Research assistant. python, neural network.

N I K H I L D E E P A K D E S A I

864-***-**** ***************@*****.*** Clemson SC

OBJECTIVE

Proactive problem solver with excellent communication abilities and master’s degree in Computer Science. Looking to obtain an intern/co-op position to utilize exceptional research and statistical analytical abilities. Coming with strong interpersonal, leadership, and programming abilities. EDUCATION

Master of Science in Computer Science May 2021

Clemson University GPA: 3.83/4.0

Bachelor of Science in Computer Engineering May 2019 Mumbai University GPA: 3.33/4.0

WORK EXPERIENCE

Graduate Research Assistant at Clemson University Jun 2020 -Present o Collaborated with Motion planning lab and conducted research under Dr Ioannis Karamouzas o Plan, define, and execute autonomous driving vehicle using reinforcement learning o Controlled the autonomous car’s decision using lidar scan Data science intern at Kubixsquare Jun 2020 – August 2020 o Worked on bitcoin data scrapping, handling, manipulation, and data analysis. o Responsible for developing interactive graphs and visualizations using tensorboard. PROJECTS

Heart Disease Classification using supervised learning and Neural Networks Apr 2020 o Classified whether the patient has severe risk of heart disease or not o Used Supervised Algorithms like KNN, Logistic Regression, Decision Tree and Neural networks o Achieved an accuracy of 87% using a three-layer Neural Networks o Predicted the features likes Blood Pressure and diabetes having major impact on Heart Disease Controlling a 2D Robot using DQN and Convolutional Neural Network Mar 2020 o Developed and trained an Acrobot with two links using Deep Q learning o Actions space includes applying +1, 0 or -1 torque on the joint between two Acrobot links o Trained the Robot by passing the state as frame of images to the neural network o Used Epsilon Greedy strategy for the working of Acrobot using exploration and exploitation Deep Learning: Waste Disposal Image Classification Using Convolutional Neural Network Nov 2019 o The dataset was used from Kaggle, the system is highly recommended for binary classification o Dual layer of Convolution with Relu function was used to extract important features and tackle linearity o Max pooling of features is performed to prevent overfitting issues o Accuracy of around 90%was achieved by the CNN model Stock prediction using predictive analysis Feb 2019 o Developed the prediction model in python using LSTM (Long short-term memory) algorithm o The combination of technical and fundamental indicators was used as input o Predicted the information of the current trend of the stock o Suggested user whether the stock should be purchased or sold by analyzing the simple moving average Developed online platform (website) for local vendors using Web Technology Mar 2018 o Created a survey with the local vendors and understood their requirements o Tested the project using black box and white box testing o Worked as a backend developer using PHP and developed UML diagrams for interactions between the developers PROGRAMMING SKILLS

Programming Languages: Python(Pandas, NumPy, Matplotlib, Scikit-learn, Keras, TensorFlow), R, Java, JavaScript, C. Machine learning: Linear & Logistic Regression, SVM, Decision Tree, KNN, K-means, CNN, Naïve Bayes, NLP. Tools: MS Excel, Jupyter Notebook, JupyterHub, Google Colab, Anaconda, Plotly, OpenCV, Tensorboard. ACTIVITIES

Codex Committee member (June 2017 – June 2018)

Participated in Prakalp Technical paper presentation competition (Sept 2018) Member of SRC committee (Social Organization)

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