SAPTHAGIRI VENKAT RAGHURAMAN

720-***-**** ac8ezp@r.postjobfree.com

MS Graduate (Computer Science) specializing in data science with 2 years of professional experience.

Strong understanding of Algorithms and Data Structures with experience in Python coding.

A computer enthusiast working constantly in enhancing the required skills for developing technologies.

ACADEMIC BACKGROUND

2017-2019 University of Colorado Denver.

Master of Science (M.S) in Computer Science. Expected Graduation: May 2019

2013-2017 R.M.D. Engineering College, Anna University, Chennai.

Bachelor’s in Engineering (B. E), Computer science & Engineering.

TECHNICAL SKILLS

Programming Languages: SQL, Python – Pandas, NumPy, SciKit learn.

Databases: PostgreSQL, MS Access, MYSQL, SQL Server, Oracle DB, MS Excel.

Tools: WebTMA, Tableau, SAS.

Framework: Hadoop - Spark, Pig, Hive, Mango DB, HBase, Kafka, Sqoop.

Cloud Service: AWS - IAM, EC2, S3.

Areas of Interest: Machine Learning, Data Structures.

PROFESSIONAL EXPERIENCE

AURARIA HIGHER EDUCATION CENTER (AHEC), DENVER, USA

ASSISTANT DATA SPECIALIST – SEPT 2017 to JAN 2019

Worked on the predicting the expenses of key systems with the dataset of key distribution to staffs and students using K-NN algorithm.

Assisting the database administrator by designing and maintaining spreadsheets and databases and also load the data in WebTMA tool and produce necessary analytical reports using SQL queries.

HEWLETT PACKARD ENTERPRISE (HPE), CHENNAI, INDIA

SOFTWARE DEVELOPER INTERN – JAN 2017 to JUNE 2017

Developed a software for active learning through integrated data exploration using ASP.NET connected to SQL Server for database where it, assists the users in discovering new interesting data patterns.

This application eliminates expensive exploratory queries with real-time experts rating the results. The back-end operation of this project was implemented in C#.Net.

ACADEMIC PROJECTS

FACILITATING THE PERSONALIZED MEDICINE BY PREDICTING THE OUTCOME OF GENETIC VARIANTS, DEC 2018 (MASTER’S PROJECT)

Developed an RNN system to classify the different types of mutation which leads to the growth of cancer tumor in human body from a text document. Genes and the variants were used for this classification.

The dataset used had real-time information on genes, variations, and the label of classes. Keras library function in python was used for this implementation which resulted in performance accuracy of 91%.

SCIENCE FICTION WRITER, OCT 2018

Built a science fiction writer using character level and word level Recurrent Neural Network. Three novels written by Jules Verne was used.

Three different novels were concatenated which were fed to the neural network to learn the writing structure by this great sci-fi legend. A vocabulary size of 5000 most frequent words by Jules Verne was used.

AMERICAN SIGN LANGUAGE RECOGNITION, MAY 2018

A system was developed to understand the signs of American Sign Language into the corresponding letters in English with the help of Convolution Neural Network based classifier.

The images of signs were captured in 5 different sessions, with similar lighting and background. A suitable CNN was built to do the classification well. TensorFlow was used for this implementation and achieved an accuracy of 96%.

FINGERPRINT CLASSIFICATION, APRIL 2018

Built a multi-class classifier from the non-linear support vector machines (RBF kernel) using the dataset which had fingerprint images. SVM library function in Python was used.

A checker program was written that takes fingerprint images as input and based on the trained model in the preprocessing step, it prints the identification number of the person. Checker program was used to see the test dataset’s performance resulting in performance gain of 82%.

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