Chief Scientist of the data science platform Kaggle, where he was the top ranked participant in international machine learning competitions 2 years running. He was the founding CEO of two successful Australian startups (FastMail, and Optimal Decisions Group–purchased by Lexis-Nexis). Before that, he spent 8 years in management consulting, at McKinsey & Co, and AT Kearney. Jeremy has invested in, mentored, and advised many startups, and contributed to many open source projects. He has many television and other video appearances, including as a regular guest on Australia’s highest-rated breakfast news program, a popular talk on TED.com, and data science and web development tutorials and discussions.
Machine learning researcher with focus on language. Completed a PhD on question answering at the University of Bari, Italy, were he founded a startup, QuestionCube. Worked for Yahoo Labs in Barcelona on learning to rank, IBM Watson in New York on natural language processing with deep learning and then joined Geometric Intelligence, where he worked on grounded language understanding. He is now a research scientist at Uber AI Labs in San Francisco.
Shashi Kant is the founder and CTO of Netra, a company that empowers brands to engage with imagery and social networks. Shashi earned his Master’s in Engineering & Management from MIT and MIT Sloan School of Management. His research in “Semantics” of Artificial Intelligence at the MIT Computer Science & Artificial Intelligence Laboratory was the genesis of Netra's technology. His career has spanned Schlumberger, Absolute Software, NASA-Ames and “big data” consulting with multiple Fortune-100 companies. He holds a Bachelor’s degree in Engineering from India and was an ASP Fellow at MIT.
Steven Hamblin is an academic by background, having done his PhD and postdocs in computational evolutionary biology and biostatistics. He's also been programming since he was a kid and seems to be unable to give it up. More recently he's transitioned into industry, first as the head of the artificial intelligence team at babylon health, where he built the team from scratch to recognition as one of the health industry's leading AI efforts, and more recently as CTO of Shoal, a new early-stage startup aimed at making insurance better.
Hedi received his diploma from Centrale-Supelec French engineering school. His work is related to deep learning for multimodal representations - combining text and visual information. He notably worked on Visual Question Answering. He works jointly as a deep learning scientist at Heuritech, and as a PhD at Université Pierre and Marie Curie (LIP6).
I am blind and also a professional scientist by training. I have been teaching graduate level engineering courses since I first graduate from the university at age 24. I have also been both peer reviewer on numerous governmental and private sector based scientific and engineering research funding committees. In addition to writing numerous successful scientific and engineering grant proposals that have funded my research throughout the years. I have a PhD. in Robotics and a B.S. degree in Computer Systems Engineering from the State University of New York at Stoney Brook. I presently am a professor emeritus and teach as an adjunct professor at several local colleges and universities. I teach at both the undergraduate and graduate levels. Presently, I am a Co-Advisor on the doctoral committee of a foreign PhD. candidate in Robotics and Artificial Intelligence. This candidate is doing additional work on hardware based adaptive neural networks for machine vision applications and his work is based in large part upon my own research on the NERVOTRON that was done in 1994. Also, I am a scientific peer reviewer on the IEEE-WCCS (Institute of Electrical and Electronic Engineers - World Conference on Complex Systems) research paper acceptance committee and I also do contract based jobs in robotics and artificial intelligence based systems design.