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Mayank Padhi

Last updated in . Get the latest version at mayankpadhi.github.io/cv.

M.Sc. Student
Data Science in Engineering
Eindhoven University of Technology, Eindhoven

https://mayankpadhi.github.io
m.padhi@student.tue.nl
@mayankpadhi

Research Area

I study Neural Networks and Machine Learning techniques and their interdisciplinary applications in a plethora of fields. My work relies on data preprocessing, statistics, regression, classification, computer vision, genetic algorithms, fuzzy systems, bayesian networks, evolutionary computation and dimensionality reduction techniques. In programming languages, I prefer working with Python. For Statistical analysis, I like working on SAS and R.

Education

2019 -
M.Sc. in Data Science in Engineering
,    
Eindhoven University of Technology
Eindhoven, The Netherlands

2015 - 2019
B.S. in Computer Science
,    
Indian Institute of Information Technology
Gujarat, India

Experience

2021
Research and Development Intern
,     Canon Venlo, The Netherlands

Thesis Title: Prediction model of color dry back. Studied the factors that affect the dry back. Designed a regression model that predicts the colors upon drying for a given set of media.

2020- 2021
Data Scientist (Internship)
,     Rev'it Sports International Oss, The Netherlands

The tasks revolved around business analytics, pre-processing of the sales and marketing data, visualization, data modelling and prediction. Worked on technologies like Google Analytics, Microsoft Power BI, R.

2019
Software Developer (Internship)
,     Maximl Chennai, India

Designed and developed the product deployer, Falcon. Worked on technologies like Microsoft Azure, AWS, Gitlab CI/CD, Django, NodeJS.

2018
Software Developer (Internship)
,     Stochastic Solutions Pvt Limited Gurugram, India

Collaborated with Google on the project Scholargraph in various foundational algorithms and database management. . Revamped and optimized the existing data structure and data management. Designed a ML model, SEO and analytics.

2017
Volunteer Work
,     Freepathshala Gurugram, India

Built a fully working website from scratch for the NGO

2017
Developer
,     Hasura Bangaluru, India

Designed a Coffee Shop Jukebox, where the customers can add their favourite music in the Jukebox by simply connecting to their network and logging in to the captive portal. Used HTML5, CSS, Javascript for frontend and kubernetes cluster, NodeJS, postgreSQL hasura tool for backend, CoovaChilli tool for captive portal login feature.

Relevant Coursework

Eindhoven University of Technology
,    
           
  • Foundations of Data Mining (Wouter Duivesteijn, Decebal Mocanu)
  • Advanced Algorithms (Mark de Berg)
  • Introduction to Process Mining (B. van Dongen)
  • Advanced Process Mining (Dirk Fahland)
  • Applied Statistics (Richard Post)
  • Data Visualization (Michel Westenberg)
  • Statistical Learning Theory (Rui Castro)
  • Database Technology (Nikolay Yakovets, George Fletcher)
  • Web Information Retrieval And Data Mining (Joaquin Vanschoren)
  • Stochastic Networks (Ungraded) (Ellen Cardinaels)
  • Statistics for Big Data (Ungraded) (Edwin van den Heuvel)
  • Deep Learning (Vlado Menkovski)
  • Data Engineering (Odysseas Papapetrou, George Fletcher)
  • Ethics of Technology (Peter Novitzky)
  • Introduction to The HTI Domain (K.C.H.J. Smolders)
  • Human Aspects of Innovation (J. Gevers)
Indian Institute of Information Technology
,    
           
  • Data Structures
  • Algorithms
  • Database Management Systems
  • Discrete Mathematics
  • Distributed Computing
  • Computer Networks
  • Artificial Intelligence
  • Deep Neural Networks
Big Data
,     Coursera
    Guided me through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. I got experience on how one can perform predictive modeling and leverage graph analytics to model problems. This specialization prepared me to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets.
           
  • Introduction to Big Data
    It provided an introduction to Hadoop framework.
  • Big Data Modeling and Management Systems
    Learned how do you collect, store and organize your data using Big Data solutions and experience various data genres and management tools appropriate for each. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL.
  • Big Data Integration and Processing
    Learned to describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications. Executed simple big data integration and processing on Hadoop and Spark platforms.
  • Machine Learning With Big Data
    Applied machine learning techniques to explore and prepare data for modeling. Identified the type of machine learning problem in order to apply the appropriate set of techniques. Constructed models that learn from data using widely available open source tools.
  • Graph Analytics for Big Data
    I modeled a problem into a graph database and performed analytical tasks over the graph in a scalable manner. Then, I applied these techniques to understand the significance of the data sets for the projects.
  • Big Data- Capstone Project
    Capstone Project, I walked through the typical big data science steps for acquiring, exploring, preparing, analyzing, and reporting.
Machine Learning
,     Coursera
    Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).
           
Full Stack Web and Multiplatform Mobile App Development
,     Coursera
    Learned to create hybrid mobile applications, using the Ionic framework, Cordova and NativeScript. On the server side, I implemented NoSQL databases using MongoDB, worked within a Node.js environment and Express framework, and communicate to the client side through a RESTful API.
           
  • Server-side Development with NodeJS, Express and MongoDB
    Reviewed basic CRUD operations, NoSQL databases, in particular MongoDB and Mongoose for accessing MongoDB from NodeJS. I also examined the REST concepts and built a RESTful API.
  • Multiplatform Mobile App Development with NativeScript
    Learnt about UI development with NativeScript UI and layout support and access the native mobile platform's capabilities from Javascript.
  • Multiplatform Mobile App Development with Web Technologies Ionic and Cordova
    Learned about UI development with Ionic and then using Cordova's modules to access the native mobile platform's capabilities from Javascript.
  • Front-End JavaScript Frameworks Angular
    Learned about the basics client-side developement using Angular.
  • Front-End Web UI Frameworks and Tools Bootstrap 4
    Implemented grids and responsive design, Bootstrap CSS and JavaScript components. Learned about CSS preprocessors, Less and Sass. Learned the basics of Node.js and NPM and task runners like Grunt and Gulp.
Cloud Computing
,     NPTEL
    Introduction, architecture of clouds. Service, Data and Resource management of cloud. Cloud Security concerns. Hands on Open Source, commercial clouds and their simulators. Research areas in cloud computing and introduction to fog computing.
           
Internet of Things(IOT)
,     NPTEL
    Introduction, basics of networking and communication protocols. Sensor Networks, Machine2Machine communication. Introduction to Arduino and Raspberry Pi programming. Introduction to SDN for IOT, Data handling and analytics. Fog computing, Smart cities, homes, grids and smart vehicles. IOT in Industries. Implementation on Agriculture, Healthcare and Activity Monitoring.
           
Amazon Web Services
,     Udemy
    Learned launching instances in EC2(Elastic Cloud Compute). Adding EBS volumes to EC2 instances. Created and managed snapshots and security groups. Launching, creating and inserting data to DynamoDB. Creating S3(Simple Storage Service) bucket, uploading files to it and its versioning.
           
Introduction to Modern Application Development (IMAD)
,     NPTEL
    Learned basics of developing web and mobile applications. Developed the insight of the authentication, security and the best practices. Connection of backend to frontend and deploying the server for a webapp. Introduction to client-side and server-side javascript. Database concepts, its properties, security, backup and recovery. ACID properties of SQL, their analytics and views. Scaling up the app, introduction to popular network protocols and authentication with HTTP.
           
Deep Learning
,     Udacity
    Learned classification for detection and ranking. Concepts of cross-entropy and hot labels in Multinomial Logistic Classifications. Creating, training, validating, testing and optimising the logistic classifiers and deep learning network. Implementing Rectified Linear Units(ReLU) in neural networks. Introduction to Stochastic Gradient Descent, Convolutional Neural Networks(CNN), Recurrent Neural Networks(RNN) and Long Short Term Memory(LSTM), Convolutional Networks(CovNets).
           

Achievements

2017
Elite in IOT
,     IITKgp-MHRD

Performance was evaluated by assignments, a small project and a nationwide online exam. `Elite’ tag is awarded to top scorers.

2017
Elite in Cloud Computing
,     IITKgp-MHRD

Performance was evaluated by assignments, a small project and a nationwide online exam. `Elite’ tag is awarded to top scorers.

2017
Elite in IMAD course
,     IITM-MHRD

Performance was evaluated by assignments and a nationwide online exam. `Elite’ tag is awarded to top scorers.

2017
Runner up in Android Monk Hackathon
,     Wisel

Developed a working 9x9 Tic Tac Toe game for Android in 24 hrs.

2016
Ranked in Top 150 in CodeFest, 2016
,     IIT-BHU

Scored in events of Decipher, Capture the flag, Appathon. Over 6000 candidates across the globe participated in the event

2016
SnackDown 2016 Pre-finalist
,     CodeChef

Top 300 teams were selected for the prefinal round for annual CodeChef coding event

2015
Scored 99 percentile in JEE Mains All India in 2015.
,     JEE(Mains) and JEE(Advanced)

JEE mains is common entrance exam for engineering colleges in India.

2014
Best Student of the Year, 2014
,     Kendriya Vidyalaya No. 2 Ambala

The award was given on overall performance on academics, sports and discipline.

2012
CBSE merit in class X
,     CBSE

References

Dirk Fahland
Analytics for Information Systems
Eindhoven University of Technology
d.fahland@tue.nl

Joaquin Vanschoren
Machine Learning
Eindhoven University of Technology
j.vanschoren@tue.nl