PRATHIKSHA BALAKRISHNA

San Marcos, TX ***** • 630-***-**** • adc7kc@r.postjobfree.com

www.linkedin.com/in/prathiksha-balakrishna

https://github.com/Prathiksha-Balakrishna

SOFTWARE ENGINEER

I am a self-driven professional who is enthusiastic about designing, developing, and delivering innovative software solutions to resolve complex challenges and attain business goals. I am eager to leverage my recent software development experience, strong academic foundation, and collaborative work ethic to complete high-quality technical projects. CORE COMPETENCIES

Software Development • Machine Learning • Web Application Design • Scientific Analysis • Mathematical Modeling Research • Cloud Computing • Project Management • Technical Problem Solving • Collaboration • Strong Communication EDUCATION

5/2020 TEXAS STATE UNIVERSITY SAN MARCOS, TX

Master of Science, Computer Science

• Relevant courses include Design & Analysis of Algorithms, Database Design & Theory, and Advanced Software Engineering Project.

• Completed project to detect malicious URLS using deep networks. Analyzed logistic regression performance via bigrams, CNN, and CNN-LSTM models to detect phishing URLs. Used Python as language, TensorFlow with keras, and Sklm as algorithms. 2017 SRI JAYACHAMARAJENDRA COLLEGE OF ENGINEERING MYSURU, KARNATAKA Master of Computer Applications, Computer Applications 2014 AMRITA SCHOOL OF ARTS AND SCIENCES MYSURU, KARNATAKA Bachelor of Computer Applications, Computer Applications EXPERIENCE

12/2019-

Present

TEXAS STATE UNIVERSITY SAN MARCOS, TX

Graduate Research & Teaching Assistant

• Promoted to supervise 20 instructional assistants across C++, Data Structures, and Algorithms courses; delegate responsibilities and attend courses to provide performance feedback.

• Cultivate students’ ability to program by leading weekly course labs. Prepare and present brief lecture to introduce lab procedures and monitor individual progress towards completion.

• Guide learners through analyzation and resolution of technical programming issues in assignments; record errors for weekly grading.

• Leverage in-depth technical knowledge and strong communication skills to deliver high-quality and informative assistance to undergraduate and graduate students during tutoring hours. 12/2018-

12/2019

TEXAS STATE UNIVERSITY SAN MARCOS, TX

Graduate Instructional Assistant

• Facilitated impactful learning outcomes for students in C++, Data Structures, and Algorithms courses by deploying quality instruction and assistance to ensure learners accurately completed lab assignments.

• Provided technical support to professors and other lab leads for all graduate and undergraduate levels. 8/2017-

7/2018

ACCENTURE SOLUTIONS PRIVATE LIMITED BENGALURU, KARNATAKA Associate Software Engineer, Smart Hub Team

• Collaboratively spearheaded research & development projects, delivering robust machine learning and AI solutions intended for company’s US-based clients. Assisted in resolution of real-time problems such as crowd detection and worker safety.

• Designed, developed, and modified software; ensured optimal systems by using scientific analysis and mathematical models to accurately predict and measure design outcome/consequences.

• Strengthened machine’s problem-solving capabilities by training and testing existing/customized models appropriate for the identified challenge.

• Technical Tools/Languages used: Python as programming language, AWS, and OpenCV and Tensor-flow tools for video analytics.

TECHNICAL

• Languages: C++, Python, Java

• Web Technologies: HTML, CSS

• Database: MYSQL

• Tools & Software: MATLAB, Putty, SSH, OpenCV, Tensor-flow, AWS

• Operating Systems: macOS, Windows, Linux

ADDITIONAL ACADEMIC PROJECTS

• MCA Department Portal: Developed portal to access department-wide resources such as faculty member information, student grades, attendance, and announcements. PhP used as frontend and SQL as backend.

• Different segmentation techniques for a crop extraction from its background: Segmented Oil Palm crop bunch from tree image capture under natural environment. Explored different segmentation methods including Means clustering, Fuzzy C Means (FCM), Expectation – Maximization (EM), and Random Walk. Performance was evaluated using parameters such as Correlation, Jaccard coefficient, True Positive Rate

(TPR), and Dice coefficient. Concluded using newly created dataset of 200 images for demonstration.

• Design of algorithms to address signature samples' recognition and verification, and intrapersonal signature verification problems: Addressed signature variations using Grid application, PCA for feature extraction, and SVM and MLP for classification, for which MATLAB was used. PUBLICATIONS

• Deep Learning Approach for Enhanced Cyber Threat Indicators in Twitter Stream o https://arxiv.org/abs/2004.00503

• Deep Learned Based Frameworks for Handling Imbalance in DGA, Email, and URL Data Analysis o https://arxiv.org/abs/2004.04812