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On Studying Computer Science - Shared screen with speaker view
Reem Alghamdi
10:21
good morning!
Xinge Yang
10:28
hello!
Yuchen Li
10:50
good everying?
Yuchen Li
11:01
Good evening!
Jerry Lu
11:44
Can we manually watch the video in YouTube and join the discussion later?
Xingdi Zhang
11:52
Good afternoon!
Markus Hadwiger
12:43
can you see the slides and hear the audio?
Shariq farooq
12:50
yes
Feng Liang
12:51
yes
Hussain Almajed
12:54
yes
Yuchen Li
12:55
perfect
Markus Hadwiger
13:23
awesome, thank you!
Reem Alghamdi
28:19
is the voice faster than the video?
Shariq farooq
28:33
I think so too
Konstantin Burlachenko
28:37
https://sites.google.com/site/burlachenkok/articles/ee263_fun_moments_with_s_boyd
Konstantin Burlachenko
28:42
EE 263. Fun moments in introduction to linear dynamic system Stephen Boyd
Xinge Yang
28:59
I think so
Konstantin Burlachenko
29:29
For whom it maybe interesting, S.Boyd is pretty fun teacher!
Reem Alghamdi
29:40
thank you!
Reem Alghamdi
29:55
I can recommend prof. Gilbert strang too! absolutely amazing!
Reem Alghamdi
30:03
even his book is fantastic
Shariq farooq
30:09
Thank you for the fun link @konstantin
Muhammad Sabirin Hadis
30:45
ty
Yuchen Li
35:41
Yes, I still remember the days that we freshman first studied linear algebra. The online linear algebra course from professor Gibert almost cover half of teaching time for we freshman lol~
Muhammad Sabirin Hadis
36:00
where can i get this speaker slide ?
Markus Hadwiger
40:34
I will send them later, as soon as I get them
Hussain Almajed
52:03
😂😂😂😂
yusuf
54:54
how do you narrow down your field if one is interested in many different fields of CS
Xinge Yang
55:17
you should write an email to peter as i think
Reem Alghamdi
55:19
I am also wondering..How to choose an area if undergrad is not an indication?
Xinge Yang
55:21
hah
Reem Alghamdi
55:35
I think he will answer after the talk
Yuchen Li
55:43
All in ai, yes~
Yuchen Li
55:48
233333
Shariq farooq
58:54
A few minutes ago, I was being told how Deep Learning is not everything and basically dumbs down research areas XD.
peter.wonka@kaust.edu.sa
59:09
It is difficult to pick a research area well, because no one knows all the areas really well and what they offer. It is just important to be intentional in your search.
Reem Alghamdi
59:27
He said the same thing. Having a good backbone (math+technical skills) is more importnat
Reem Alghamdi
59:44
learning deep learning without the basics is a recipe of disaster
peter.wonka@kaust.edu.sa
59:55
1) Talk to students in a research field and ask what they do day to day. What skills do they employ? How much do they program? Talk to professors
peter.wonka@kaust.edu.sa
01:00:18
2) Look at recent papers in top conferences as suggested
Shariq farooq
01:00:32
Yes, agreed. @Reem
Reem Alghamdi
01:00:50
Great talk!
Xiaochuan Gou
01:00:59
Thank you!
Shariq farooq
01:01:39
Thank you for the great talk!
Reem Alghamdi
01:03:32
is MS a good time to explore areas then decide in Phd? or should I decide in MS?
Shariq farooq
01:03:37
NO
Shariq farooq
01:04:33
Sorry for that “NO”. It was a typo!
Konstantin Burlachenko
01:06:07
How I can improve English skills?
Muhammad Sabirin Hadis
01:06:11
I like IoT but still confused, what area I pick if wanna take on computer science
Muhammad Sabirin Hadis
01:06:25
?
Konstantin Burlachenko
01:09:41
A lot of times we mention papers as output research. What about research software development? If I do software can I submit it to ML/AI conference? Or NIPS/ICML are pure paper-based?
Saleh Alqaryan
01:09:51
I am a non-thesis M.S. student and I am not sure if research is for me because I never tried it, how can I know? how can I find an advisor without any research expertise? Thank you
Reem Alghamdi
01:10:09
thank you!
Saleh Alqaryan
01:10:10
I am interested in a thesis^^
Reem Alghamdi
01:11:30
see engvid.com :D it is very good
Reem Alghamdi
01:11:34
for english
Roden Luo 罗登
01:12:24
As you mentioned Deep Learning is dominant now, how is the Deep Learning impact on Graphics research? Take my self: I’m doing nanoscale (biology) graphics and visualization. I know a bit of how to apply some basic ML or DL learning libraries to a dataset, but not much of the math background, also not much about the practical experiences. So, do you suggest I pay attention to deep learning or not, or should I play with more advanced learning models, or should I learn the more general math basics rather than focus on the advanced models? THANKS.
Konstantin Burlachenko
01:14:34
During the talk prof.P.Wonka mentioned that manage a lot of code and integrate own code, is any some extra advices?
Asaad Alghamdi
01:15:19
With most people going into Machine Learning research field, it is becoming more competitive to get accepted into top PhD programs abroad (as some manage to have 2-3 publications before starting their PhD). Would it be a wiser choice to go with more traditional CS research fields to focus more on quality work more than # of publications?
Asaad Alghamdi
01:16:01
Especially since publication in ML is follow a high pace since its at the spotlight now
yusuf
01:17:18
Is KAUST Ms program oriented more towards research or practical knowledge ?
Konstantin Burlachenko
01:20:26
Relationships with an advisor - what questions should be discussed with the advisor and what I should manage by myself to not overwhelm the advisor?
Asaad Alghamdi
01:21:27
What if I already have publications from my undergrad in unrelated research fields to what I am working on for my masters. How would that help?
Asaad Alghamdi
01:22:09
(In PhD admissions I mean)
Konstantin Burlachenko
01:23:30
How to read papers? Some papers are pretty long maybe there are some summarization resources, which performs summarization?
Asaad Alghamdi
01:23:46
https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf
Asaad Alghamdi
01:23:55
This is a good resource for how to read research papers
Muhammad Sabirin Hadis
01:24:33
tyyy
Shariq farooq
01:24:55
Follow researchers on Twitter!
Reem Alghamdi
01:26:03
thank you so much!
yusuf
01:26:23
Thank you :)
Asaad Alghamdi
01:26:39
Thank you for this cool seminar!
Markus Hadwiger
01:26:44
YouTube link of the talk: https://youtu.be/ln9pOPOCl9k