Editorial Office of Intelligent Computing at Zhejiang Lab

On January 3, 2023, I started work at Zhejiang Lab at the editorial office of Intelligent Computing: A Science Partner Journal.

My role, as a native speaker of English with a background in Computer Science and experience in academic publishing, is to help strengthen the reputation of the journal.

Zhejiang Lab (之江实验室) is a research institute established jointly by the Zhejiang Provincial Government, Zhejiang University, and Alibaba Group in September, 2017. (The name of the province is 浙江. That is, it uses a different ‘Zhe’ but the same ‘jiang’; the name of the lab is sometimes spelled ‘Zhijiang’.)

Intelligent Computing, launched in 2022, is an English-language Open Access Science Partner Journal published in affiliation with Zhejiang Lab and distributed by the American Association for the Advancement of Science (AAAS).

Want to know what my workplace is like? See below for some maps and photos of the lab campus.

Zhejiang Lab (ZJL)

Here’s the lab mascot. It’s an elf. (I don’t know why, but it seems that big companies in China all have cartoon mascots…) I don’t know if this thing has a name. Or a gender, for that matter. His/her/its hat is presumably meant to look like the logo of the lab.

Edit: The elf’s name is Xiaozhi (“Little Zhi”, sounds kinda like “Shao Juh”).

Yay science!

The lab campus is located in Yuhang District, not particularly close to any current Alibaba or Zhejiang University buildings. Here’s Nan Hu, the area where the lab is (satellite image from Baidu):

Edit: My apartment is in one of the buildings on the right edge of the image, just to the east of the lake. As of March 18, the tiny bridge is closed due to nearby construction for improving regional waterways.

Here’s a closer look at the lab campus:

Here’s a cartoon map of the lab campus:

Here’s a somewhat more realistic building map:

“Location Where You Are”

Edit: There’s something I bet you didn’t notice. It took me a while too. There is no Building 5. The numbers go from 1 to 4 and 6 to 11. The little grey building above Building 3 doesn’t have a number, and in any case you wouldn’t put Building 5 there. You’d put it just to the left of Building 6, a space partly occupied by sports facilities for soccer, basketball, and tennis. My guess, and this is pure speculation, is that there was a building planned, but the plan got torpedoed somehow or other, and it was decided not to renumber all the other planned buildings.

Incidentally, the campus sits on top of an invisible underground parking garage. I’ve only been in it twice, briefly, so I don’t know how big it is, but I half suspect it stretches all the way from one side of the campus to the other.

Edit: I’ve been in it a few more times. And I think it *does* cover the existing campus back to front and side to side. It would be so much fun to skate around in, if it weren’t for all the cars.

There are plans for more buildings (and another pond) to be built to the north and east of the existing Zhejiang Lab buildings. According to whoever made this architectural drawing, which I found on the ZJL website, eventually the campus will look like this:

Once more, with numbers:

As you may have guessed, this is the main building:

Here’s the pond:

Off to the east are the lab housing buildings, including the hotel:

Editorial Office of Intelligent Computing

Here’s the journal office, up on the 11th floor of the main building:

We have a fantastic view!

Unless it’s foggy, lol! But fog is special in its own way. Singapore doesn’t have fog.

Here’s a view facing east from the main building.

I love seeing mountains out my window.

Intelligent Computing is published continuously online, but here’s a printed collection of the first batch of articles:

Zhejiang Lab and Science solicited the opinions of experts to identify “10 Fundamental Scientific Questions on Intelligent Computing”. These stamps were created to celebrate their forward-looking achievement:

10 Fundamental Scientific Questions on Intelligent Computing

  1. How do we define intelligence and establish the evaluation and standardization framework for intelligent computing?
  2. Is there a unified theory for analog computing?
  3. Where will the major innovations in computing come from, and will quantum computing approach the computational power of the human brain?
  4. What new devices will be built (transistors, chip design, and hardware paradigms: photonics, spintronics, biomolecules, carbon nanotubes)?
  5. How could intelligent computing enable intelligent machines?
  6. How can we understand the storage and retrieval of memory based on the digital twin brain?
  7. What is the most efficient path to converge silicon-based and carbon-based learning?
  8. How to build interpretable and efficient AI algorithms?
  9. Can strong intelligent computing with features of self-learning, evolvability, and self-reflection be realized?
  10. How can we use real-world data to discover and generalize knowledge?

If you happen to be doing research relating to these open questions, consider submitting your work to Intelligent Computing, which publishes articles about: (1) Computing methodologies for machine intelligence; (2) Computational technology achieved through AI-based methodologies; and (3) Scientific findings achieved through machine intelligence, data, and computing methodologies.

» Intelligent Computing: A Science Partner Journal (mission and scope)