Graduate Research and Teaching Assistant, 08/2017 to 05/2018 The University of Texas
Research Assistance in Claim Buster, fact finding and fact checking Project under Dr.
Chengkai Li in 2016.
Helped students with C++ labs, projects and graded assignments and exam papers.
Maintaining computer research lab, working with hypervisors & installation of OS, Shell Scripting to apply UTA policies.
Senior Software Engineer, 08/2013 to 08/2016
Created and Maintained Trade Data Analytics Dashboard, which helped to visualize the information, on various trade details.
Designed and Implemented High-Volume Trade Processing Platform, helps Fidelity Trade Processing Team to overcome congestion of Trade traffic in system on high volume trading days.
Managed Agile Scrum Master Role in the team of 6 associates and collaborated with other teams outside business unit and gave my timely guidance to overcome unseen obstacle and seamless practice in Agile methodology.
Systems Engineer, 11/2009 to 08/2013 Tata Consultancy Services Ltd
Integrated 450 isolated Government offices to upload data to a Survey Site (http://www.pas.org.in/).
Which has helped Government officials see comparison report across various states performances on sanitation, water supply etc.
Negotiate contracts with clients by Requirement Gathering, Analysis and Design Document preparation, which brought benefits to both Clients and TCS to come together at a legal proceeding in terms of software development and design.
Machine Learning on Coursera by Andrew Ng [License: J33KZAU3DAAA] Deep Learning specialization on Coursera by Andrew Ng [License: WWHYGCV2FX46] Neural Networks and Deep Learning Convolutional Neural Networks Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization Structuring in Machine Learning Projects Sequence Models AWS (In Progress) Publications VLDB Conference 2017: Vol.
10, Issue 12: Paper: 1214, Title: ClaimBuster- The First-ever End-to-end Fact-checking System Achievements Awarded with 2nd place in Herox Challenge(https://herox.com/factcheck).
IDIR Lab in 2017.
Deep Learning Technology: PyCharm, Python, C++, Tensorflow, Keras, OpenCV, Numpy, Unix/Linux, Scikit-learn, Matplotlib, dlib, pandas Image Captioning using deep learning Implemented LSTM network and VGG16 network for image captioning, uploaded to GitHub and would helped other researchers and educational purpose.
Moving Object Detection and classification using Google object detection API Started research activity through learning process using Google Object detection API - Tensorflow, trained COCO and PASCAL VOC dataset and tried with training and got better accuracy of 97%.
Developed Human Pose Estimation Prepared histogram of video content of human activity and then classified those using KNN and SVM to estimation pose for the unseen video content.
The accuracy was even best and surpass my expectation to 90%.
Face Detection system using Adaboost and Eigen Faces Implemented Viola Jones Paper for face detection using cascades.
Got over better accuracy with little modification on top of Viola Jones paper.
Machine Learning Technology: PyCharm, Python, C++, Matlab, Numpy, Mac, Unix/Linux, Scikit-learn, Matplotlib, Java Implementation of SVM, KNN, Reinforcement Learning, Mixed Gaussian model, classification, clustering, regression, PCA, decision tree, random forest, DTW, Bayesian estimation from the mathematical front to analyze the complexity and compared against available ML libraries.
Data Mining [R] Technology: R, R Studio, Unix/Linux Implemented data mining methodologies, data cleaning, data analysis and visualization in various algorithms.
Applied ARIMA Model, Classification and Clustering model on cleaned dataset and predict & find accuracy.
Robotics Projects Technology: C++, Ultrasonic Sensor, Touch Sensor, Color Sensor, Gyroscope, Eclipse, PD Controller, PID Controller, SLAM Path Planning Designed and built bot from scratch and implemented A* to reach goal.
Also experimented and tested with Dijkstra, BFS, DFS, RRT and RRT*.
Behavior Based Designed and built behavior-based bot for goal search in arbitrary space without any prior knowledge about space and demonstrated various behavior including obstacle avoidance, wall follower, space exploration.
Object Cleanup Designed and build cleanup bot to pick up the specific color object and place it on specific region in room with having any prior knowledge about the space and location of goal and object.
Primary focus in Deep Learning, Machine Learning and Computer Vision (Supervisor - Dr. Farhad Kamangar).
*Related course work: Neural Network, Machine Learning, Computer Vision, Robotics, Data Mining, DAMT
Bachelor's: Information Technology | VSSUT, Burla, May 2009 Information Technology | VSSUT, Burla GPA: 8 / 10.0
Anil Kumar Nayak
Deep Learning | Computer Vision | Machine Learning | Robotics
2 Years in Academic Research Experience
7+ Years of Experience (Development) Over 7 years of software development experience. 2 years of research experience in deep learning, machine learning, python and tensoflow. Research publication at VLDB on fact finding and fact checking application. Dedicated and passionate about Deep Learning, Computer Vision and Machine Learning.
Member of Robotics Club and won 1st prize in inter college robotics competition
*Member of organizing team for College annual technical festival, College Cricket Team
Java, Algorithm, C, C++, Data Structure, Analog and Digital Electronic Circuit, Compiler Design.
Research / Thesis - Face Detection and Recognition System
Designed and implemented face detection and recognition system using CNN, Inception Model and SVM, KNN classifier using embedding and achieved 98% accuracy over testing data.