Data Scientist/ Machine Learning Engineer, Software Engineer

ANKITA RANE

Email: ************@*****.*** Phone: (469)–230 6943

LinkedIn: https://www.linkedin.com/in/ankita-rane-aa7391135 Location: Dallas, Texas, USA EDUCATION

University of Texas at Dallas, Richardson, USA (Jonsson Merit Scholar) August 2019-May 2021 Master of Science in Computer Science (Data Science Track) CGPA 3.9/4 Subjects Taken: Algorithm Design, NLP, Stats for Data Science, DB Design, Computer Vision

Birla Institute of Technology & Science, Pilani, Dubai, UAE (BITS Merit Scholar) August 2019 Bachelor of Engineering (Hons.) in Computer Science CGPA 8.7/10

Birla Institute of Technology & Science, Pilani, Dubai, UAE August 2019 Minor in Finance - Project Appraisal, Mgmt. & Accounting, Econometric Methods, Portfolio Mgmt. COMPUTER SKILLS

Programming: Python, Java, C, C++, C#, R, HTML, CSS, Bootstrap, Javascript, jQuery, AJAX, PHP Data Science: Tensorflow, Keras, Pandas, NumPy, OpenCV, Natural Language Processing, Data Mining, Git & Version Control Others: Tableau, MySQL, MongoDB, JDBC, Machine Learning, Neural Networks, NLTK, Unity, Linux (Ubuntu), Azure ML, Azure IoT WORK EXPERIENCE

Data Science Intern T-Mobile Inc, USA June 2020 – August 2020 Technical lead in developing IoT Connectivity product & POC – Smart Parking Management System. Implemented a robust Deep Neural Network model to detect vacant parking spaces in real-time using custom Mask-RCNN. Analyzed traffic data from parking lots and created a web dashboard to give insights based on time-series analysis. Developed an UI application to monitor parking vacancies. Deployed model on RaspberryPi and established connection with IoT Hub & Stream Analytics Job.

Marketing Data Analyst Intern Zomato, Dubai Jan 2019 - July 2019 Analyzed correlation between marketing strategies and Online ordering volume rates. Got trained on SEM strategies & SEO practices. Performed phrase-level analysis of popular keywords using Google Trends to optimize the website content that resulted in a higher page rank. Worked with social media analytics team to monitor engagement rates and social media strategies used.

Customer Technology Intern FedEx Express, Dubai June 2017 – July 2017 Developed Letter of Authorization toolbox using Visual Basic Studio. Also, worked on improvising Apology toolbox using Microsoft SharePoint. Analyzed weekly/monthly trends of IVR application users to increase automation performance. PROJECTS

Hidden Fortune – VR Maze game Jan 2020 – May 2020

Designed a single-player game to explore the maze and collect treasure using Unity. Implemented 3D travel and manipulation techniques using 5UDE and VRTK. Wrote player-object interaction scripts in C#. Added 3D sounds with reverberation & Doppler Effect. Sematic Textual Similarity (STS) Oct 2019 – Dec 2019

Designed and implemented a model to determine the similarity between 2 sentences. Extracted lexical and semantic level similarity using WordNet features (Synsets, POS tags, Dependency Parse, Action verb detection etc) and Word Sense Disambiguation. Model was ensemble on machine learning, heuristics and Doc2vec (Deep Learning model) based classifiers. Image Captioning using Deep Learning Sept 2018 – Dec 2018

Developed a Computer Vision based system to analyze images and generate accurate captions describing it. We make use of GANs to address exposure bias problem of Maximum Likelihood Estimation. An Intelligent Food Production Predictor using Machine Learning AI Hackathon (Sept 2018)

Analyzed world food production pattern for the past 50 years and built an AI algorithm to predict the food demands of the future population. Also created a website using HTML, CSS and Bootstrap to display the prediction results. Ship-Iceberg Classifier using Deep Learning Jan 2018 – May 2018

Analyzed Geo-spatial dataset containing satellite images of ship and iceberg. Adopted semi-supervised learning (pseudo-labelling) Approach to deal with scarcity of labelled samples. Achieved ship-iceberg classification accuracy of 95%. Sentiment Classification System for US Airline Service Analysis Sept 2017 – Dec 2017

Built a sentiment classifier to analyze tweets and classify them as positive, negative or neutral sentiment. Pre-processed the tweets using NLTK. Adopted Doc2vec approach to perform a phrase-level analysis of tweets. PUBLICATIONS

Ankita Rane and Dr.Vadivel Sangili, “Implementation of Improved Ship-Iceberg Classifier using Deep Learning”, Journal of Intelligent Systems (JISYS), July 2019.

Ankita Rane and Dr.Anand Kumar, “Sentiment Classification System of Twitter Data for US Airline Service Analysis”, IEEE Annual Computer Software and Applications Conference (COMPSAC), Tokyo, Japan, July 2018. ACHIEVEMENTS AND ACTIVITIES

Participated in Microsoft Hackathon 2020 – ASL Recognition System for T-Mobile Accessibility USA, July 2020

Winner at Artificial Intelligence Week Hackathon, Dubai IQPC, Sept 2018

Best Smart Artificial Intelligence Hack Team by Dubai Municipality UAE, Sept 2018

Arts & Culture Volunteer at Dubai Foundation for Women & Children UAE, July 2018

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