Machine Learning Reinforcement

Laxmi Tiwari

Kathmandu, Nepal • Tel: +*** 986-***-****• Email: ***********@*****.***• github:TiwariLaxuu Summary

As a graduate student, I am a committed and dedicated professional, I bring a strong work ethic and a passion for excellence to every project. I have 3+ years of hands-on experience on machine learning, mainly reinforcement learning implementation on different domain games, trading, ridesharing. This journey has not only honed my technical skills but has also involved extensive research, particularly delving into the intricacies of mathematics and algorithms. Work Experience

Jan 2022 AI Engineer Logictronix Technologies Lalitpur,Nepal

Review and research different github papers and find research gaps and algorithms.

Develop a model of risk minimization and profit optimization for High frequency Trading.

Dynamic parameter optimization for Algo-Trading

Implementing different Reinforcement Learning architectures and algorithms mostly TD algorithm(Q-Learning, DDQN, Sarsa) on FOREX Dataset(USDJPY) with multi-agents Take Profit(TP) and Stop Loss(SL) for Long Session and Short Session.

Use OHLC data to feature using technical indicators, momentum indicators and pre-processing and denoising techniques.

Evaluation Techniques: Profit, Loss, Win Ratio, Frequency of TP, SL, Gross Loss, Gross Profit

Hyperparameter Tuning, Regularization and Optimization

It is hosted live on Amazon Instance integrating with Oanda Api.

Currently working on Co-operative MARL, pymarl, AiGym library. Aug 2020 - Dec 2021 Research Engineer Nerdplatoon Bhaktapur, Nepal

I used a machine learning approach(XGBoost, SVM), for price prediction of old vehicles using different features of cars/vehicles. This application is live tested on the Canada Car Store.

March 2020 - Aug 2020 Research Intern Naamii Kathmandu, Nepal

I have implemented a non-deep learning and deep-learning approach to estimate the similarity scores between two images based on their visual contents, to serve for the retrieval-based visual localization. In this setting, between the two compared images, location of one (reference) image is known, whereas the location of the other (query) image is unknown. If two images are visually similar, the location of the query image is derived from that of the reference image. May 2020 - Present Committee Member Women in Big Data Nepal

■ Organize events, connect working professional women in data and encourage women in tech fields.

Education

2015-2019 Electronics and communication Engineering Tribhuvan University, Nepal 2022 Oxford Summer school Machine Learning (OXML-202*-****-**** Master in Financial Engineering WorldQuant University Relevant Skills

●TechnicalSkill:Python, Pytorch, Data Analysis, Data Wrangling, Research, Debugging code

●SoftSkill:Communication, Critical Thinking, Problem Solving

●Languages: Nepali, English

Professional Certifications

NEPAL ENGINEERS ASSOCIATION: REGISTER ELECTRONICS AND COMMUNICATION ENGINEER COURSERA

● DEEP NEURAL NETWORKS WITH PYTORCH

● NEURAL NETWORKS AND DEEP LEARNING

● IMPROVING DEEP NEURAL NETWORKS:HYPERPARAMETER TUNING, REGULARIZATION AND OPTIMAZATION

● STRUCTURING MACHINE LEARNING PROJECTS

Awards

2023: PROJECT VA AUTONOMOUS AGENTS HACKATHON

2023: MENTOR(TECH/ETHICS) TEENS IN AI

2022: TEAM LEAD IN DATA SCIENCE OLYMPIANS WOMEN IN BIG DATA 2021: REGIONAL AMBASSADOR- HACKMAKERS BUILDWITHAI-HACKATHON 2021: AWS MACHINE LEARNING SCHOLARSHIP UDACITY

2021: NOMINATED FOR WOMENTECH GLOBAL AWARDS WOMENTECH NETWORK 2020: NATIONAL WINNER DECLARED BY UNICEF PROJECT PANCHAKANYA COLD-STORE 2020: THEME WINNER IN TOURISM AND AGRICULTURAL FIELD TRIBHUVAN UNIVERSITY

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