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followers: 11.0 following: 7.0 repos: 65.0 gists: 0.0

Name: Vadim Avkhimenia

Type: User

Company: University of Alberta

Bio: I am an Engineer and Data Scientist who is passionate about solving problems with data-driven approaches using DL, DRL, and mathematical optimization methods.

Location: Edmonton, AB, Canada

Blog: www.linkedin.com/in/vadimavkhimenia

👋 Hi, I’m @avkhimen. I am a Canadian Engineer and Data Scientist.
👀 I’m interested in applications of Deep Learning, Deep Reinforcement Learning, and mathematical optimization methods to problems in transmission and distribution systems. I am also actively following developments in economics, finance, and cryptocurrencies.
🌱 I’m currently learning how to apply cutting-edge multi-agent reinforcement learning algorithms to problems involving continuous action spaces.
💞️ I’m looking to collaborate on solutions to problems in finance, cryptocurrencies, engineering, and social sciences.
📫 I can easily be reached at [email protected] or [email protected].

Vadim Avkhimenia's Projects

altcoin_spike_clustering

Tool to cluster multiple altcoins and build a model to predict their spikes

automatic_git_populator

Script that will take a repository and using a language model will create commits that will be regularly posted to github

avellaneda_lee

Empirical testing of whether the trading strategy described in the 2008 Avellaneda-Lee paper may have been used in live trading

avkhimen.github.io

Personal website with career highlights, education, and work experience

bess_degradation_from_moving

Code for bess degradation curve when moving bess between substations

crypto_price_scraper

Jupyter notebook for scraping historical crypto prices from the Bittrex exchange

crypto_stocks_covariance_lag_analysis

Analyzing common crypto stocks for lag

crypto_trader

Repo for RL-based (and maybe others) trading agents

cwgan-gp-image-generation

Conditional Wasserstein GAN with gradient penalty for image generation trained with mnist dataset

cwgan-gp-time-series

Conditional Wasserstein GAN for synthetic time series genetaion

diet_cost_optimizer

Diet calculator designed to create a schedule for meals to minimize monthly food cost and ensure daily calories

electric_vehicle_charging_simulation

This project implements Q-Learning to find the optimal policy for charging and discharging electric vehicles in a V2G scheme under conditions of uncertain commitment of EV owners. The problem is modelled as a multi-objective multi-agent cooperative game. Project is part of fulfillment criteria for ECE 730 course at the University of Alberta.

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