Arun Gopal Govindaswamy

+1 (312) 927-6076 · agovind2@depaul.edu

Arun is a data science professional with 2+ years of academic research experience in machine learning, data science, computer vision, and artificial intelligence and 1.5 years of industry experience as a DevOps Engineer. Arun is passionate about applying machine learning and deep learning models to real-world applications. Arun has defended his master's thesis, published three research papers and has been awarded Research Assistantship twice during his graduate schooling . Arun's research interests are in the computer vision and deep learning space. Arun has collaborated with various stakeholders in the past and has held responsible positions during his research work. Arun is looking for positions such as Data Scientist, Machine/ Deep Learning Engineer, Computer Vision Engineer, AI Engineer, and Research/ Applied Scientist.


Experience

Graduate Research Assistant - Computer Vision and Machine Learning

Mar 2019 - Present
College of Computing and Digital Media, DePaul University
  • Working in the Medical Imaging Informatics (MedIX) research laboratory which focuses on medical imaging, image processing, computer vision, machine learning, data mining and knowledge discovery for healthcare, medicine, and biology related applications.
  • Worked on different research projects applying image processing, machine learning and computer vision techniques.
  • Colloborated with stakeholders, professors and students for project delivery.
  • Conducted research from brainstorming of ideas, literature surveying, implementation of methods and publishing of scientific papers.

IT Support Specialist

Sep 2019 - Present
Career Center, DePaul University
  • Responsible for continuous delivery of service demands, identifying opportunities to streamline vendor-supplied software through the use of IT and custom solutions, and enabling stable operation of technology components.
  • Identifying potential technical improvements; creating training materials and procedures to the users; training non-technical users.
  • Communicating realistic solutions to existing and potential issues with the the internal and external stakeholders.

DevOps Engineer

Dec 2017 - Feb 2019
Cognizant
  • Built continuous integration and continuous delivery pipelines by leveraging the CI/CD tools.
  • Collaborated with application development, application support and architecture team for application and environment related information.
  • Built and maintained configuration and deployment management scripts.
  • Worked with other teams to troubleshoot the issues related to CI/CD pipelines, configuration and deployment issues.
  • Built tools and processes to improve build and release management activities and also to improve team productivity.
Tools Used
  • CI/CD Tools: IBM UDeploy, Jenkins, Sonarqube
  • Analytical Tools: ElasticSearch, Kibana, Grafana
  • Scripting: Groovy, Shell, Java

Customer Service Provider

Aug 2017 - Dec 2017
Sitel India
  • Used company troubleshooting resolution tree to evaluate technical problems while leveraging personal expertise to find appropriate solutions.
  • Provided basic technical support for clients on a wide range of client products.
  • Promoted superior experience by addressing customer concerns, demonstrating empathy and resolving problems swiftly.
  • Effectively communicated with customers about account changes, new products or services, and potential upgrades.
  • Assessed caller accounts to determine benefits, identify service needs and resolve issues.
  • Facilitated inter-departmental communication to effectively provide customer support.

Publications

CNN as a feature extractor in Gaze Recognition

This research work was published at the Artificial Intelligence and Cloud Computing Conference (AICCC 2020). This work performs a thorough investigation of the two types of features used for image classification tasks - learned and hand-crafted features. This work also highlights the significance of convolutional neural networks in image classification tasks. Further, this work shows the significance of CNNs as a feature extractor. This work was a part of the NSF funded project.

GitHub PDF Publication

Predicting physician gaze in clinical settings using optical flow and positioning

This research work was published at The 35th conference on Image and Vision Computing (ICVNZ 2020). This work applies advanced image processing and machine learning techniques in the recognition of physician's gaze. This work uses video interaction and shows the applied methodology could reduce human labor in the annotation process and produces a gaze recognition tool capable of predicting physician gaze with 83% accuracy. This work was a part of the NSF funded project.

GitHub PDF Publication

Measurement of similarity in C. Elegans healthspan using dynamic time warping on movement features

This research work was published in the 12th International Conference on Bioinformatics and Computational Biology (BICoB 2020). In this work, the health-span of C elegans in the presence of a life-span extending mutation was explored. Various data analysis, data visualization, video analysis, and statistical techniques were performed in this work. This was a project conducted in collaboration with Rosalind Franklin University.

GitHub PDF Publication

Projects

Federated Learning in Gaze Recognition (FLIGR)

Master's thesis in federated learning - a new paradigm in deep learning and a clever idea of dealing with multi-institutional data without the need for data sharing.

GitHub PDF

Predicting progression in age-related macular degeneration (AMD) using drusen as a biomarker

The goal of this research project is to diagnose age-related macular degeneration (AMD), a common eye disease in the early stages using drusen as biomarkers. This work applies image processing techniques such as segmentation in identifying drusen and uses drusen characteristics and machine learning techniques in identifying the type of AMD.

GitHub PDF

Spoken letter recognition using machine learning

This work automatically predicts the English alphabets spoken by different subjects. The extracted cepstral coefficients are used as attributes and various machine learning techniques such as decision trees, ensemble methods are used in classifying. This machine learning model classifies spoken English alphabets with an accuracy of 93%.

GitHub PDF

HR Analytics

In this work, thorough data analysis was performed in the attrition data of a private company. Various data analysis techniques such as feature selection, dimensionality reduction, data exploration, and supervised learning techniques were performed.

GitHub PDF

Identification of posture in C. Elegans using Template Matching

This research work applies various image processing techniques on video data and identifies the postures of the nematode C. Elegans. The postures made by the nematode had biological implications on the lifespan and the healthspan of the microbe and accurate identification of postures were required.

GitHub PDF

Speech Emotion Recognition Using Tamil Corpus

A model that could identify the emotional state of the speaker was built. The emotions identified by the model were angry, sad, happy, fear and neutral. Audio samples from the tamil language were used as attributes for the model and the various prediction algorithms were used to train the model.

GitHub PDF

Education

DePaul University

Master of Science in Data Science
Computational Methods Track

GPA: 4.0

Mar 2019 - Jun 2021

BS Abdur Rahman University

Bachelor of Technology
Computer Science and Engineering

GPA: 3.44

Jul 2013 - May 2017

Leadership Experience

Graduate Student Ambassador

Aug 2019 - Present
College of Computing and Digital Media, DePaul University
  • Serve as representative of the Data Science Graduate Program for the College of Computing and Digital Media.
  • Assist prosepective/incoming students by answering questions about the college, the curriculum, and sharing personal experience directly useful to the students.
  • Pro-actively resolving students' queries about Data Science and DePaul University.

Campus Lead

Nov 2019 - Mar 2020
India Student Hub USA
  • The India Student Hub is a collaboration between the Education Team at the Embassy of India, Washington D.C., and Indian students on U.S. campuses. In this pilot project, more than 60 campus leads on over 40 campuses have volunteered to rally Indian students in the U.S. to take more ownership in building the India of their dreams. The Campus Lead is a competitive position that requires self-initiative, strong leadership and interpersonal skills, and once projects are underway, should impart considerable project management, facilitation, and resourcing experience. Learn more at https://ishubus.com

Joint Secretary

Jul 2015 - May 2017
Computer Science Department, BS Abdur Rahman University
  • Motivated and lead a team of other students and volunteers.
  • Fostered an environment of growth, leadership, learning and support within the Department.
  • Built the brand, increase volunteers, and promote engagement.
  • Reported quarterly to the CS Department, Advisory Council and faculty advisor.
  • Maintained a positive standing with the student organization regulatory body.
  • Established partnerships between the department and corporate partners, professors, staff, students, alumni, and outside organizations.
  • Managed an annual budget and seeked new ways to generate revenue to support organization's mission and values.
  • Effectively communicated with people at all level, including strong public speaking skills.

Skills

Programming Languages & Tools
Skillset
  • Deep Learning
    • Convolutional Neural Networks
    • Recurrent Neural Networks
    • Natural Language Processing
    • Computer Vision
    • Sequence Analysis
  • Data Science
  • Big Data and Engineering
  • Predictive Analytics
  • Data Visualization
  • Programming

Certifications

  • Google Certified TensorFlow Developer
    • Foundational principles of ML and Deep Learning
    • Building image recognition, object detection, text recognition algorithms with deep neural networks and convolutional neural networks
    • Using real-world images in different shapes and sizes to visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy
    • Exploring strategies to prevent overfitting, including augmentation and dropouts
    • Applying neural networks to solve natural language processing problems using TensorFlow
  • Certified Data Scientist with R
    • Domain understanding and knowledge extraction
    • Developing modeling solutions to support decision making
    • Implementation of solution to various domains
    • Overview of various domains like healthcare, finance, security, marketing, customer relationship management (CRM), and multimedia
    • Implementation of traditional statistical analysis
  • Business Analyst Using R
  • Machine Learning 202
  • R Prgramming Fundamentals

Contact

Give me a call or send me an email and I will get back to you as soon as possible!

+1 (312)-927-6076