Yifeng Jiang is a graduate student at Peking University studying computer science and technology. He received his bachelor's degree from Beijing Institute of Technology where he graduated at the top of his class. During his studies, he has received numerous honors and scholarships for his academic performance. He has work experience in research labs focusing on areas like computer vision, image processing, and information security. Currently he is the vice president of the graduate student union and founder of a student catering business in Shenzhen.
Feedback for medicine - Long cases using PebblePad - Ruth Weeks (University o...ePortfolios Australia
This presentation will focus on the use of an eportfolio (PebblePad) to provide timely formative feedback on long case histories in seven clinical schools across the University of Sydney Medical Program. A common complaint from students and residents is that they are not given enough feedback in the clinical setting. This project was designed to offer feedback on written cases and, in addition, to gather data on who was actually viewing the presentations of long cases in the clinical setting. From 2015, a required formative assessment was introduced, consisting of eight long cases which were presented orally (with immediate feedback given by a supervisor or other staff), then written up and submitted via Pebblepad. Formative assessment was provided by a Medical Lead in each clinical school also via the eportfolio. Students had the option of reflecting on their written cases.
Feedback for medicine - Long cases using PebblePad - Ruth Weeks (University o...ePortfolios Australia
This presentation will focus on the use of an eportfolio (PebblePad) to provide timely formative feedback on long case histories in seven clinical schools across the University of Sydney Medical Program. A common complaint from students and residents is that they are not given enough feedback in the clinical setting. This project was designed to offer feedback on written cases and, in addition, to gather data on who was actually viewing the presentations of long cases in the clinical setting. From 2015, a required formative assessment was introduced, consisting of eight long cases which were presented orally (with immediate feedback given by a supervisor or other staff), then written up and submitted via Pebblepad. Formative assessment was provided by a Medical Lead in each clinical school also via the eportfolio. Students had the option of reflecting on their written cases.
Using GPUs to handle Big Data with Java by Adam Roberts.J On The Beach
Modern graphics processing units (GPUs) are efficient general-purpose stream processors. Learn how Java can exploit the power of GPUs to optimize high-performance enterprise and technical computing applications such as big data and analytics workloads. This presentation covers principles and considerations for GPU programming from Java and looks at the software stack and developer tools available. It also presents a demo showing GPU acceleration and discusses what is coming in the future.
The talk by Maksud Ibrahimov, Chief Data Scientist at InfoReady Analytics. He is going to share with us how to maximise the performance of Spark.
As a user of Apache Spark from very early releases, he generally sees that the framework is easy to start with but as the program grows its performance starts to suffer. In this talk Maksud will answer the following questions:
- How to reach higher level of parallelism of your jobs without scaling up your cluster?
- Understanding shuffles, and how to avoid disk spills
- How to identify task stragglers and data skews?
- How to identify Spark bottlenecks?
Using GPUs to handle Big Data with Java by Adam Roberts.J On The Beach
Modern graphics processing units (GPUs) are efficient general-purpose stream processors. Learn how Java can exploit the power of GPUs to optimize high-performance enterprise and technical computing applications such as big data and analytics workloads. This presentation covers principles and considerations for GPU programming from Java and looks at the software stack and developer tools available. It also presents a demo showing GPU acceleration and discusses what is coming in the future.
The talk by Maksud Ibrahimov, Chief Data Scientist at InfoReady Analytics. He is going to share with us how to maximise the performance of Spark.
As a user of Apache Spark from very early releases, he generally sees that the framework is easy to start with but as the program grows its performance starts to suffer. In this talk Maksud will answer the following questions:
- How to reach higher level of parallelism of your jobs without scaling up your cluster?
- Understanding shuffles, and how to avoid disk spills
- How to identify task stragglers and data skews?
- How to identify Spark bottlenecks?
What have we learned from 6 years of implementing learning analytics amongst ...Bart Rienties
By Professor Bart Rienties, Head of Academic Professional Development, Institute of Educational Technology, The Open University, UK
Abstract
The Open University UK (OU) has been implementing learning analytics since 2014, starting with one or two modules to its current practice of large-scale implementation across all its 400+ modules and 170.000+ students and 4000+ teaching staff. While a range of reviews (e.g., Adenij, 2019) and scholarly repositories (e.g., Web of Science) indicate that the OU is the largest contributor to academic output in learning analytics in the world, behind the flashy publications and practitioner outputs there are a range of complex issues in terms of ethics and privacy, data infrastructures, buy-in from staff, student engagement, and how to make sense of big data in a complex organisation like the OU.
Based upon large-scale big data research we found some interesting tensions in both design and educational theory, such as:
– 69% of engagement by students on a week by week basis is determined by how teachers are designing courses (i.e., learning design and instructional design indeed directly influence behaviour and cognition), but many teachers seem reluctant to change their learning design based upon data of what works and what does not work (e.g., making sense of data, agency);
– How teachers engage with predictive learning analytics (PLA) significantly improves student outcomes, but only a minority of teachers actually use PLA;
– Some disadvantaged groups engage more actively in OU courses, but nonetheless perform lower than non-disadvantaged students.
During this CELDA keynote I would like to share some of my own reflections of how the OU has implemented learning analytics, and how these insights are helping towards a stronger evidence-base for data-informed change. Furthermore, by sharing some of the lessons learned from implementing learning analytics on a large scale I hope to provide some dos and don’ts in terms of how you might consider to use data in your own practice and context.
«Learning Analytics at the Open University and the UK»Bart Rienties
In this seminar, Prof Bart Rienties will reflect on how the Open University UK has become a leading institution in implementing learning analytics at scale amongst its 170K students and 5K staff. Furthermore, he will discuss how learning analytics is being adopted at other UK institutions, and what the implications for higher education might be.
eMadrid seminar on «Review and challenges in Learning Analytics»
1. Yifeng Jiang
Mobile: (+86)185-6666-8113
E-mail: jiangyifeng@sz.pku.edu.cn
EDUCATION
Peking University, M.S. in Computer Science and Technology Shenzhen, China
Recommended Student with Full Scholarship. Aug, 2014 ~ Jun, 2017
Beijing Institute of Technology, B.E. in Information Security and Countermeasure Beijing, China
Total Ranking: 1/66. Overall GPA:89.5 out of 100. Cum Laude. Sep, 2010 ~ Jul, 2014
Nanyang Technological University, Research Assistant Singapore
Exchange Student Scholarship. Mar, 2014 ~ Jul, 2014
Chung Yuan Christian University Zhongli, Taiwan
Exchange Student, School of Biological and Medical Engineering. Jul, 2012 ~ Aug, 2012
INTERNSHIP
Telecommunication and Information Security Lab, PKU Lab Member Aug, 2014 ~ Present
Teaching Assistant. Mainly researched in 2D-to-3D conversion and stereo vision. Attended international
technology workshops and academic conferences.
Rapid-Rich Object Search Lab (Rose Lab), NTU Lab Member Mar, 2014 ~ Jul, 2014
Research Group of Wechat (Tencent Co., Ltd): Assisted in accomplishing the retrieval function of the branded bags
on mobile terminal. Leveraging the popular Grab-cut technique implemented the image segmentation and
facilitated the user interaction.
Information Security and Countermeasure Lab, BIT Lab Member 2012 ~ 2013
Information Security and Countermeasure Competition: Organized the competition and participated in assigning
topics. Engaged in designing the logo and wrote the final competition report.
EXPERIENCE
Union Card, Shenzhen University Town Founder Sep, 2015 ~ Present
Created Union Card aiming for providing the faculties and graduates with the best catering and the most favorable
price in Shenzhen University Town. Over 30 noted merchants have joined us.
Student Maker Special Fund, Shenzhen Project Manager 2015
Automatically Planned UAVs path in three-dimensional scene considering terrain data, threat of weather,
performance parameters of UAVs, etc. Successfully passed the project defense and won the highest fund.
Graduate Student Union of Peking University, Shenzhen Campus Vice President Apr, 2015 ~ Present
Peking University Boya Financial Association, PHBS Outreach Minister 2014 ~ 2015
Conducted several major financial forums such as Weiming Lake Forum Series and Dialogue with Real Finance
Seminar Series, etc. Volunteered in many vital financial conferences held at Peking Univ. HSBC Business School.
Meritorious Winner, Mathematical Contest in Modeling, USA Team Leader 2013
Analyzed and addressed the problem brownie pan was uneven heated. Proposed several considerate approaches
to satisfy various users. Investigated in Paris Baguette, Starbucks and Christine. Wrote the dissertation.
Honorable Mention, Interdisciplinary Contest in Modeling, USA Team Leader 2012
With respect to the increasingly severe commercial criminal problem, based on semantic analysis, unveiled the
secret of the conspirators, and located the related suspects so as to chase the principal. Wrote the dissertation.
HONORS AND AWARDS
Peking University: Social Work Award (2014~2015), Deputy of PKU in Cross-Pacific Youth Initiative held in
Jeju (Jul, 2015), Delegate of Upperclassman in Opening Ceremony (Aug, 2015).
Beijing Institute of Technology: 6 times The People Scholarship 1st Place (Top 5%) (2011~2013), Hua Rui
Century Scholarship (Top 1%) (2012), China Aerospace Science & Industry Corp Scholarship (Top 1%) (2013),
Beijing Merit Undergraduate (Top 5%) (Jun, 2014), Deputy of Rose Lab in Global E3 annual meeting in SG.
PERSONAL
Computer Skills: MS Office, Prezi, C, C++, MATLAB, HTML, Assembly Language.
Language Skills: TOEFL, CET-6, Proficient in English, Experiences in TA, RA and CA overseas.
Hobbies: Fitness (three times a week), Running (Care Action in HK, 30km), Table Tennis (school team
member), Photography and post production, Remix of Music.