Mehak Piplani

Los Angeles, CA adjpdq@r.postjobfree.com 213-***-**** https://www.linkedin.com/in/mehakpiplani30/ https://github.com/mpiplani https://scholar.google.com/citations?user=deDXcpEAAAAJ&hl=en EDUCATION

University of Southern California, Los Angeles, CA January 2020–Present Master of Science, Computer Science (Data Science Specialization) GPA: 3.93/4 Courses: Deep Learning, Database Systems, Data Mining, Analysis of Algorithms, Artificial Intelligence Indian Institute of Information Technology, Vadodara, India August 2015–May 2019 Bachelor of Technology, Computer Science Engineering CGPA: 9.37/10 SKILLS

Programming Languages: Python, R, JavaScript, Java, HTML, CSS, Bootstrap, Angular, NodeJS, Express.js Tools, IDEs, and DBMS: MySQL, GIT, RStudio, Postgres SQL, Android Studio, Flask, Django, Jupyter Machine Learning: NumPy, Pandas, TensorFlow, Keras, PyTorch, GAN, RNN, LSTM, CNN, Azure, AWS Data Analytics and Visualization: Tableau, Excel, Python (Seaborn, Matplotlib) WORK EXPERIENCE

Graduate AI Researcher, USC, LA (Python, NumPy, Matplotlib, Reinforcement Learning) April 2020–July 2020

• Collaborated and supervised a team of 5 to design a Q learning agent to play tower defense game “Spurpunk” and classify levels as easy, medium, or hard.

• Utilized Generative Adversarial Networks (GAN) to generate unique hard levels as per agent’s performance. Deep Learning Research Intern, MIDAS LAB, India (TensorFlow, Pytorch, Keras, Sklearn, Pandas, nltk) December 2018–December 2019

• Assisted in building efficient speech to text pipeline with 85% accuracy to help people communicate better.

• Proposed a deep learning architecture (MMAMTL) for early-stage Acute Leukemia detection achieving 82% accuracy.

• Succeeded in designing an educational tool for automated formative and summative assessment of short answers to reduce load on teachers. [LINK]

Undergraduate Researcher, DA-IICT Speech Lab, India (KALDI, Python, Deep Learning, TensorFlow) May 2018–December 2018

• Worked on RNNLM-based Modelling solution bagging 5th position in 5th CHiME Challenge by achieving 72% WER.

• Led team by arranging meetings, coordinated with professor, resolved conflicts, and solved conceptual and technical issues. PUBLICATIONS

• DA-IICT/IIITV SYSTEM FOR THE 5TH CHIME 2018 CHALLENGE, CHIME WORKSHOP, INTERSPEECH 2018

• DEEP LEARNING FOR SPEECH EMOTION RECOGNITION, SPRINGER DEEP LEARNING BASED APPROACHES FOR SENTIMENT ANALYSIS 2019

• MIXUP MULTI-ATTENTION MULTI-TASKING MODEL FOR EARLY STAGE LEUKEMIA IDENTIFICATION, ICASSP 2020 PROJECTS

Web Technologies Project Summer 2020

• Deployed web application for products search using eBay API on Google Cloud Platform with Node.js (Express.js framework) at backend, and responsive UI through Bootstrap, Angular, CSS, and HTML. Little GO Game Agent (Python, Artificial intelligence) Spring 2020

• Coded a 5*5 GO game agent wining 85% games employing Minimax algorithm along with alpha-beta pruning. Twitter Data Wrangling [LINK] (Python, Matplotlib, pandas, requests, Tweepy API, Data Analytics) February 2019

• Gathered data from multiple sources and enhanced quality by merging and cleaning for analyzing trends. Prosper Loan Data Exploration [LINK] (Python, Seaborn, pandas, R, Data Visualization) January 2019

• Performed Exploratory Data Analysis on loan data by exploiting Univariate, Bivariate, and Multivariate Plots. Stock Prediction [LINK] (Python, Matplotlib, google finance client, Sklearn, Keras, Deep Learning) May 2018

• Developed a Long-short term memory (LSTM) model for price prediction of different stocks attaining R-Squared score of 0.96. AWARDS

• Gold Medal, Best Academic Performance in batch of 2015-2019.

• Chairperson Gold Medal, Best Academic Performance in University.

• Presented research work at Young Female Researchers in Speech Science & Technology Workshop (YFRSW) and got $800 grant for INTERSPEECH 2018.

LEADERSHIP

• Motivated and supervised students as Google Code-In Mentor 2018. [Certificate]

• Mentored students as Teaching Assistant for Operating Systems 2017.

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