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.
kuopio, finland
It's currently 9:06 PM here
Joined August 16, 2015
0 Recommendations
Taha N.
@abdelhalimnakabi
3.0
3.0
100%
100%
kuopio, finland
80%
Jobs Completed
100%
On Budget
100%
On Time
N/A
Repeat Hire Rate
Machine learning Ops expert
Contact Taha N. about your job
Log in to discuss any details over chat.
Portfolio
Portfolio
Check my website for portfolio
Check my website for portfolio
Reviews
Changes saved
Showing 1 - 4 out of 4 reviews
$555.00 USD
Python
Algorithm
Software Architecture
CUDA
Machine Learning (ML)
F
•
$190.00 USD
Python
Data Processing
Machine Learning (ML)
•
$1.00 USD
Python
Matlab and Mathematica
Machine Learning (ML)
Data Science
+1 more
•
$15.00 USD
Matlab and Mathematica
Statistics
Research Writing
Statistical Analysis
SPSS Statistics
M
•
Experience
Data scientist
Jan 2017 - Present
Implementing algorithms for simulation data analysis
Implementing a recommender system for VR content
Python developer
Jan 2016 - Dec 2016 (11 months, 1 day)
Implementing financial indices' calculations in a Python framework and automating the daily calculation and publication
Education
PhD in AI for smart grids
(3 years)
Master of science
(5 years)
Publications
Computational intelligence for smart grid’s flexibility
Itä-Suomen yliopisto
Recent advances in artificial intelligence (AI) and machine learning (ML) are influencing many aspects of today’s society. The success of AI is a result of the availability of large amounts of data and high computational power. The advances of AI technology can contribute to the next revolution in the most vital asset of the modern life: electricity.
Optimal price-based control of heterogeneous thermostatically controlled loads under...
F1000Research
In this paper, we consider the problem of thermostatically controlled load (TCL) control through dynamic electricity prices, under partial observability of the environment and uncertainty of the control response. The problem is formulated as a Markov decision process where an agent must find a near-optimal pricing scheme using partial observations of the state and action. We propose a long-short-term memory (LSTM) network to learn the individual behaviors of TCL units...
Computational intelligence for demand side management and demand response programs in smart grids
8th International Conference on Bioinspired optimization methods and their applications
The reliability of a power system relies more on its flexibility, which is no longer easy to achieve on the production side because of the large integration of renewable energy sources. With the advances in smart grids, demand side management can achieve this flexibility by making customers participate in demandresponse programs. In this paper, we mainly discuss a variety of techniques mostly relying on computational methods to implement efficient demand response programs...
Deep reinforcement learning for energy management in a microgrid with flexible demand
Sustainable Energy, Grids and Networks
In this paper, we study the performance of various deep reinforcement learning algorithms to enhance the energy management system of a microgrid. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a set of thermostatically controlled loads, a set of price-responsive loads, and a connection to the main grid...
An ANN-based model for learning individual customer behavior in response to electricity prices
Sustainable Energy, Grids and Networks
In this paper, we consider the problem of learning the electricity consumption patterns of an individual residential electricity customer, in response to electricity price signals in a demand response program. Two new methods are presented for predicting the hourly loads using the outdoor temperatures, electricity prices and previous loads...
Contact Taha N. about your job
Log in to discuss any details over chat.
Verifications
Top Skills
Browse Similar Freelancers
Browse Similar Showcases
Invite sent successfully!
Thanks! We’ve emailed you a link to claim your free credit.
Something went wrong while sending your email. Please try again.
Copy to clipboard failed, please try again after adjusting your permissions.
Copied to clipboard.
Loading preview
Permission granted for Geolocation.
Your login session has expired and you have been logged out. Please log in again.