Resume of Herambeshwar pendyala

1. Herambeshwar Pendyala
hpend001@odu.edu​ ​|​ ​linkedin.com/in/herambeshwar-pendyala-46b865104/​ ​|​github.com/Heramb001
Computer Science Graduate student. Actively​ ​looking for internship opportunities in an organization where I can put my problem solving and
decision making skills to make a significant business impact, gain practical experience and learn new technologies. Backend Developer (NLP
related) with ​2 years ​of experience working in agile methodology. My primary area of interest lies in leveraging machine learning techniques
to solve problems that make a business impact.
EDUCATION
Master of Science - Computer Science - ​Old Dominion University (ODU) ​(Jan 2019 – Dec 2020)
Bachelor of Technology - Electronics and Communication Engineering - ​Lovely Professional University (LPU) ​(Aug 2012 – May 2016)
TECHNICAL SKILLS
Programming Languages : ​Java, Python, C, C++, UNIX Shell Script, Assembly
Big Data Ecosystem​ ​:​ Spark, Hadoop, MapReduce, HDFS
Frameworks & Libraries​ ​:​ Numpy, Pandas, Matplotlib, Scipy, NLTK, Scikit-learn, Tensorflow, Keras, Django, OpenCV
Web technologies :​ HTML5, CSS3, Bootstrap, JavaScript, JSON, XML, PHP, Node JS, Express
Databases : ​Oracle 12c, SQL, MySQL, Mongodb
​Tools ​& ​IDEs : ​Eclipse, Microsoft Visual Studio code, WinSCP, PuTTY, Postman, SoapUI, SQL Developer, Toad​, ​GIT Cloud
​ ​PROFESSIONAL WORK EXPERIENCE
Graduate Research Assistant, ​Information Technology Services, Old Dominion University​ ( ​May 2019 – Present )
Developing Data,web related products for various departments in the university.
● Diva - Chatbot | Virtual Assistant : ​Developed a course chatbot that can answer basic questions related to the course. Accompanied
with a feedback system that helps improving the chatbot performance.​ ​Technologies : ​Google DialogFlow, Node JS, MySQL.
Graduate Research Assistant, ​Old Dominion University ( May 2019 - Aug 2019 )
● Parallel and distributed computing using raspberry pi cluster ​: ​Built a 4 node Raspberry Pi cluster to study about parallel and
distributed computing, implemented various algorithms that can be benefitted from parallel computing such as face detection,
Homographic encryption of images, Log mining. Comparing the performance by using multiple nodes. Framework : ​mpi4py, opencv
Graduate Teaching Assistant​, Old Dominion University ( Jan 2019 – May 2019 )
● Created semester project, a board game by implementing object oriented concepts in C++, programming quizzes and assignments.
Software Engineer​ – Tech Mahindra, Noida, India. ( Jul 2016 – Dec 2018 )
Done several POCs on Data Analytics, Machine learning applications in a way to help speed up deliverables.
● Skill Sphere | Data Analytic​s : ​Improved performance of model which ranks users based on technical skill set by parsing resume, using
information retrieval tools ​SOLR, Kibana ​and​ ElasticSearch​. ​Worked as a developer created a webservice using ​Python, Django​.
● Customer Query Clustering | Data Science : ​Built a k-means clustering model to categorize user queries, using NLP techniques like
TF-IDF​ for feature engineering on text data, packages like ​NLTK​ and ​scikit learn​. achieved 95% accuracy in categorizing the queries.
● EDGE - Dispatch and Scheduling Engine | Java : ​Role was to Automate the web services and microservices testing processes using
Java, Maven based framework, UNIX shell Scripts, tools like Postman and SOAPUI. Web scraping using selenium to perform UI
validations.
​PROJECTS (GRADUATE)
Learning Analytics - Predict Students at risk | Data Mining : ​Predicting failure rate of Student for a course. Performed data
cleaning, data preprocessing, Exploratory Data analysis and built machine learning model such as ​Random forest, Decision Tree, naive
bayes classifier​ and evaluated model performance using ROC curve. achieved 85% test accuracy Framework : ​Scikit-Learn, Weka​.
Automatic Hand Sign Detection | Deep Learning : ​Built a ​CNN(Convolution Neural Network) model ​from scratch that recognizes
sign language. Applied techniques of ​hyperparameter tuning, regularization, adam optimization to get an accuracy of 85% on a test set.
Framework : ​tensorflow
Happy House Challenge | Deep Learning :​ ​Built a ​CNN(Convolutional Neural Network) model​ to detect happy faces in the images
and achieved 95% test accuracy (and 99% train accuracy) using​ adam optimizer​. Framework : ​Keras
Chatbot | Deep Learning : ​Developed a chatbot with ​NLP ​techniques by building a ​Seq2Seq RNN(Recurrent Neural Network) model
on Cornell movie database which generates phrases that can be used as replies. Framework: ​tensorflow​.
ACHIEVEMENTS
Rated X (5/5), received ​Grand Salute LiveWire Award​, Tech Mahindra, f​or demonstrating technical proficiency and an unwavering
commitment to the brand and the organizational vision. ​Runner up ​LPU Project Expo, 2016, for an Innovative Project AVI (Assistant for
Visually impaired).