關於 uc berkeley computer science ，我們在網路上蒐集到這些相關的討論、資訊與評價

TOP 5 ĐẠI HỌC THẾ GIỚI TRONG TỪNG LĨNH VỰC!

Các bạn có từng tự hỏi trong vô số các ngành nghề thì có phải ngành nghề nào top 1 cũng là Harvard, Oxford hay Cambridge không? Thật ra thì mỗi đại học có những thế mạnh khác nhau đó, ví dụ Harvard thì quá sức nổi bật với trường kinh doanh, Johns Hopkins thì nổi tiếng với Y khoa, MIT thì quá sức nổi bật với ngành khoa học máy tính hay Wharton (University of Pennsylvania) thì luôn nổi tiếng với Tài chính. Hôm nay chị sẽ tổng hợp top 5 đại học trên thế giới ở mỗi lĩnh vực, theo QS ranking, nhé. ;)

KINH DOANH:
1. Harvard (US)
2. INSEAD (France)
3. London Business School (UK)
4. Massachusetts Institute of Technology [MIT] (US)
5. University of Pennsylvania (US)

KINH TẾ:
1. Harvard (US)
2. MIT (US)
3. Stanford (US)
4. University of California, Berkeley (US)
5. University of Chicago (US)

TÀI CHÍNH:
1. Harvard (US)
2. MIT (US)
3. Stanford (US)
4. Oxford University (UK)
5. London School of Economics and Political Science (LSE) (UK)

KHOA HỌC MÁY TÍNH (Computer Science):
1. MIT (US)
2. Stanford (US)
3. Carnegie Mellon (US)
4. UC Berkeley (US)
5. Cambridge University (UK)

LUẬT:
1. Harvard (US)
2. University of Oxford (UK)
3. University of Cambridge (UK)
4. Yale (US)
5. Stanford (US)

QUẢN LÍ NHÀ HÀNG KHÁCH SẠN (Hospitality):
1. Ecole hôtelière de Lausanne (Switzerland)
2. University of Nevada - Las Vegas (US)
3. Les Roches Global Hospitality Education (Switzerland)
4. Glion Institute of Higher Education (Switzerland)
5. The Hong Kong Polytechnic University (Hong Kong)

NGÔN NGỮ HỌC (Linguistics):
1. MIT (US)
2. University of Massachusetts Amherst (US)
3. University of Maryland (US)
4. University of Edinburg (UK)
5. Harvard (US)

NGHỆ THUẬT & THIẾT KẾ:
1. Royal College of Art (UK)
2. University of the Arts London (UK)
3. Parsons School of Design at The New School (US)
4. Rhode Island School of Design (US)
5. MIT (US)

Y KHOA:
1. Harvard (US)
2. Oxford (UK)
3. Cambridge (UK)
4. Stanford (US)
5. John Hopkins (US)

DƯỢC:
1. Oxford (UK)
2. Harvard (US)
3. Monash University (Australia)
4. University of Toronto (Canada)
5. UC San Francisco (US)

KỸ THUẬT (Engineering):
1. MIT (US)
2. Stanford (US)
3. ETH Zurich - Swiss Federal Institute of Technology (Switzerland)
4. Cambridge (UK)
5. UC Berkeley (US)

CHÍNH TRỊ & QUAN HỆ QUỐC TẾ:
1. Harvard (US)
2. Oxford (UK)
3. Sciences Po (France)
4. LSE (UK)
5. Cambridge (UK)

THỂ THAO:
1. Loughborough University (UK)
2. University of Queensland (Australia)
3. University of British Columbia (Canada)
4. University of Sydney (Australia)
5. University of Toronto (Canada)

<3 Like page, tag và share cho bạn bè để không bao giờ lỡ info hay nhé <3

#HannahEd #duhoc #hocbong #sanhocbong #scholarshipforVietnamesestudents

【Talk】Prof. Zhengya Zhang (U Michigan): Neuromorphic Computing Using Sparse Codes: From Algorithm to Hardware (July 16, 2015(Thursday, 10:30am-12pm)

Invite you all to join it. 歡迎踴躍參加 !

Title: Neuromorphic Computing Using Sparse Codes: From Algorithm to Hardware

Date: July 16, 2015 ( Thursday, 10:30 am ~ 12:00 pm)

Place: ED528, 5F, Engineering Building 4, NCTU
交通大學(光復校區)工程四館5樓528室

Speaker: Prof. Zhengya Zhang (University of Michigan, Ann Arbor)

Abstract:
Some of the latest advances in computer vision have been built upon the understanding of the mammalian primary visual cortex (V1). The receptive fields of V1 neurons can be compared to the basis functions underlying natural images. Learning the receptive fields allows us to carry out complex vision processing, including efficient image encoding, feature detection, and classification. Sparse coding is one development in unsupervised machine learning for training a network of neurons using natural images to extract the receptive fields that resemble the V1 receptive fields. We explore the dynamics of the sparse coding algorithm for an efficient mapping onto practical hardware. Design considerations involving tuning network and neuron responses have a significant impact on the neuron spiking pattern that determines the fidelity of image processing and the efficiency of resource utilization. The spiking pattern can be further exploited to improve the performance and scalability of the hardware architecture. The soft neural computation is intrinsically error tolerant and many opportunities exist in approximating the neuron communication and computation in designing high-performance and energy-efficient image processing hardware.

Biography:
Zhengya Zhang received the B.Sc. degree from the University of Waterloo in Canada in 2003, and the M.S. and Ph.D. degrees from the University of California, Berkeley, in 2005 and 2009, respectively. Since 2009, he has been with the Department of Electrical Engineeringand Computer Science at the University of Michigan, Ann Arbor, where he is currently an Associate Professor. His research is in the area of low-power and high-performance VLSI circuits and systems for computing, communications and signal processing. Dr. Zhang received the Intel Early Career Faculty Award in 2013, the National Science Foundation CAREER Award in 2011, the David J. Sakrison Memorial Prize from UC Berkeley in 2009, and the Best Student Paper Award at the Symposium on VLSI Circuits in 2009. He is an Associate Editor of the IEEE Transactions on Circuits and Systems-I, II, and the IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

Host: 交大電子系楊家驤教授 Email: chy@nctu.edu.tw

[Free Symposium]2013 NCTU-UC Berkeley I-RiCE Bilateral Symposium on III‐V/Si Heterogeneous Integration for Next Generation Microelectronic Applications

Time : 09:00 a.m.-17:30 p.m., Friday September 13, 2013
Location: Conference Room 100, MIRC, National Chiao Tung University(交通大學電子資訊研究大樓國際會議廳)
Registration : Before September 12, 2013. Please visit http://goo.gl/WuDAxP to register. This Symposium is free of charge.

Please visit http://www.ee.nctu.edu.tw/News/ShowArticle.php?Number=1043 to find the detailed information.

Agenda :

09:00-09:30
Registration

09:30-09:40
Opening Remarks
Prof. Edward-Yi Chang
Dean of Research and Development
Professor, Department of Materials Science and Engineering; Department of Electronics Engineering, NCTU, Taiwan


Session Chair: Prof. Steve S. Chung (NCTU)
09:40-10:40
Subject : FinFET and Thin Body Transistor
Prof. Chenming Hu
Professor, Department of Electrical Engineering and Computer Sciences, UC Berkeley, USA

10:40-11:00
Coffee Break

11:00-12:00
Subject : On the Possibility of a Negative Capacitance Transistor for Low Power Electronics
Prof. Sayeef Salahuddin
Professor, Department of Electrical Engineering and Computer Sciences, UC Berkeley, USA

12:00-13:30
Lunch

Session Chair: Prof. K. N. Chen (NCTU)
13:30-14:10
Subject : InAs QWFET for Terahertz and Post CMOS Device Applications
Prof. Edward-Yi Chang
Dean of Research and Development
Professor, Department of Materials Science and Engineering; Department of Electronics Engineering, NCTU, Taiwan

14:10-14:50
Subject : High Mobility Ge Channel MOSFETs Directly on Si
Prof. Chao-Hsin Chien
Professor, Department of Electronics Engineering, NCTU, Taiwan

14:50-15:10
Coffee Break

Session Chair: Prof. H. C. Lin (NCTU)
15:10-16:10
Subject : La2O3 Gate Dielectrics for InGaAs Channel: Interface Control and Scalability
Prof. Kuniyuki Kakushima
Professor, Department of Electronics and Applied Physics, Tokyo Institute of Technology, Japan

16:10-16:50
Subject : Analysis of Germanium UTB/FinFET Logic Circuits and SRAM Cells
Dr. Vita Pi-Ho Hu
Assistant Researcher, Department of Electronics Engineering, NCTU, Taiwan

16:50-17:30
Closing Remarks

今天巧遇來 Google 借廁所看烏龜的哈佛姐 Alice
雖然廁所沒上到，免費的飯也沒吃到，但是卻從訪談中認識到學霸轉職的心路歷程其實不如大家預期的輕鬆！哈佛姐這次也在訪談中提到許多tips 跟建議，希望對於想轉職軟體工程師的你有所幫助～

哈佛姐的影片：https://youtu.be/P8X5-LoaCis

這集會聊到...

💬 Overview 💬
💙 哈佛姐是誰 0:55
💙 如何去常春藤名校 2:35
💙 學霸兒時夢想就很驚人 4:03
💙 哈佛 vs 博客來 4:45
💙 學霸轉職心得 6:03
💙 工程師職涯規劃 6:39
💙 讀書有用嗎 7:45
💙 為何要讀那麼多學位 9:14
💙 轉職需要學位嗎 9:40
💙 想跟剛進哈佛的自己說什麼 10:50
💙 遊完矽谷，哈佛姐想夢遊 __? 12:10

👇🏻 哈佛姐夢遊矽谷 AliceInSiliconWonderland 👇🏻
https://www.youtube.com/channel/UCB9ryAh6vhavNxALJUJT6-Q


📢 📣 📢 本頻道影片內容有輸出成 podcast 📢 📣 📢
可以在各大podcast平台搜尋「Untyped 對啊我是工程師」
請大家多多支持呀！！🙏🏻💁🏻‍♀️

#哈佛姐 #讀書有用嗎 #哈總統
一定要看到影片最後面並且在「YouTube影片下方」按讚留言訂閱分享唷！

【愛屋及烏】
YouTube 👉 https://www.youtube.com/c/Untyped對啊我是工程師
Podcast 👉 https://open.spotify.com/show/3L5GRMXmq1MRsliQt43oi2?si=3zgvfHlETeuGfp9rIvwTdw
Facebook 臉書粉專 👉 https://www.facebook.com/untyped/
Instagram 👉 https://www.instagram.com/untypedcoding/
合作邀約 👉 untypedcoding@gmail.com
-
Untyped 對啊我是工程師 - There are so many data types in the world of computer science, so are the people who write the code. We aim to UNTYPE the stereotype of engineers and of how coding is only for a certain type of people.
凱心琳: 一個喜歡電腦科學邏輯推理，在科技圈努力為性別平等奮鬥的工程師。