Akshay--a New Volunteer

[Akarsh Simha]

Hi Akshay

Nice to see you join team KStars! Akshay and I went to college together way
back in 2008 or so, and we used to be in the astronomy club together.

On a side note HiPS overlay is crawling on my friend’s 2019 MacBook Air and
after some time KStars hangs. Makes it unusable. Any idea what’s going on?

Regards
Akarsh


On Mon, Mar 17, 2025 at 09:21 Jasem Mutlaq <mutlaqja at ikarustech.com> wrote:

> Hello Akshay,
>
> Welcome abroad! I find that Machine Learning powered guiding is indeed
> very exciting but as you rightfully indicated, very challenging for a first
> time task! You are indeed correct, we used AI+RAG to answer FAQs and other
> knowledge based articles related to StellarMate.
>
> The binning statistics sound good. There are also many KStars issues
> reported here that would be of interest:
> https://invent.kde.org/education/kstars/-/issues
>
> Regarding the ML Guiding, I'm not sure if this is something we can
> crowdsource per se. My intuition is that it should learn on the user's own
> setup due to many contributing factors in seeing, mount, camera, and optics
> that can vastly differ from one user or another. It would be possible to
> start "training" after a guiding session is over for example, or while it
> is running, or in a special "train mode". At any rate, I am by no means an
> expert on this, so feel free to suggest a better model to approach this
> issue!
>
> --
> Best Regards,
> Jasem Mutlaq
>
>
>
> On Mon, Mar 17, 2025 at 4:52 AM Akshay Subramaniam <akshaysubr at gmail.com>
> wrote:
>
>> Hi all,
>>
>> Firstly, I want to say I really appreciate all of your work developing
>> kstars and INDI and for putting out a ton of education material as well.
>> And thanks for all the suggestions on how to get started. Just as a
>> warning, I've never contributed to a full stack application and have no
>> clue how frontend development works so I might be very slow to implement
>> things in kstars 😅
>>
>> The AI based guiding algorithm sounds fun but also daunting as a first
>> effort. I assume the biggest challenge would be inferencing the model in
>> real time faster than a single guide exposure at the very least. Maybe the
>> first step to tackle that would be to add a harness that outputs a bunch of
>> guiding data along with all the relevant mount parameters. That way, we can
>> crowd source data from people that would be willing to share. That would be
>> necessary to train a base model which folks can then finetune that model
>> for their specific mount either as an offline step or on the fly. I'd also
>> imagine there would need to be some guardrails around the predicted guiding
>> pulses just so things don't go off the rails because of some instability
>> mode of the model. Another idea is a simple LLM+RAG model that a kstars
>> user can chat with to answer simple questions like "What should my meridian
>> flip settings be for an OnStep based mount?". I believe Jasem and the
>> Stellarmate folks already have something similar and it can even take
>> actions based on natural language commands!
>>
>> The binning conditional statistics enhancement seems like a simpler
>> starting point so I can maybe start with that.
>>
>> Thanks,
>> Akshay
>>
>> On Sun, Mar 16, 2025 at 6:10 PM Hy Murveit <murveit at gmail.com> wrote:
>>
>>> Akshay,
>>>
>>> and I'll throw one in too, related to John's suggestion. How about a
>>> adaptive guider based on machine learning? E.g. it decides on the
>>> correction pulses based on how well recent pulses have corrected the guide
>>> error--so presumably learns about periodic error and backlash. I suppose it
>>> could be pre-trained and/or adapting on the fly, or more likely both. I'd
>>> be happy to collaborate on that.
>>>
>>> Hy
>>>
>>>
>>> On Sun, Mar 16, 2025 at 1:28 PM John Evans <john.e.evans.email at gmail.com>
>>> wrote:
>>>
>>>> Hi Akshay,
>>>>
>>>> Welcome to the project, great to have you on board!
>>>>
>>>> I had a quick look at the links Hy enclosed and see you’re working on
>>>> AI related topics. I’m sure there are some interesting things in this area
>>>> that could be brought to KStars. I personally know very little about this
>>>> field but would be very interested to collaborate if you think it would be
>>>> appropriate.
>>>>
>>>> Regards,
>>>> John.
>>>>
>>>> On 16 Mar 2025, at 18:53, Hy Murveit <murveit at gmail.com> wrote:
>>>>
>>>> 
>>>> Folks,
>>>>
>>>> I bumped into Akshay (cc'd) today at a local astro-club function.
>>>>
>>>> Akshay is an aeronautical engineer at NVidia, with a PhD in physics
>>>> from Stanford
>>>> and a KStars user, who's interested in contributing to our project.
>>>> If you have any suggestions on projects which might help start to
>>>> contribute, please feel free to reach out to him at
>>>> akshaysubr at gmail.com
>>>>
>>>> https://developer.nvidia.com/blog/author/akshay-subramaniam/
>>>> https://scholar.google.com/citations?user=hNhELoYAAAAJ&hl=en
>>>>
>>>> Hy
>>>>
>>>> Hey Hy,
>>>>
>>>> Nice meeting you today and I really enjoyed our chat. You mentioned a
>>>> kstars framing workflow video you had made, I’d love to watch that
>>>> incorporate that into my process.
>>>>
>>>> Also, I’m enthusiastic about contributing to kstars/ekos. If anything
>>>> specific comes up, let me know. Maybe something simple to start with so I
>>>> get a bit more familiar with the kstars development process before trying
>>>> to tackle anything more complicated. I was thinking adding an offset
>>>> between plate solving and the mount location might be a nice easy one so
>>>> one could use a guide camera and finder scope for plate solving with the
>>>> main scope used for visual.
>>>>
>>>> Thanks,
>>>> Akshay
>>>>
>>>>
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