Kumar Kshitij P. Profile

EXPLORE

0.0

(0 reviews)

You're now following

Error following user.

This user does not allow users to follow them.

You are already following this user.

Your membership plan only allows 0 follows. Upgrade here.

Successfully unfollowed

Error unfollowing user.

You have successfully recommended

Error recommending user.

Something went wrong. Please refresh the page and try again.

Email successfully verified.

$20 USD / hour

india

$20 USD / hour

It's currently 11:12 PM here

Joined August 24, 2017

0 Recommendations

Kumar Kshitij P.

@kishinmh

0.0

(0 reviews)

0.0

$20 USD / hour

india

$20 USD / hour

N/A

Jobs Completed

N/A

On Budget

N/A

On Time

N/A

Repeat Hire Rate

Machine Learning, optimization and AI Expert

I am a computer science major with interests in AI, Machine learning, optimization and Deep learning research. Having done many projects in these fields, I have a thorough knowledge of implementation intricacies, as well as ground result production for several tasks. Besides, I can work on many programming languages on different levels of computer architecture. I have a vast knowledge of cognitive science and psychology too.

See all Scientific Researchers in India

Contact Kumar Kshitij P. about your job

Reviews

Changes saved

No reviews to see here!

Experience

CS772 2017-18/I, IIT Kanpur, Kanpur, India

Aug 2017 - Present

• Preprocessed the simple wiki dataset, to make huge paraphrase dataset. • Implemented VAE for Paraphrase generation and Machine Translation.

PSY 789 2017-18/I, IIT Kanpur, Kanpur, India

Aug 2017 - Present

Studied the AI algorithms for sparse learning in machines.

CS773 2016-17/II, Summer 2017, IIT Kanpur, Kanpur, India

Jan 2017 - Aug 2017 (7 months, 1 day)

• Submitted to AAAI-18 for reviewing. • Conducted experiments for rUCB algorithm while establishing it as the best MAB algorithm for Sub-Gaussians. • Worked on a robust algorithm for contextual bandit setting. • Tested multiple linear bandit algorithms against there developed robust counterparts.