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Curriculum Vitae

Mayank Rana

******.****@***.***

Preamble

I am a graduate student in Computer Science at Courant Institute of Mathematics and

Sciences, New York University.

My research interests are Machine Learning, Computer Vision and Algorithms.

My relevant courses are Fundamental Algorithms, Machine Learning & Pattern Recognition

and Motion Capture for Games & Urban Sensing.

Education

MS, Computer Science, CIMS, NYU, USA (Expected June-2012)

B.Tech (Computer Science and Engineering), JIITU, India 2009

High School, CBSE, Vivekanand School (New Delhi, India)

Work Experience

Organization:

Siemens Corporate Research, Princeton

Designation: Research Intern

Duration: May 2011 - Aug 2011

Organization:

Courant Institute of Mathematical Sciences, New York University.

Designation: Adjunct Instructor, Data Structures

Duration: Sept, 2010 Dec, 2010

Organization:

Accenture Services Pvt. Ltd.

Designation: Associate Software Engineer

Duration: Dec, 2009 July, 2010

Selected Achievements

Dec 2010 Presented two projects with live demo at annual project showcase, CIMS, NYU

Aug 2009 Presented a poster paper at the International Conference on Contemporary

Computing, India

Dec 2008 Program Co-ordinator of Digital Image Processing and Advanced Problem Solving

in C workshops for IEEE student branch JIITU

Aug 2008-May 2009 Mentored more than 25 projects on Computer Vision and C-Applications

Jul 2007-May 2008Teaching assistant for the undergraduate courses Introduction to

Computer Programming and Data Structure at JIITU

July 2007, June 2008 Internship at Shristi, an NGO for learning disabled kids and

CANKIDS, an NGO for kids suffering from cancer

Technical Proficiency

Language/Technologies: C, C++, C#, Java, Malab, Lush/Lisp, MySQL, HTML5, J2EE, JSP, JSF,

ASP.NET

IDE/Tools/Libraries: OpenCV, Microsoft Visual Studio .NET 2003 & 2005, Eclipse Galileo &

Helio, True Vision 3D, Turbo C++ 3.0, Eclipse Galileo

Conferences

Image Reconstruction by Object Cut-out and Enhancement with Sub-pixel Accuracy

Graduate Projects

Multipurpose Home Robot

(Dec 2010)

This robot with xbox kinect sensor is trained using neural network for obstacle

avoidance, human detection, face detection and face recognition. It can roam around the

house to find a particular person.

Lean Machine

(Dec 2010)

This game can be controlled by the motion of a large audience. The game can recognize

audience lean (left or right) using a single camera and can do the assigned task

accordingly. The game can recognize any different motions after a little training using

support vector machines.

Undergraduate Projects

Scene Reconstruction by Object Insertion at any Depth

(May 2009)

This system implements a novel method for object extraction from an image with minimal

user interaction. The extracted object can then be put up in any other image at any depth

and position using segment based depth evaluation method.

Developed Using: Microsoft Visual C#.NET

Image Reconstruction by Object Cut-out and Enhancement with Sub-pixel Accuracy

(May 2009)

In this project, an object is extracted out from an image with sub -pixel accuracy using

minimal user interaction. The image can be reconstructed by altering colour, brightness

and contrast of the extracted object in the image without affecting the background. A set

of user interface tools are designed and implemented for editing the properties of the

extracted object.

Developed Using: Microsoft Visual C#.NET

Video Completion by Moving Object Removal

(May 2009)

This system tracks a moving object selected by the user in a video sequence. The

extracted object is then removed from the entire video sequence and the empty background

left behind is filled up with the information from the neighbouring frames. It modifies

the video as if the selected moving object was never present in the original video.

Developed Using: Microsoft Visual C#.NET

Scene Interpolation using Segment Based Depth Evaluation from Stereo Images

(Feb2009)

In this system a novel segment based algorithm is proposed and implemented which extracts

the depth information of the objects present in a scene with the help of stereo images.

The developed system also interpolates and renders a new view of the scene from any

viewpoint.

Developed Using: Microsoft Visual C#.NET

NRITYASHALA : Learning Tool for Indian Classical Dance

(July 2008)

It is a dance learning tool which helps a dance scholar to identify the mistakes in

movements which he has done wrong while learning dance steps. It takes input from web

camera in the form of video and simultaneously compares it with existing database to find

out movements which are different from original dance form. The mismatches in the dance

postures and a popup message are displayed if user has performed wrong dance steps, so

that he can learn by watching his mistakes.

Developed Using: Microsoft Visual C#.NET

3D-Reversi

(May 2008)

The artificial intelligence based game Reversi is implemented in a 3D environment. This

is a chess like game in which user can play on a 64 chequered board against the computer.

Developed Using: Microsoft Visual C#.NET

Image Based Video Search Engine

(May 2007)

This video retrieval system is used for searching images in large video databases. It

supports queries based on images. The videos in the database are pre-processed and along

with every video, its extracted features essential for retrieval are stored. The system

extracts features from the query image at run time and matches them with the features

stored in the database to produce the desired results with real time performance.

Developed Using: Microsoft Visual C#.NET

Line Following Robot

(Nov 2007)

An automated robot which follows a line is developed at IURS - Indian Underwater Robotics

Society workshop.

Developed Using: Bascom

GENSIM: A Generic Queue Simulator

(Nov 06)

This tool is a generic simulator which can perform any type of queue simulation. It is

generic in terms of processors, counters, queues, priority of queues, processing time,

probability of an entry, time of simulation. This simulation gives an average waiting

time, time at each counter and many more details of all entries.

Developed Using: Turbo C++

Industrial Training (Tata Consultancy Services)

CLOUS: A Collaborative Learning and Office Utility Software

(May 2008)

In this online collaborative learning software, different groups/ communities can be

formed for different subjects; each group has a moderator (faculty). The students can

register to different groups and can ask queries from faculty as well as from the other

group members by using a text chat. A database is maintained for all the members. The

software can be used in colleges as well as in offices.

Developed Using: Microsoft Visual C#.NET

Extra Curricular Activities

Actively Involved with NGOs: Pravah, Cankids, Shristi

Hobbies: Drawing Portraits, Playing Guitar

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