BigData AI Edu Symposium 2021
About The Symposium
SCU and the Big Data AI Center at California State University Los Angeles organize the 2021 International Symposium of Big Data, AI and the Education. The organizing committee is pleased to announce the Symposium 2021 to be held on Oct 29 2021 virtually in Seoul, Korea(Oct 28 2021 Pacific Time). The symposium will provide high-profile talks and panel discussion about the cutting edge technology in the area of Big Data, AI and education. The speakers are invited from the leading companies and the universities to see the current and the future trends of IT technology. The symposium should create great opportunities to learn the latest technology and show the insight of how the industry and the university collaborate to deliver the education and research in AI & Big Data. The Symposium is supported by NRF.
Your participation is crucial to the success of the symposium. We hope to see you all in October.
Best regards, The Symposium 2021 Organizing Committee
Your participation is crucial to the success of the symposium. We hope to see you all in October.
Best regards, The Symposium 2021 Organizing Committee
Programs
| Speaker(Affiliation) | 10/28 Thur Pacific Time PT | 10/29 Fri KST Seoul, Korea Time | Talk Title |
|---|---|---|---|
| In Kang (President, Seoul Cyber University) | 5:00-5:05 pm | 9:00-9:05 am | Opening Remarks |
| Srijith Rajamohan (Ph.D., Sr. Developer Advocate(Data Science and ML), Databricks) | 5:05-5:20 pm | 9:05-9:20 am | Deep Learning at Scale with Databricks |
| Sanghoon Lee (Professor, Yonsei University) | 5:20-5:35 pm | 9:20-9:35 am | Multi-camera studios for high-quality 3D data acquisition |
| Joe Bungo(DLI Program Manager, NVIDIA) | 5:35-5:50 pm | 9:35-9:50 am | Bringing GPU Accelerated Computing, AI and Data Science to the Classroom |
| All Speakers and Ji-Young Chun (Professor, Seoul Cyber University) | 5:50-6:05 pm | 9:50-10:05 am | Panel Discussion: Education and research in Big Data and AI at University |
| Jongwook Woo (Professor, California State University Los Angeles) | 6:05-6:10 pm | 10:05-10:10 am | Closing Remarks |
Speakers
- Speaker 1
- Srijith Rajamohan
- Sr. Developer Advocate(Data Science and ML) at Databricks
- Dr. Srijith Rajamohan is currently employed as a Sr. Developer Advocate at Databricks where he works on Data Science and Machine Learning (ML) problems. He is interested in all things related to the ML lifecycle and has a focus on Natural Language Processing and Bayesian modeling. He recently launched a series of three courses on Coursera to teach 'Computational Statistics and Bayesian Inference' using PyMC3. He was previously employed at Virginia Tech as a Computational Scientist from 2014 to 2020 where he worked on Natural Language Understanding using deep learning techniques, Bayesian inference and reproducible/scalable infrastructure for ML problems. He is a graduate of the SimCenter: Center of Excellence in Applied Computational Science and Engineering where he did his thesis work on Computational Electromagnetics using the Finite-Element Method and earned a Doctorate in Computational Engineering from the University of Tennessee in 2014. He also hold a Masters in Electrical Engineering from The Pennsylvania State University where he worked on implementing Neural Networks for Computer Vision on the IBM Cell processor
- Speaker 2
- Sanghoon Lee
- Professor, Yonsei University
- Dr Lee Sanghoon joined the faculty of the Department of Electrical and Electronics Engineering, Yonsei University, Seoul, Korea, where he is a full professor. He has been an Associate Editor of the IEEE Trans. Image Processing (2010-) and an Editor of the Journal of Communications and Networks (JCN) (2009-), and the Chair of the IEEE P3333.1 Quality Assessment Working Group (2011-). He served as the Technical Committee of the IEEE IVMSP (2014-), the General Chair of the 2013 IEEE IVMSP workshop, and a guest editor of IEEE Trans. Image Processing 2013. He has received a 2012 special service award from IEEE Broadcast Technology Society and 2013 special service award from IEEE Signal Processing Society. His research interests include image/video quality assessments, medical image processing, cloud computing, wireless multimedia communications and wireless networks.
- Speaker 3
- Joe Bungo
- DLI Program Manager at NVIDIA
- Joe Bungo is the Deep Learning Institute (DLI) Program Manager at NVIDIA where he enables the use of deep learning and GPU accelerated computing technologies in universities, including curriculum and teaching material development, DLI University Ambassador/Instructor Certification, facilitation of academic ecosystems, and hands-on workshops. Previously, he managed university programs at Arm and worked as an applications engineer. Joe received his degree in Computer Science from the University of Texas at Austin. The call for accelerated computing, AI and data science skills is soaring and university classrooms are on the frontlines of feeding the demand. The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI, GPU computing, and accelerated data science. Developers, scientists, educators, researchers, and students can get practical experience powered by GPUs in the cloud. DLI Teaching Kits are complete course solutions that lower the barrier of incorporating AI and GPU computing in the classroom. The DLI University Ambassador Program enables qualified educators to teach DLI workshops, at no cost, across campuses and academic conferences to faculty, students, and researchers. DLI workshops offer student certification which demonstrates subject matter competency and supports career growth. Join NVIDIA’s higher education leadership to learn how to get involved in these programs.
- Speaker 4
- Ji-Young Chun
- Professor, Seoul Cyber University
- Dr. Ji Young Chun is currently a member of the Department of Big Data and Information Security at Seoul Cyber University where she is currently researching big data security, cryptographic protocols, as well as privacy enhancing technologies. On top of this she is also currently actively researching privacy-preserving federated learning to further improve user privacy. She received funding from the national research foundation of Korea for this project. Prior to taking her job at Seoul Cyber University Dr. Chun performed postdoctoral research in the United States, where she worked on a project known as SHARPS (Strategic Healthcare IT Advanced Research Projects on Security). This project was done through the University of Illinois at Urbana-Champaign with the goal of the project being aimed at reducing security and privacy barriers to improve the effective use of health information technology. Dr. Chun received her M.S and Ph.D from the Korea University in the department belonging to the Graduate School of Information Management and Security, and her B.S from the Department of Mathematics at Ewha Womans University.
- Speaker 5
- Jongwook Woo
- Professor, California State University Los Angeles, Endowed-Chair Professors at SCU
- Dr Jongwook Woo received his Ph.D from USC and went Yonsei University. He is a Professor at CIS Department of California State University Los Angeles, and Endowed-Chair Professor at SCU. He has served as a NVidia Ambassador, Teradata Academic Ambassador, a president at KSEA-SC, and a Council Member of IBM Spark Technology Center. He has consulted companies in Hollywood: CitySearch, ARM, E!, Warner Bros, SBC Interactive. He published more than 80 papers and his research interests include Scalable Big Data AI Analysis and Prediction. He awards Teradata TUN faculty Scholarship and received grants for distributed deep learning and Big Data from NRF of Korea, Amazon, IBM, Oracle, MicroSoft, and partnered with NVidia, Intel, Databricks, Cloudera, Hortonworks, SAS, QlikView, Tableau. He is a founder of Hemosoo Inc and The Big Link. He was invited as an invited speaker to more than 30 events, and as a keynote speaker at Open Innovation Network I-CON 2019, The 14th Asia Pacific International Conference on Information Science and Technology 2019, Conference of Korea Society of Computer and Information 2017.
Abstract of the Talk
- Srijith Rajamohan, Databricks
- Machine learning/Deep learning as a decision making tool has gained wide acceptance. However, in order to extract information from data using machine learning, it is critical that the ML/DL lifecycle be managed using best practices. In this talk, we cover how the Databricks Lakehouse platform can be used to perform Deep learning at scale.
- Sanghoon Lee, Yonsei University
- 3D data is now an essential datatype that is used in various media. Although the consumption and demand for high-quality 3D data are increasing daily, it is still cumbersome for an individual to acquire such data. Either a user should request a professional designer or use complex capturing devices to achieve high-quality 3D data, which is burdensome in terms of cost. In this session, we introduce three multi-camera studio prototypes for high-quality 3D data acquisition which can be easily implemented with off-the-shelf camera sensors. Each prototype studio is specialized in RGB, 3D mesh, and real-time streamed data. A user can directly follow or customize their own studio based on the design principles of our prototype studios. We also show some simple applications, 2D human style transfer and 3D human reconstruction, using the data acquired from our multi-camera studios.
- Joe Bungo, NVIDIA
- The call for accelerated computing, AI and data science skills is soaring and university classrooms are on the frontlines of feeding the demand. The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI, GPU computing, and accelerated data science. Developers, scientists, educators, researchers, and students can get practical experience powered by GPUs in the cloud. DLI Teaching Kits are complete course solutions that lower the barrier of incorporating AI and GPU computing in the classroom. The DLI University Ambassador Program enables qualified educators to teach DLI workshops, at no cost, across campuses and academic conferences to faculty, students, and researchers. DLI workshops offer student certification which demonstrates subject matter competency and supports career growth. Join NVIDIA’s higher education leadership to learn how to get involved in these programs.
By attending this talk, you will learn:- · How education can access Teaching Kits with curriculum materials in accelerated computing, AI, and robotics.
- · How to access free online training, certification, and cloud access to GPUs for teachers and students.
- · An overview of the NVIDIA DLI and University Ambassador Program.
- · How the Ambassador Program fits into larger programs that support teaching.
Hands-on learning, Training, HPC education, Deep learning, Machine learning, Artificial intelligence, GPU, Data science, Parallel computing, Accelerated computing
Organizers
- President
- In Kang
- President at SCU
- General Chair
- Jongwook Woo
- Professor at California State University Los Angeles, Endowed-Chair Professor at SCU
- Program Chair
- Yun-Na Kim
- Professor at SCU
- Local Chair
- Geon-Tae Noh
- Professor at SCU
- Communication Chair
- Ji-Young Chun
- Professor at SCU
About The SCU
Seoul Cyber University (SCU) was founded in 2000. SCU is located in Seoul, Korea and has nurtured the great number of students to lead their own paths to educational information and experience.
