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NUS School of Computing Summer Workshop

NUS School of Computing Summer Workshop. (1) 4 July to 26 July 2019 (Year 2 & above). (2) 14 July to 5 August 2019 (Year 1). Organizer : NUS School of Computing (Graduate Division) Program Director : Prof. Tan Tiow Seng Publicity & Execution : Liv Dai.

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NUS School of Computing Summer Workshop

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  1. NUSSchool of ComputingSummer Workshop (1) 4 Julyto26 July 2019 (Year 2 & above) (2) 14 July to5 August 2019 (Year 1) Organizer : NUS School of Computing (Graduate Division) Program Director : Prof.Tan Tiow Seng Publicity & Execution : Liv Dai

  2. National University ofSingapore (NUS) • Founded in 1905, NUS has since established itself as one of the top universities worldwide Education Resource Center University Town

  3. National University ofSingapore (NUS)

  4. School of Computing

  5. School of Computing • Department • Computer Science • Information Systems and Analytics • Staff • 109 (teaching) • 118 (research) • Student • 2300 undergraduate students • 600 PhD/Master students

  6. Summer WorkshopIntroduction

  7. Summer WorkshopApplication

  8. Summer WorkshopApplication

  9. For Students • (1) 2nd Year & above: arrive on 3rd or 4th July 2019 to check-in(2) 1st Year: arrive on 14 July 2019 to check-in • While in School of Computing (SOC) • Each student will attend 3 topics in the assigned clustereach for 1 days (total 3 lecture days) • Each student ranks the topics in order of preference in the cluster to do a group project (4 persons in a team) • Each group has about 4 hours of consultation time with the professor (mentor), and each mentor may provide a few more hours of lecture/guidance to all teams • (1) 2nd Year & above: Final showcase on 25 July 2019 (Thursday)(2) 1st Year: Final showcase on 2 August 2019 (Friday) • Check-out of student dormitory early morning of 26 July 2019 for all (and move to outside campus accommodation if needed)

  10. Program Itinerary (Year 2 & above)

  11. Program Itinerary (Year 1) • 26th July • Move to off-campus accommodation

  12. Program Itinerary (Year 2 & Above)

  13. Program Itinerary (Year 1)

  14. Selection of Topics (Year 2 & Above) Year 2 Students will select 1 out of 3 clusters. They will then attend 3 lectures covering the topics in the chosen cluster (two half-day of lecture per topic). For clusters with 4 topics, students will only be allowed to attend lectures for 3 topics as there are parallel lectures that are conducted concurrently. Each student will rank his/her preferences of the topics in the cluster to do a project. Each topic can take up to 11 project teams (maximum 44 students). The organizer, in consultation with the professors (mentors), has the final say on which topic a student will do a project.

  15. Selection of Topics (Year 1) Students will attend all topics, each for two half-days of lecture. Each student will then rank his/her preferences of the topics to do a project. Each topic can take up to 44 students. The organizer, in consultation with the professors (mentors), has the final say on which topic a student will do a project.

  16. Available Topics Year 2 and above Year 1

  17. Cluster 1 Multimedia & VR/AR Building a Video Streaming System with DASH 2D Videogame Development Real-Time and Realistic Graphics Rendering Immersive VR Experience Development

  18. Topic 1 • Real-Time and Realistic Graphics Rendering

  19. Topic 1

  20. Topic 2 2D Videogame Development

  21. Topic 2

  22. Topic 3 Immersive VR Experience Development

  23. Topic 3

  24. Topic 4 • Building a Video Streaming System with Dynamic Adaptive Streaming over HTTP (DASH)

  25. Topic 3

  26. Cluster 2 Big Data and Cloud Computing Mining Communities in Big-Data with Algorithms and Computational Thinking Simulation – Allowing “What if?” Scenarios • Data Analytics for Winning Data Competitions Cloud Computing with Big Data

  27. Topic 1 Mining Communities in Big-Data with Algorithms and Computational Thinking

  28. Topic 1

  29. Topic 2 Cloud Computing with Big Data

  30. Topic 2

  31. Topic 3 Simulation – Allowing ‘What if?’ scenarios

  32. Topic 3

  33. Topic 4 • Data Analytics for Winning Data Competitions

  34. Topic 4

  35. Cluster 3 AI and Security Tele-Robotic Deep Learning DOTA Defense of the Ancients Securing service in untrusted environment

  36. Topic 1 • Tele-Robotic Deep Learning

  37. Topic 1 • Tele-Robotic Deep Learning

  38. Topic 1

  39. Topic 2 • DOTA Defense of the Ancients

  40. Topic 2

  41. Topic 3 • Securing service in untrusted environment

  42. Topic 3

  43. Year 1 Topics Computational Pearls with Functional Programming Building Your Dream Smart Home Descriptive Analytics with R

  44. Topic 1 • Computational Pearls with Functional Programming -- You think you know programming? Think again!

  45. Topic 1

  46. Topic 2 • Descriptive Analytics with R

  47. Topic 2

  48. Topic 3 Building Your Dream Smart Home

  49. Topic 3

  50. Getting to KnowSingapore 4th

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