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Satwik Mishra
satwik.mishra1995@gmail.com
+1 (585)-754-5924
EDUCATION
ROCHESTER INSTITUTE
OF TECHNOLOGY
MS COMPUTER SCIENCE
| AUG 2018- JUNE 2021 (EXPECTED)
Rochester, New York
CGPA: 3.89/4
MANIPAL INSTITUTE
OF TECHNOLOGY
B.TECH IN INFORMATION TECHNOLOGY
| 2014-2018
Manipal, India
CGPA: 8.29/10
COURSEWORK
MS CS
Mobile Robot Programming
Intro to Big Data
Advanced Object Oriented
Fundamentals of Intelligent Systems
B.TECH IT
Neural Network and Fuzzy Logic
Pattern Recognition
Computer Vision
SKILLS
PROGRAMMING
Languages:
•Python • Java •C++ •C#
•Javascript •Apex
•HTML •CSS
Concepts/Frameworks:
•PostgreSQL • MongoDB
•JDBC • ROS • Gradle •PyTorch
•Tensorflow
•Node.js•Express.js
•AWS •Salesforce
•Git •MySQL •LATEX
•TCP/IP•UDP•RMI
•Multithreading
CERTIFICATION
2016 Coursera Algorithms Part 1
Stanford University
LINKS
Github:// Satwik95
Google Scholar://Satwik
LinkedIn:// satwik-mishra
EXPERIENCE
TRIMBLE INC. SOFTWARE ENGINEER INTERN, FALL CO-OP
Aug 2019 - Dec 2019 | Victor, NY, USA
• Researched on ESRI’s ArcGis GeoEvent Server and implemented a POC for
automating and making the process of conversion of 811 Dig tickets to work-orders
independent of original message format(JSON/XML/CSV etc), and sending the
work-orders to Trimble Unity REST Endpoint.
• Integration of GainsightPX and Salesforce instance: fetch Trimble Unity KPIs like
usage statistics, NPS etc.
• Stress testing with NeoLoad and Datadog Synthetics.
• Tech stack: AWS EC2 Servers, Python, JS, Node.js, Bash, Visual Scripting on Esri’s
GeoEvent Server, Apex, Visualforce Controllers, NeoLoad, Datadog.
APOLLO MUNICH HEALTH INSURANCE | DATA SCIENCE INTERN
May 2017 - July 2017 | Gurgaon, Haryana, India
• Implemented a Fraudulent health insurance claim prediction model using Python
and Excel. Created an ensemble of Random Forest, Gradient Boosting and
XGBoost.
• Implemented a GUI to fetch tweets and give public sentiment analysis for a given
company name.
• Libraries used - Sklearn, imblearn, XGBoost, Seaborn, Tweepy, TextBlob, NLTK,
Wordcloud, PyQt
RESEARCH AND PUBLICATION
BAGGING AND BOOSTING WITH EQUIVALENT SPACE
CONSUMPTION | SCOPUS | AUTHOR
May-Dec 2017 | Manipal, India
• Implemented and compared the various trade-offs between Bagging and Boosting
Algorithms under different conditions.
• Publication: Journal of Advanced Research in Dynamical and Control Systems
PROJECTS
LUNG CANCER DETECTION USING DEEP LEARNING |3D CNN,
TENSORFLOW, DATA AUGMENTATION, ENSEMBLE LEARNING
Jan 2018 - May 2018 | Manipal, India
• Developed an algorithm using 3D CNN with an ensemble of different activation
functions and data augmentation to determine when lesions in the lungs are
cancerous.
• Data set: High-resolution CT Scans of lungs provided by Kaggle.
MOVIE RECOMMENDATION USING COLLABORATIVE FILTERING |
HADOOP MAPREDUCE
Aug 2016 - Nov 2016 | Manipal, India
• To recommend movies using Collaborative filtering and sentiment analysis
incorporated with MapReduce.
• Implemented mapper and reducer classes and performed sentiment analysis on
movie reviews, computed Tanimoto co-efficient for item based filtering.

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Satwik Mishra Resume

  • 1. Satwik Mishra satwik.mishra1995@gmail.com +1 (585)-754-5924 EDUCATION ROCHESTER INSTITUTE OF TECHNOLOGY MS COMPUTER SCIENCE | AUG 2018- JUNE 2021 (EXPECTED) Rochester, New York CGPA: 3.89/4 MANIPAL INSTITUTE OF TECHNOLOGY B.TECH IN INFORMATION TECHNOLOGY | 2014-2018 Manipal, India CGPA: 8.29/10 COURSEWORK MS CS Mobile Robot Programming Intro to Big Data Advanced Object Oriented Fundamentals of Intelligent Systems B.TECH IT Neural Network and Fuzzy Logic Pattern Recognition Computer Vision SKILLS PROGRAMMING Languages: •Python • Java •C++ •C# •Javascript •Apex •HTML •CSS Concepts/Frameworks: •PostgreSQL • MongoDB •JDBC • ROS • Gradle •PyTorch •Tensorflow •Node.js•Express.js •AWS •Salesforce •Git •MySQL •LATEX •TCP/IP•UDP•RMI •Multithreading CERTIFICATION 2016 Coursera Algorithms Part 1 Stanford University LINKS Github:// Satwik95 Google Scholar://Satwik LinkedIn:// satwik-mishra EXPERIENCE TRIMBLE INC. SOFTWARE ENGINEER INTERN, FALL CO-OP Aug 2019 - Dec 2019 | Victor, NY, USA • Researched on ESRI’s ArcGis GeoEvent Server and implemented a POC for automating and making the process of conversion of 811 Dig tickets to work-orders independent of original message format(JSON/XML/CSV etc), and sending the work-orders to Trimble Unity REST Endpoint. • Integration of GainsightPX and Salesforce instance: fetch Trimble Unity KPIs like usage statistics, NPS etc. • Stress testing with NeoLoad and Datadog Synthetics. • Tech stack: AWS EC2 Servers, Python, JS, Node.js, Bash, Visual Scripting on Esri’s GeoEvent Server, Apex, Visualforce Controllers, NeoLoad, Datadog. APOLLO MUNICH HEALTH INSURANCE | DATA SCIENCE INTERN May 2017 - July 2017 | Gurgaon, Haryana, India • Implemented a Fraudulent health insurance claim prediction model using Python and Excel. Created an ensemble of Random Forest, Gradient Boosting and XGBoost. • Implemented a GUI to fetch tweets and give public sentiment analysis for a given company name. • Libraries used - Sklearn, imblearn, XGBoost, Seaborn, Tweepy, TextBlob, NLTK, Wordcloud, PyQt RESEARCH AND PUBLICATION BAGGING AND BOOSTING WITH EQUIVALENT SPACE CONSUMPTION | SCOPUS | AUTHOR May-Dec 2017 | Manipal, India • Implemented and compared the various trade-offs between Bagging and Boosting Algorithms under different conditions. • Publication: Journal of Advanced Research in Dynamical and Control Systems PROJECTS LUNG CANCER DETECTION USING DEEP LEARNING |3D CNN, TENSORFLOW, DATA AUGMENTATION, ENSEMBLE LEARNING Jan 2018 - May 2018 | Manipal, India • Developed an algorithm using 3D CNN with an ensemble of different activation functions and data augmentation to determine when lesions in the lungs are cancerous. • Data set: High-resolution CT Scans of lungs provided by Kaggle. MOVIE RECOMMENDATION USING COLLABORATIVE FILTERING | HADOOP MAPREDUCE Aug 2016 - Nov 2016 | Manipal, India • To recommend movies using Collaborative filtering and sentiment analysis incorporated with MapReduce. • Implemented mapper and reducer classes and performed sentiment analysis on movie reviews, computed Tanimoto co-efficient for item based filtering.