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R Tharun Gowda

Upcoming Software Engineer at Salesforce

Resume

About Me

I'm a final-year student, studying Electronics and Communication at Indian Institute of Technology, BHU Varansi, India. I have always been fascinated by the recent advances in the field of Artifical Intelligence from Deep Learning to Deep Reinforcement Learning. I mainly study and work in the field of computer vision and deep reinforcement learning and occasionally on natural language processing. I enjoy solving problems and actively take part in online coding challenges.

Experience

Salesforce

Software Engineer Intern

Worked on a new technology which enables cross-platform fragment and experience sharing, saving time and increasing code reusability across all Salesforce properties. Worked on core Salesforce technologies such as Lightning Web Components, Flexcards, Flexipages and Lightning App Builder.

Microsec

Data Engineer Intern

Worked on detecting cyberattacks and classifying them using Machine learning and Deep learning.

Starvic

Machine Learning Engineer Intern

Worked on implementing models for career path and job role recommendation systems.

Shunya OS

IoTIoT.in

Aritfical Intelligence Engineer Intern

Implemented a robust image segmentation model for anomaly detection.

Prof. Oh-Seol Kwon,

Changwon National University, South Korea

Research Intern

Developed an objected detection model for advanced driver-assistance systems to perform real-time detection and recognition of objects.

Prof. Prateek Chatopadya

IIT BHU

Mentored Project

Re-identification of a person across an array of cameras, which have a non overlapping field of view using state of the art machine learning models such as GAN and using GAIT-analysis (used for biometric recognition ).

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Roboreg

IIT BHU

Research

Worked at Robotics Research Group, IIT BHU trying to achieve swarm intelligence in robots using multi-agent reinforcement learning. I mainly implemented the clustering, representation of kilobots and Reinforcement learning algorithms for the swarm system.

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Education

Indian Institute of Technology (BHU), Varanasi

July 2019 - Present

Bachelor of Technology

Fourth year, Electronics and Communication engineering. CPI: 9.19

Projects

Help visually impaired know their surroundings

Built a pipeline to input two images obtained from stereo imaging to produce a detailed map of the image, which includes identifying the objects, their position relative to the observer and the distance from the observer. Obtained distance of objects from stereo images using triangulation and stereo depth mapping techniques.

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License plate detection and recognition in unconstrained scenarios

Detecting license plates using yolov5 object detection models. Using opencv to perform image segmentation to extract characters from license plate and training ResNets to classify them. Also implemented an end-to-end number plate recognition model using yolov5s and yolov5l.

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Implementing RL algorithms to play games

Worked on implementing RL algorithms such as Q-learning , Deep Q networks, Deep Deterministic Policy Gradients and Actor-Critic algorithms on basic games such as atari breakout games .

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Optical character recognition

OCR of hindi language characters using opencv to segment out characters from words and ResNet models to classify segmented characters. Classification accuracy was 99.72 on the validation dataset.

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Skin Lesion Classification

Built a skin lesion classifier using Pytorch and densenet121 architecture on the HAM10000 dataset. The top accuracy achieved on the validation set was 0.906.

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Captcha Solver (identifier)

Trained a model to identify the letters and numbers hidden captchas. The model was built on a faster_rcnn_inception_v2_coco object detection architecture and using the Tensorflow object detection API. It had an average validation accuracy of about 99.2% on all the characters.

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Covid19 Chest Radiology Classification

Built a chest radiology classifier using Pytorch and Resnet34. Top accuracy achieved on the validation set 0.95

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Handwritten Bengali character classification

Built a model to classify handwritten bengali characters based on their consonant diacritic , grapheme root , vowel_diacritic using Convolutional neural networks followed by fully connected neural networks using tensorflow keras and open cv.

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Sentiment Analysis Using BERT

Built a sentiment classifier on Smile Annotation dataset using pytorch and BERT pretrained model.

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Disaster tweet classification

NLP model built using BERT (Bidirectional Encoder Representations from Transformers) to classify tweets. Using a data set on tweets to classify tweets pertaining to any disaster . It got a validation F-score of 85 and training F-score of 89.

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Covid-19 x-ray classifier

Trained a model to classify chest radiology images of potential COVID-19 patients. The model consisted of Convolutional neural networks followed by fully connected neural networks using tensorflow keras and sklearn . Data augmentation was used to further improve the accuracy. It received a test accuracy of 96.67% and a training accuracy of 94.62%.

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Skills

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