Rishabh G Upadhyay

RISHABH G UPADHYAY

Phn no: +919967840478

http://uhrishabh.wixsite.com/uhrishabh

Email: uhrishabh@gmail.com

EDUCATION:

2013–Present Bachelor of Engineering, Major: Information Technology.

Fr. Conceicao Rodrigues College of Engineering, Mumbai University, Recent GPA: 7.8/10.

RESEARCH EXPERIENCE:

06/2016 -07/2016 Research Assistant, Ben Gurion University of Negev, Israel

● Developed and improved Algorithm for Data stream Clustering (PcStream 2).

● Technology used: Python.

12/2015- 04/2016 Visiting Student, Hosei University, Japan

● Designed and implemented a method for knowledge extraction for list of research paper. We

implemented this method by using semantics and NLTK.

● Technology used: Python, NLTK.

06/2015-07/2015 Summer Research Student, Moscow Institute of Physics and Technology, Russia.

● Implemented a convolution neural network on Matlab using Convnet Toolbox. This

Implementation was used to train and test IDS Dataset.

● Technology used: Matlab.

12/2014- 01/2015 Research Intern, University of Donja Gorica, Montenegro

● Developed and implemented Algorithm for Detection of porous Material using Cellular

Automata.

● Technology used: Java.

PROJECTS: ONGOING:

● Pedestrian detection using deep learning (2016-):

Working on this project under the supervision of Ass. Prof. David Vázquez Bermúdez, Spain. We are

finding the best way for pedestrian detection and comparing the results of the classifiers. I was given the

task of implementing and experimenting.

● Accent classification using deep learning (2016-):

Working on this project for my bachelor thesis. Using accent, I am trying to find the current location of

the person and where he had lived in past.

● Facial Emotion Detection using deep learning (2016-):

Working on this project under the supervision of Prof. Liliana Lo Presti, Italy. I am working on improving

the classifiers for facial emotion classification.

● Implementation and improving Growing Convolutional neural networks (2016-):

Working on implementing growing CNN which can be useful in computer vision related projects and

applications. This project is done under the supervision of Prof. Herve Glotin, France.

● Detection of hand and head location using CNN (2016-):

Working on this project under the supervision of Prof. Robert Laganiere. I am working on implementing a

model for locating Hand and Head from a video.

COMPLETED:

● PcStream2- Data Stream Clustering Algorithm (2016):

Worked on this project under the supervision of Mr. Yisroel Mirsky, Israel. Implementing new algorithm

by improving PcStream1.

● Semantic Knowledge Extraction from Research papers (2015-16):

Worked on this project under the supervision of Prof. Akihiro Fujii, Japan. This Project was related to

applying Semantics method for knowledge extraction from Research papers.

● Application of Convolutional Neural Network for Intrusion type recognition (2015):

Worked on this project under the supervision of Prof. Alexander Galushkin, Russia. CNN was trained and

tested for Intrusion type recognition.

● Background modeling using Deep learning (2016):

Worked on this project remotely under the supervision of Prof. Thierry Bouwmans, France. This project

was related to subtracting background using Deep learning.

Rishabh G Upadhyay

● Music emotion classification and auto labeling (2016):

Worked on this project remotely under the supervision of Prof. Simon Lui, Singapore. This project was

related to Emotion classification and auto-labeling using Deep learning.

● Application of Cellular Automata in Modeling of Porous Building Materials and Solis Porous

Media (2014-15):

Worked on implementing Cellular Automata for modeling Porous Building Materials. This project is done

under the supervision of Prof. Biljana Stamatovic, Montenegro.

● Data-mining on Titanic data-set (2015):

Implemented various Data mining algorithms to Titanic data-set and observed the results.

Technology used: Weka.

● Library Alert System (2015):

This project was about making an system to which can alert the student regarding the delay of book issue.

Technology used:Java, Python, PostgreSQL, HTML+CSS.

● Movie review System website (2015):

In this project, website was designed which takes the user reviews about movies.

Technology used: PostgreSQL, HTML+CSS, JDBC.

● Bounce game (2015):

Implemented Bounce game using Java applets.

Technology used: Java applets.

PUBLICATIONS:

● Biljana Stamatovic, Rishabh Upadhyay and Nikolai Vatin, "Cellular Automata in Modeling of Porous Building

Materials and Solis Porous Media", In Proc. of the International Scientific Conference – Urban Civil Engineering

and Municipal Facilities, Russia, March 2015.

● Rishabh Upadhyay and Dmitry Pantiukhin, “Application of convolutional neural network for intrusion type

recognition", In Proc. of the International Conference of Engineering and Telecommunication, Russia, November

2015. (Local Conference preceding) Link.

● Rishabh Upadhyay and Akihiro Fujii, "Extracting knowledge from Technological Research Papers in

Application of IoT" , In Proc. of the Portland International Conference on Management of Engineering and

Technology, Hawaii, USA September 2016.

● Rishabh Upadhyay and Akihiro Fujii. “Semantic Knowledge Extraction from Research Documents”, In Proc of

the Federated Conference on Computer Science and Information Systems, Poland, September 2016.

● Yisroel Mirsky, Tal Halpern, Rishabh Upadhyay and Sivan Toledo. “Enhanced Situation Space Mining for Data

Streams”, In Proc of the 32nd ACM Symposium On Applied Computing, Morocco, April 2017 (Accepted).

PRESENTATION DONE:

● “Automatic License Plate Recognition”, Image processing, 2016.

● “Semantic Knowledge Extraction from Research Documents”, Federated Conference on Computer Science

and Information Systems, Poland, September 2016.

● “Bluetooth Technology”, Wireless Technology, 2016.

● “Natural Language processing”, Intelligence System, 2016.

ONLINE COURSES:

● “Machine learning”, Prof. Andrew Ng, Stanford University, Coursera (2014).

● “Neural Networks for Machine Learning”, Prof. Geoffrey Hinton, University of Toronto, Coursera (2014).

● “Introduction to Machine Learning”, Katie Malone & Prof. Sebastian Thrun, Stanford University, Udacity

(2015)

● “Deep Learning”, Dr. Vincent Vanhoucke, Google, Udacity (2015).

SKILLS:

Languages: Java, C, HTML, Python.

Database and Client/Server Technologies: PostgreSQL, MongoDB.

Software Tools: Google App engine, PuTTY, Matlab, Netbeans, Octave.