Shantanu Gupta is a data intelligence and cloud developer with over 5 years of experience in data analysis, cloud computing, and web development. He is currently pursuing opportunities in machine learning and data science. He holds an MS in Computer Engineering from Arizona State University and a BTech in Information Technology from Harcourt Butler Technical University in India. His skills include programming languages like Python, Java, and SQL as well as tools like AWS, Spark, and TensorFlow. He has worked on projects involving computer vision, pattern recognition, and predictive analytics.

1. SHANTANU GUPTA
1255 E University Dr Apt 336, Tempe, Arizona 85281 | 612 991 9234
shantanu10193@gmail.com
LinkedIn: https://www.linkedin.com/in/shantanugupta7 | GitHub: https://github.com/shantanu-93
BRIEF OVERVIEW
Highly motivated professional with 5 years of relevant industry experience in Data Analysis, Cloud Computing and
Web Development. Actively looking for opportunities in Machine Learning and Data Science intern roles.
EDUCATION
Master of Science in Computer Engineering Aug 2019 – May 2021
Arizona State University, Tempe AZ GPA: 3.33/4.0
Bachelor of Technology in Information Technology Aug 2010 – May 2014
Harcourt Butler Technical University, Kanpur India GPA: 3.5/4.0
SKILLS
Programming: Java, Python, SQL, JavaScript
Tools & Technologies: AWS EC2, S3, SQS, Lambda; Hadoop, Spark, Git, ELK, REST, Flask, MongoDB, PostgreSQL
Machine Learning Libraries: TensorFlow, Keras, scikit-learn, OpenCV, Pandas, NumPy, matplotlib
PROFESSIONAL EXPERIENCE
Data Intelligence and Cloud Developer | ASU Cloud Innovation Center | Scottsdale AZ March 2020 – Present
- Utilizing AWS cloud services in Big Data, Analytics and Machine Learning to build prototypes for smart city
initiatives in a collaboration between ASU & Amazon.
- Developing a Tempe city Graffiti Abatement project by real-time analysis of moving vehicle camera recordings for
automatic graffiti detection using Deep Learning and Computer Vision models and geotagging for further action.
Senior Associate Technology | Publicis Sapient | Minneapolis MN June 2018 – July 2019
- Cut majorlosses to the company in the range of $100K per week on online orders by fixing complex, long pending
production issues by identifying patterns in faulty orders.
- Prototyped Proof of Concepts for modern headless architecture application leading to a successful global launch
in more than 80 countries.
- Saved business owners 4 hours per day by creating data visualization application for stakeholders to make
informed decisions regarding inventory needs and revenue forecasting backed by statistics.
Associate Technology | Publicis Sapient | New Delhi IN August 2014 – May 2018
- Speeded up website load time 3X by designing a database index scan of more than 15M records in Couchbase
Server. Boosted performance of the e-commerce platform with SQL optimization.
- Slashed customer care call volume by 40% about shipment queries by integrating FedEx Service into checkout
process providing real-time delivery estimate and online tracking capability using RESTful web services.
- Enhanced business processes by developing back order management capability into online portal for business
admins and sales reps. Helped users track open orders data online instead of backend SAP management system.
ADDITIONAL PROJECTS
Object Detection Using Raspberry Pi and AWS January 2020 – March 2020
- Developing video surveillance system to detect objects from videos in real time using edge and cloud computing.
- Using Raspberry Pi based IoT for on-device detection implementing lightweight YOLO Computer Vision models.
- Using cloud-based services for scalable real-time detection using AWS compute, storage and messaging services.
Fitness Tracking from Sensory Data August 2019 – November 2019
- Performed sensory data analysis from fitness trackers to recognize and monitor the day-to-day human activities
such as walking, eating, sleeping using Machine Learning algorithms (PCA and Logistic Regression).
- Conducted study showing a 60% improvement in users successfully meeting daily fitness objectives.
Pattern Recognition in Hand Images August 2019 – December 2019
- Created image recognition software achieving 95% accuracy implementing algorithms for data cleaning, feature
extraction and dimensionality reduction for efficient similarity searches using PCA/LDA techniques.
- Performed Machine Learning techniques to automatically learn patterns and predict classifications by implementing
clustering (k-means and DBSCAN) and classification (SVM and k-NN).
Handwritten Digit Recognition January 2020 – March 2020
- Recognized handwritten digits from images with 98% precision in TensorFlow and Keras.
- Experimented with Logistic Regression and Convolutional Neural Network for optimal precision.