Mali Dasharathbhai Dahyvalal is currently pursuing a Master of Engineering in Signal Processing at the Indian Institute of Science in Bangalore. He completed a Bachelor of Engineering in Electronics and Communication Engineering from Govt. Engg. College Gandhinagar Sec-28 in Gujarat in 2012. His areas of interest include computer vision, machine learning, image processing and optimization. He is currently working on a project titled "Attribute Based Facial Image Retrieval Using Transformation Learning" under the guidance of Dr. Soma Biswas.

1. MALI DASHARATHBHAI DAHYALAL
Personal Data
Date of Birth: 11 May 1991
Permanent Address: Chandralok Society Road, Deesa
Banaskantha - 385535, Gujarat
Phone: +91 9611065879
Email: dasharathmali11@ee.iisc.ernet.in
dasharathmali11@gmail.com
Objective
To work for an organization which provides me the opportunity to improve my skills and knowledge to
growth along with the organization objective.
Education
Current Master of Engineering in Signal Processing,
Indian Institute of Science, Bangalore
Project: “Attribute Based Facial Image Retrieval Using Transformation Learning”
Advisor: Dr. Soma Biswas
CGPA: 7.2/8(until 3th semester)
May 2012 Bachelor of Engineering in Electronics and Communication Engineering,
Govt. Engg. College Gandhinagar Sec-28, Gujarat
Project: “Face Recognition Using Principal Component Analysis”
Advisor: Prof. Jignesh Bhavshar
CGPA: 8.75/10
March 2008 HSC Examination
Gujarat Education Board, Gandhinagar, Gujarat
Marks: 82.80 %
March 2006 SSC Examination
Gujarat Education Board, Gandhinagar, Gujarat
Marks: 78.43 %
Projects
Attribute Based Facial Image Retrieval Using Transformation Learning
Facial image retrieval based on attributes has wide range of applications, such as law enforce-
ment,online social networks, personal photo libraries, etc. Towards these applications, we propose
a learning-based approach based on the attributes of a query image.
Face Recognition Using Principal Component Analysis
This project explores the relationship between Eigen face recognition performance and different
training data sets. Using the method Principal Component Analysis [PCA] we are able to compute
Eigen faces from a large number of training samples. This allows us to compare the recognition
performance using different training data sizes. Experimental results show that rich data set give
better recognition performance.

2. Interested Areas
Computer Vision, Machine Learning, Image Processing,Optimization
Courses taken at IISc as part of the PG degree requirement
Computer Vision
Pattern Recognition and Neural Network(Machine Learning)
Digital Image Processing
Linear and Non-linear Optimization
Convex Optimization
Matrix Theory
Random Process
Information Theory
Detection and Estimation Theory
Digital Communication
DSP System Design
Achievements
Secured All India Rank of 70 in GATE 2013 Examination.
Skills
Programming language : C
Assembly Language Programming : 8085, 8051
Mathematical Software : Matlab
Application Packages : MS Office, LATEX(beginner)
References
Dr. Soma Biswas
Assistant Professor
Department of Electrical Engineering
Indian Institute of Science
Bangalore - 560012
Email id: soma.biswas@ee.iisc.ernet.in