Machine Learning for Discovery Sciences
October 18 – 21
Workshop Sponsors: National Science Foundation, Foundation for Armenian Science and Technology
Seating is limited.
First come first serve.
The primary objective of the inaugural FAST-NSF workshop is to bring researchers and practitioners from machine learning and other data-intensive disciplines, to foster cross-disciplinary collaborations that can facilitate discovery science in those fields. The other important objective of the workshop is to establish and foster mutually beneficial collaborations between international and Armenian scientists, researchers, and students. Finally, we intend use the workshop to explore models for partnerships to facilitate such collaborations through different research and innovation programs, e.g., through joint graduate and post-doctoral fellowship programs between NSF and FAST.
topics of interest
The workshop will include participation from leading experts from a number of disciplines. Specifically, the workshop will bring together researchers who focus on foundational aspects of machine learning and practitioners who are interested in various applications. The topics covered include, but are not restricted to, the following:
Theory and Algorithms
- Deep Learning
- Unsupervised Representation Learning
- Graphical & Latent Variable Models
- Structure Learning
- Reinforcement Learning
- Statistical Physics of Learning
- Computer Vision & Image Processing
- Computational Biology and Bioinformatics
- Computational Social Science
- Natural Language Processing
- Network Analysis & Graph Mining
- Computational Neuroscience
Aram Galstyan, PhD
Director, MINDS, Information Sciences Institute, USC
Dr. Aram Galstyan holds an appointment as a research associate professor of computer science. Dr. Galstyan’s current research focuses on various problems at the intersection of machine learning, information theory, and statistical physics. His research has been supported by various U.S. funding agencies, including NSF, NIH, DARPA, IARPA, and ARO. He is currently the PI for DARPA’s Big Mechanism project, which aims revolutionize caner biology.
Naira Hovakimyan, PhD
Member, Board of Advisers, FAST
Before joining the faculty of UIUC in 2008, she has spent time as a research scientist at Stuttgart University in Germany, at INRIA in France, at Georgia Institute of Technology. Dr, Hovakimyan is currently W. Grafton and Lillian B. Wilkins Professor of Mechanical Science and Engineering at UIUC. In 2015 she was named as inaugural director for Intelligent Robotics Lab of CSL at UIUC. She is a fellow and life member of AIAA, a Senior Member of IEEE, and a member of SIAM, AMS, SWE, ASME and ISDG.
Foundation for Armenian Science and Technology
Foundation for Armenian Science and Technology (FAST) is driving technological innovation and scientific advancement in Armenia and beyond. It is a neutral and open platform that intends to concentrate, coordinate, and catalyze the activities of the global Armenian community of scientists, innovators, and entrepreneurs.
Welcoming Remarks from FAST
Co-Founder, Member of the Board
- Founder, Managing Partner and CEO of Flagship Ventures
- Member of the Corporation Development Committee of MIT
- Member of the Board of Trustees of Skolkovo Institute of Science and Technology
- Member of the Central Board of AGBU
Armen Orujyan, PhD is an entrepreneur and innovator who is the Founder and CEO of Athgo, one of the world’s leading entrepreneurial platforms in consultative status with the UN Economic and Social Council and the UN Department of Public Information.
Co-Founder, Member of the Board
- Founder – RVVZ Foundation
- Founder and CEO of Troika
- Dialog, one of the oldest and largest investment banks in Russia and the CIS
- Member of the Economic Advisory Board at IFC
- Member of the Board of AGBU
- Member of the Supreme Religious Council of the Armenian Apostolic Church
The National Science Foundation (NSF) is an independent federal agency created by the United States Congress in 1950 “to promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense…” NSF is vital in supporting basic research and people to create knowledge that transforms the future.
With an annual budget of $7.5 billion (FY 2016), NSF funds about 24% of all federally supported basic research conducted by America’s colleges and universities. In many fields such as mathematics, computer science and the social sciences, NSF is the major source of federal backing.
The emergence of big data has been transformational in many areas in science and engineering – biology, health sciences, material science, physics, and so on. At the heart of this transformation is statistical machine learning, subfield of computer science that aims at studying and developing algorithms that can analyze large volumes of data. The goal of this workshop is to bring together researchers, both from USA and Armenia, who work on machine learning (ML) and other scientific disciplines that are poised to benefit from the recent advances in ML.
Science and Technology in Armenia
During the Soviet times, Armenia was one of the main hubs of cybernetics research in ex-Soviet Union, where centers such as the Mergelyan Institute (one of the three major producers of computer equipment in former USSR), and the Computing Center of the National Armenian Academy of Science (currently the Institute for Informatics and Automation Problems) conducted cutting edge research on topics ranging from robotics to algorithmic game theory to automated machine translation. Currently, Armenia has a small but vibrant research community in machine learning and data science, some members of which have participated in past and present DoD-sponsored research projects in collaboration with US colleagues. Armenia also boasts several established world class research centers in biomedical sciences and biotechnology, theoretical and experimental cosmology, and high energy physics in the country, disciplines where the role of data intensive methods is becoming more and more important. Furthermore, Armenia’s IT sector, which has been the fastest-growing sector of the economy, provides an excellent framework for technology transfer. Local subsidiaries of tech giants include Synopsys, National Instruments, Mentor Graphics (acquired by Siemens) and VMware. Microsoft, Oracle, and IBM have established R&D offices and training facilities in Armenia. Some of the homegrown companies in Armenia, such as the PicsArt, Triada Studio, Teamable, and FimeTech, have succeeded in raising sufficient venture capital resources to expand their R&D teams outside the country, with many establishing offices in Silicon Valley of the US.
Yerevan is the capital and largest city of Armenia as well as one of the world’s oldest continuously inhabited cities.
Situated along the Hrazdan River, Yerevan is the administrative, cultural, and industrial center of the country. It has been the capital since 1918, the thirteenth in the history of Armenia, and the seventh located in or around the Ararat plain. (Wikipedia)
Republic Square, Yerevan