MLconf Atlanta

Friday, September 19, 2014 from 8:00 AM to 6:00 PM (PDT) More Information → Register

Join us for an exciting event on September 19th, a block away of Georgia Tech at the Academy of Medicine for the first Atlanta-based MLconf. This year MLconf will focus on ML platforms, tools and algorithms. We'll host a speaker from Facebook whom will give us an overview of how machine learning shapes the biggest social network. We are very happy to have speakers from emerging platforms like Revolution Analytics one of the top players in industrial strength parallel R, SkyTree with their super fast and scalable machine learning server, Context Relevant with their scalable platform that finds structure in the data in record time, and 0xdata’s will present their open source platform and the new deep learning toolbox. Come and find out more about Systap’s graph analytics and machine learning platform on GPUs and Finally if you play in the traditional RDBMS field ORACLE will tell you how to do machine learning. If you are in he NOSQL arena, Cloudera will present the current trends. Professor Manos Antonakis will explain why machine learning alone cannot solve problems, without some domain expertise through his experience in internet security. Professor Amy Langville, the guru of ranking and also the author of “Who is #1”, “Google’s, Page rank and Beyond” will tell us how to rank all kinds of data, from sport teams to movies. If you want to find out how Netflix and Meetup, do their recommendations, you will be surprised by the difference on the constraints and data availability they have.

Event Speakers: 

Ewa Dominowska
Engineering Manager, Facebook

Ewa Dominowska joined Facebook in spring of 2014 as an Engineering Manager focused on Science and Metrics for Online Advertising. Before coming to Facebook she designed a large scale predictive analytics platform for mobile devices as a Chief Architect at Medio Systems (acquired by Nokia). Prior to her start-up days, Ewa spent 10 years in various roles at Microsoft. At Microsoft, Ewa joined the Online Services Division to help found adCenter, the second largest online advertising platform in the US. Her work focused on real-time ad ranking, targeting, content analysis, click prediction, and pricing models. As part of the small yet dynamic original team, Ewa designed, architected, and built the alpha version of the contextual advertising product. In 2007, Ewa founded the Open Platform Research and Development team. As part of this effort, she organized the Beyond Search academic program, TROA WWW Workshop, and IRA SIGIR Workshop, resulting in a number of very successful collaborations between academia and industry. During her tenure in the Online Services Division, Ewa spent a year serving as the TA for Satya Nadella, where she advised and assisted in operation and planning for the division. The role encompassed architecture, technology, large-scale data services, and cross-organizational efficiency. Ewa was responsible for the intellectual property process, long-term strategy, and prioritization for the division. In 2010 Ewa started the adCenter Marketplace team responsible for all aspects of the advertising marketplace health and tuning. She architected and built a petabyte-scale distributed data and analytics platform and created a suite of marketplace and experimentation tools.

Ewa earned her degrees in Electrical Engineering/Computer Science and Mathematics from MIT. Her research focused on machine learning, natural language processing, and predictive, context aware systems applied in the medical field. Ewa authored several papers and dozens of patents in the areas of online advertising, search, pricing models, predictive algorithms and user interaction.

Mingxuan Sun
Senior Scientist, Pandora

Mingxuan Sun is a senior scientist at Pandora Media, working in the playlist recommendation group. She received her Ph.D. degree in Computer Science from Georgia Institute of Technology in 2012. Her general research interests include statistical machine learning and visualization, with current emphasis on developing scalable methods to make use of massive data for prediction and recommendation tasks.

Sandy Ryza
Software Engineer, Cloudera

Sandy Ryza is an engineer on the data science team at Cloudera.  He is a committer on Apache Hadoop and recently led Cloudera's Apache Spark development.

Elizabeth Elhassani
Director of Marketing Analytics and Insights, LexisNexis

Elizabeth Elhassani joined LexisNexis Risk Solutions as Director, Marketing, Marketing Analytics & Insights in January 2012. In this newly created position within Marketing, Elizabeth is responsible for leading the design and implementation of short and long term analytic strategies to benefit all of our businesses. This includes, targeting and segmenting our client and prospect databases for effective demand generation, as well as working closely with our Marketing and Sales colleagues to track, analyze and report results of all customer-facing initiatives, both online and offline.

An experienced marketing professional, Elizabeth brings more than 10 years of B2B and B2C analytics marketing experience to our ranks, with emphasis in designing statistical models, CRM strategies, segmentation schemes and cost benefit analyses. She was Associate Director for dunnhumby USA where she was responsible for scoping, pricing and designing consumer analytic insight projects for 10+ key consumer package goods clients utilizing many statistical methodologies to study customer behaviors including linear and nonlinear regression, CART/CHAID, ANOVA and cluster analysis. Prior to her work at dunnhumby, she was a Statistical Project Director for ChoicePoint Precision Marketing where she was responsible for consulting and directing projects for marketing analytics and acquisition models for external clients. In addition to her analytics expertise, she also brings an understanding of our industry with previous experience at Experian and Advanta Bank Business Cards.  



Justin Basilico
Senior Researcher/Engineer in Recommendation Systems, Netflix

Justin Basilico is a Research/Engineering manager for Page Algorithms Engineering at Netflix. He leads an applied research team focused on developing the next generation of algorithms used to generate the Netflix homepage through machine learning, ranking, recommendation, and large-scale software engineering. Prior to Netflix, he worked on machine learning in the Cognitive Systems group at Sandia National Laboratories. He is also the co-creator of the Cognitive Foundry, an open-source software library for building machine learning algorithms and applications.  

Hassan Chafi
Research Manager, Oracle Labs

Hassan Chafi is a Senior Research Manager at Oracle Labs where he currently leads various projects. His research investigates high-performance, parallel, in-memory Graph Analytics and using domain specific languages (DSLs) to simplify parallel programming. Dr. Chafi received his  PhD from Stanford University. His thesis work at Stanford focused on building a Domain Specific Language Infrastructure, Delite. His was advised by Dr. Kunle Olukotun. Prior to that, Hassan worked in the area of hardware transactional memory as part of the Transactional Coherence and Consistency (TCC) project at Stanford where he developed a scalable extension to the original TCC protocol.

Evan Estola
Data Scientist,

Evan is a Machine Learning Engineer at Meetup, where he is responsible for building intelligent systems that directly affect the user experience. Evan owns the recommendation engine at Meetup from data collection to production. Previously, Evan was on the Machine Learning Team at Orbitz Worldwide and he got his start in the Information Retrieval Lab at the Illinois Institute of Technology.

Sri Ambati
Senior Co-founder, 0xdata

Sri is co-founder and ceo of 0xdata (@hexadata), the builders of H2O. H2O democratizes bigdata science and makes hadoop do math for better predictions. Before 0xdata, Sri spent time scaling R over bigdata with researchers at Purdue and Stanford. Prior to that Sri co-founded Platfora and was the Director of Engineering at DataStax. Before that Sri was Partner & Performance engineer at java multi-core startup, Azul Systems, tinkering with the entire ecosystem of enterprise apps at scale. Before that Sri was at sabbatical pursuing Theoretical Neuroscience at Berkeley. Prior to that Sri worked on nosql trie based index for semistructured data at in-memory index startup RightOrder. Sri is known for his knack for envisioning killer apps in fast evolving spaces and assembling stellar teams towards productizing that vision. Sri is a regular speaker in the BigData, NoSQL and Java circuit.

Amy Langville
Associate Professor of Mathematics, The College of Charleston in South Carolina

Amy is an Associate Professor of Mathematics at The College of Charleston in South Carolina where she regularly teaches graduate courses in Operations Research and Optimization and undergraduate courses in calculus and linear algebra. Her research focuses on ranking and clustering. She also enjoys solving applied mathematics problems from industry and has consulted with a variety of companies from large search engines and software companies to small start-ups and law firms engaged in patent infringement cases. Amy studied Operations Research for her PhD and web information retrieval for her postdoctorate at N.C. State University. When the surf's up, Amy's riding it. When it's not, she's training jiu-jitsu, peppering a volleyball, or biking around Folly Beach.


Parikshit Ram
Senior Machine Learning Scientist, Skytree

Parikshit Ram is a member of the technical staff at the machine learning startup Skytree ( where he develops enterprise grade machine learning algorithms. Prior to this, Pari completed his doctorate in Computer Science at Georgia Tech in the School of Computational Science and Engineering where he was a member of the FASTlab and focused on developing fundamental algorithms and statistical tools for machine learning and data mining. Pari joined Georgia Tech in 2007 after completing his BS and MS in Mathematics and Computing in the department of Mathematics at Indian Institute of Technology, Kharagpur, India. Pari has also contributed to the open source machine learning library MLPACK (


Emmanouil Konstantinos Antonakakis
Assistant Professor of Computer Systems and Software, Georgia Tech 

Manos Antonakakis received his engineering diploma in 2004 from the University of the Aegean, Department of Information and Communication Systems Engineering. From November 2004 up to July 2006, he was working as a guest researcher at the National Institute of Standards and Technology (NIST-DoC), in the area of wireless ad hoc network security, at the Computer Security Division. Before joining the ECE faculty, Dr. Antonakakis held the chief scientist role at Damballa, where he was responsible for advanced research projects, university collaborations, and technology transfer efforts. He currently serves as the co-chair of the Academic Committee for the Messaging Anti-Abuse Working Group (MAAWG). In May 2012, he received his Ph.D. in computer science from the Georgia Institute of Technology under Wenke Lee's supervision. In his free time, he enjoys watching and playing soccer. 


Bryan Thompson
Chief Scientist and Founder at SYSTAP, LLC 

Bryan Thompson (SYSTAP, LLC) is the Chief Scientist and co-Founder of SYSTAP, LLC. He is the lead architect for bigdata®, an open source graph database used by Fortune 500 companies including EMC (SYSTAP provides the graph engine for the topology server used in their host and storage management solutions) and Autodesk (SYSTAP provides their cloud solution for graph search). He is the principle investigator for a DARPA research team investigating GPU-accelerated distributed architectures for graph databases and graph mining. He has over 30 years experience related to cloud computing; graph databases; the semantic web; web architecture; relational, object, and RDF database architectures; knowledge management and collaboration; artificial intelligence and connectionist models; natural language processing; metrics, scalability studies, benchmarks and performance tuning; decision support systems.

Danai Koutra
CMU/Technicolor Researcher, Carnegie Mellon University

Danai Koutra is a final-year Ph.D. candidate at the Computer Science Department at Carnegie Mellon University. Her research interests include large-scale graph mining, graph similarity and matching, graph summarization, and anomaly detection. Danai's research has been applied mainly to social, collaboration and web networks, as well as brain connectivity graphs. She holds 1 ``rate-1'' patent and has 6 (pending) patents on bipartite graph alignment. Danai has multiple papers in top data mining conferences, including 2 award-winning papers, and her work was covered by popular press, such as MIT Technology Review. She has also worked at IBM Hawthorne, Microsoft Research Redmond, and Technicolor Palo Alto/Los Altos. She earned her M.S. in Computer Science from CMU 2013 and her diploma in ECE at the National Technical University of Athens in 2010.

Jacob Mundt
Chief Technology Officer, eBrevia

Jacob Mundt is the CTO at legal tech startup eBrevia, applying information extraction and summarization to the text of legal documents and contracts. eBrevia provides software tools that help attorneys to speed their review of legal documents while increasing accuracy. Previously Jacob researched summarization, machine translation, and information extraction under Kathleen McKeown at Columbia University, and led the Research and Development team at Outcome Sciences (acquired by Quintiles) to improve patient health outcomes through collection of clinical data from hundreds of hospitals. He holds a Bachelor of Science from Rice University and a Master of Science from Columbia.