Sayanitika Mukherjee is seeking a career in research and development in displays, MEMS, and device fabrication. She has a PhD in Electrical Engineering from the University of Cincinnati and a Bachelor's in Electronics and Instrumentation Engineering. Her dissertation and research focused on developing electrophoretic displays and smart windows using a novel single layer color system. She has skills in microfabrication, characterization, and optical technologies.
Deep convolutional neural network for hand sign language recognition using mo...journalBEEI
An image processing system that based computer vision has received many attentions from science and technology expert. Research on image processing is needed in the development of human-computer interactions such as hand recognition or gesture recognition for people with hearing impairments and deaf people. In this research we try to collect the hand gesture data and used a simple deep neural network architecture that we called model E to recognize the actual hand gestured. The dataset that we used is collected from kaggle.com and in the form of ASL (American Sign Language) datasets. We doing accuracy comparison with another existing model such as AlexNet to see how robust our model. We find that by adjusting kernel size and number of epoch for each model also give a different result. After comparing with AlexNet model we find that our model E is perform better with 96.82% accuracy.
Deep convolutional neural network for hand sign language recognition using mo...journalBEEI
An image processing system that based computer vision has received many attentions from science and technology expert. Research on image processing is needed in the development of human-computer interactions such as hand recognition or gesture recognition for people with hearing impairments and deaf people. In this research we try to collect the hand gesture data and used a simple deep neural network architecture that we called model E to recognize the actual hand gestured. The dataset that we used is collected from kaggle.com and in the form of ASL (American Sign Language) datasets. We doing accuracy comparison with another existing model such as AlexNet to see how robust our model. We find that by adjusting kernel size and number of epoch for each model also give a different result. After comparing with AlexNet model we find that our model E is perform better with 96.82% accuracy.
Real time Myanmar Sign Language Recognition System using PCA and SVMijtsrd
Communication is the process of exchanging information, views and expressions between two or more persons, in both verbal and non verbal manner. The sign language is a visual language used by the people with the speech and hearing disabilities for communication in their daily conversation activities. Myanmar Sign Language MSL is the language of choice for most deaf people in this country. In this research paper, Real time Myanmar Sign Language Recognition System RMSLRS is proposed. The major objective is to accomplish the translation of 30 static sign gestures into Myanmar alphabets. The input video stream is captured by webcam and is inputed to computer vision. The incoming frames are converted into YCbCr color space and skin like region is detected by YCbCr threshold technique. The hand region is also segmented and converted into grayscale image and morphological operation is applied for feature extraction. In order to translate the signs of ASL into the corresponding alphabets, PCA is used for feature extraction and SVM is used for recognition of MSL signs. Experimental results show that the proposed system gives the successful recognition accuracy of static sign gestures of MSL alphabets with 89 . Myint Tun | Thida Lwin "Real-time Myanmar Sign Language Recognition System using PCA and SVM" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26797.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/26797/real-time-myanmar-sign-language-recognition-system-using-pca-and-svm/myint-tun
GRS '“ Gesture based Recognition System for Indian Sign Language Recognition ...ijtsrd
Recognition languages are developed for the better communication of the challenged people. The recognition signs include the combination of various with hand gestures, movement, arms and facial expressions to convey the words thought. The languages used in sign are rich and complex as equal as to languages that are spoken. As the technological world is growing rapidly, the sign languages for human are made to recognised by systems in order to improve the accuracy and the multiply the various sign languages with newer forms. In order to improve the accuracy in detecting the input sign, a model has been proposed. The proposed model consists of three phases a training phase, a testing phase and a storage output phase. A gesture is extracted from the given input picture. The extracted image is processed to remove the background noise data with the help of threshold pixel image value. After the removal of noise from the image and the filtered image to trained model is tested with a user input and then the detection accuracy is measured. A total of 50 sign gestures were loaded into the training model. The trained model accuracy is measured and then the output is extracted in the form of the mentioned language symbol. The detection mechanism of the proposed model is compared with the other detection methods such as Hidden Markov Model(HMM), Convolutional Neural Networks(CNN) and Support Vector Machine(SVM). The classification is done by means of a Support Vector Machine(SVM) which classifies at a higher accuracy. The accuracy obtained was 99 percent in comparison with the other detection methods. D. Anbarasan | R. Aravind | K. Alice"GRS “ Gesture based Recognition System for Indian Sign Language Recognition System for Deaf and Dumb People" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-2 , February 2018, URL: http://www.ijtsrd.com/papers/ijtsrd9638.pdf http://www.ijtsrd.com/engineering/computer-engineering/9638/grs--gesture-based-recognition-system-for-indian-sign-language-recognition-system-for-deaf-and-dumb-people/d-anbarasan
Exploring didactic possibilities of an electronic devices remote lab with stu...Federico Lerro
This paper presents some results of an exploratory study carried out with the
collaboration of students, whose aim was to examine the teaching potential of a selfdeveloped
remote lab, called “Electronic Physics Remote Lab”. The remote lab
allows us, among other things, to test different kinds of diodes and transistors.
Students of Electronic Engineering attending Physics IV have been asked to use the
remote lab for the development of the following activities: a) to study the development
of different junctions and infer about their constructive features and b) to obtain
parameters of the devices under different test conditions, and to explain the behaviors
observed from the point of view of the physical processes. Besides, students prepared
test reports of the remote lab.
Sign Language Recognition based on Hands symbols ClassificationTriloki Gupta
Communication is always having a great impact in every domain and how it is considered the meaning of the thoughts and expressions that attract the researchers to bridge this gap for every living being.
The objective of this project is to identify the symbolic expression through images so that the communication gap between a normal and hearing impaired person can be easily bridged.
Github Link:https://github.com/TrilokiDA/Hand_Sign_Language
Wireless sensor networks (WSNs) have recently gained a lot of attention by scientific community. Small and inexpensive devices with low energy consumption and limited computing resources are increasingly being adopted in different application scenarios including environmental monitoring, target tracking and biomedical health monitoring. In many such applications, node localization is inherently one of the system parameters.
Real time Myanmar Sign Language Recognition System using PCA and SVMijtsrd
Communication is the process of exchanging information, views and expressions between two or more persons, in both verbal and non verbal manner. The sign language is a visual language used by the people with the speech and hearing disabilities for communication in their daily conversation activities. Myanmar Sign Language MSL is the language of choice for most deaf people in this country. In this research paper, Real time Myanmar Sign Language Recognition System RMSLRS is proposed. The major objective is to accomplish the translation of 30 static sign gestures into Myanmar alphabets. The input video stream is captured by webcam and is inputed to computer vision. The incoming frames are converted into YCbCr color space and skin like region is detected by YCbCr threshold technique. The hand region is also segmented and converted into grayscale image and morphological operation is applied for feature extraction. In order to translate the signs of ASL into the corresponding alphabets, PCA is used for feature extraction and SVM is used for recognition of MSL signs. Experimental results show that the proposed system gives the successful recognition accuracy of static sign gestures of MSL alphabets with 89 . Myint Tun | Thida Lwin "Real-time Myanmar Sign Language Recognition System using PCA and SVM" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26797.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/26797/real-time-myanmar-sign-language-recognition-system-using-pca-and-svm/myint-tun
GRS '“ Gesture based Recognition System for Indian Sign Language Recognition ...ijtsrd
Recognition languages are developed for the better communication of the challenged people. The recognition signs include the combination of various with hand gestures, movement, arms and facial expressions to convey the words thought. The languages used in sign are rich and complex as equal as to languages that are spoken. As the technological world is growing rapidly, the sign languages for human are made to recognised by systems in order to improve the accuracy and the multiply the various sign languages with newer forms. In order to improve the accuracy in detecting the input sign, a model has been proposed. The proposed model consists of three phases a training phase, a testing phase and a storage output phase. A gesture is extracted from the given input picture. The extracted image is processed to remove the background noise data with the help of threshold pixel image value. After the removal of noise from the image and the filtered image to trained model is tested with a user input and then the detection accuracy is measured. A total of 50 sign gestures were loaded into the training model. The trained model accuracy is measured and then the output is extracted in the form of the mentioned language symbol. The detection mechanism of the proposed model is compared with the other detection methods such as Hidden Markov Model(HMM), Convolutional Neural Networks(CNN) and Support Vector Machine(SVM). The classification is done by means of a Support Vector Machine(SVM) which classifies at a higher accuracy. The accuracy obtained was 99 percent in comparison with the other detection methods. D. Anbarasan | R. Aravind | K. Alice"GRS “ Gesture based Recognition System for Indian Sign Language Recognition System for Deaf and Dumb People" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-2 , February 2018, URL: http://www.ijtsrd.com/papers/ijtsrd9638.pdf http://www.ijtsrd.com/engineering/computer-engineering/9638/grs--gesture-based-recognition-system-for-indian-sign-language-recognition-system-for-deaf-and-dumb-people/d-anbarasan
Exploring didactic possibilities of an electronic devices remote lab with stu...Federico Lerro
This paper presents some results of an exploratory study carried out with the
collaboration of students, whose aim was to examine the teaching potential of a selfdeveloped
remote lab, called “Electronic Physics Remote Lab”. The remote lab
allows us, among other things, to test different kinds of diodes and transistors.
Students of Electronic Engineering attending Physics IV have been asked to use the
remote lab for the development of the following activities: a) to study the development
of different junctions and infer about their constructive features and b) to obtain
parameters of the devices under different test conditions, and to explain the behaviors
observed from the point of view of the physical processes. Besides, students prepared
test reports of the remote lab.
Sign Language Recognition based on Hands symbols ClassificationTriloki Gupta
Communication is always having a great impact in every domain and how it is considered the meaning of the thoughts and expressions that attract the researchers to bridge this gap for every living being.
The objective of this project is to identify the symbolic expression through images so that the communication gap between a normal and hearing impaired person can be easily bridged.
Github Link:https://github.com/TrilokiDA/Hand_Sign_Language
Wireless sensor networks (WSNs) have recently gained a lot of attention by scientific community. Small and inexpensive devices with low energy consumption and limited computing resources are increasingly being adopted in different application scenarios including environmental monitoring, target tracking and biomedical health monitoring. In many such applications, node localization is inherently one of the system parameters.
Top Cited Article in Informatics Engineering Research: October 2020ieijjournal
Informatics is rapidly developing field. The study of informatics involves human-computer interaction and how an interface can be built to maximize user-efficiency. Due to the growth in IT, individuals and organizations increasingly process information digitally. This has led to the study of informatics to solve privacy, security, healthcare, education, poverty, and challenges in our environment. The Informatics Engineering, an International Journal (IEIJ) is a open access peer-reviewed journal that publishes articles which contribute new results in all areas of Informatics. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on the human use of computing fields such as communication, mathematics, multimedia, and human-computer interaction design and establishing new collaborations in these areas.
1. SAYANTIKA MUKHERJEE
508 Riddle Road # 7 Cincinnati OH 45220
Email: mukhersk@mail.uc.edu Phone: 513-497-5227
OBJECTIVE: Seeking a career in the field of research and development in Display, MEMS and device fabrication.
EDUCATION
Doctorate of Philosophy, Electrical Engineering Graduation Date: July 2015
University of Cincinnati, Cincinnati, USA GPA (3.9/4.00)
Bachelor of Technology, Electronics and Instrumentation Engineering Graduated: June 2011
West Bengal University of Technology, Calcutta, India GPA (8.31/10.00)
TECHNICAL SKILLS
Software and Office Applications
o MS Office, MATLAB, AUTOCAD, CFD, ImageJ, C
Characterization and Analytical Applications
o Extensive experience in
Photo Lithography
Vacuum deposition : CVD, PECVD, PVD,
ALD , Plasma Sputtering
Silicon Micro fabrication/ Fabrication on glass
/flex substrates
Soft Lithography
Lift-off process
Optical Characterization
Electrophoresis/ Electro-kinetics
Ellipsometry
Laser Micromachining
Circuit Printing
Color Science
Spectrometry
Wet and dry etching
Acquired necessary skills to perform
Contact angle measurement
Electrowetting
Scanning Electron Microscopy
Dielectrophoresis
PROFESSIONAL EXPERIENCE
Fundamentals and Applications of Large area multi-spectral state Electrophoretic Panels for Displays and Smart
Windows September 2011-July 2015
PhD Dissertation, Research Assistant
College of Engineering and Applied Science, University of Cincinnati
o Developed the first single layer color system (Biprimary color system) operated multi-color switching electrophoretic
display for E-paper applications.
o Developed a novel electrokinetic Display device operating with single layer color system that switches in multi-spectral (4
color states) and can be micro replicable and printable on non-flexible/flexible substrates
o Developed a novel application of smart window using dual-particle electrophoretic dispersions that can separately
modulate incoming light for color temperature modulation.
COURSEWORK PROJECTS
Developing a Passive micro mixer using CFD simulation followed by experimental results
January 2012-April 2012
Curriculum Project, College of Engineering and Applied Science, University of Cincinnati
Simulated the model using CFD and fabricated the passive micromixer using soft lithography process, followed by the
experimental results of micro mixing two fluids.
Developing a Circuit for an automatic door opening system and alarm using Laser sensor
September 2010-June 2011
Final Year Project, West Bengal University of Technology
Developed an entire circuit for demonstration of a Laser guided automatic door opening system and alarm.
2. PUBLICATIONS AND PATENTS
Journal Publications related to PhD dissertation:
o Sayantika Mukherjee, Nathan Smith, Mark Goulding, Qin Liu, Laura Kramer and Jason Heikenfeld, Electrokinetic
Pixels with Biprimary Inks for Color Displays and Color Tunable Smart Windows , Applied Optics, 54 (17) 2015
(cover story)
o Sayantika Mukherjee, Nathan Smith, Mark Goulding, Claire Topping, Sarah Norman, Qin Liu, Laura Kramer, Senal
Kularatne, Jason Heikenfeld, A first demonstration and analysis of the biprimary color system for reflective
displays, Journal of the Society for Information Display, , 22, 1, 2014.
Other publications:
o S. Mukherjee, S. Su, W. Panmanee, R.T. Irvin D. Hassett and S. Choi A Microliter-scale Microbial Fuel Cell Array
for Bacterial Electrogenic screening. Sensors and Actuators A: Physical, 2013 Vol (201)
o A. Fraiwan, S. Mukherjee, S. Sundermeir, H. Lee and S. Choi, A Paper-based Microbial Fuel Cell: Instant Battery for
Disposable Diagnostic Devices. Biosensors and Bioelectronics, Vol 49, 2013
Conference Proceedings
o Invited Speaker: Sayantika Mukherjee, Jason Heikenfeld, Nathan Smith, Mark Goulding, Claire Topping, Sarah
Norman, Qin Liu, Laura Kramer, “ Biprimary Dual-Particle Electrokinetic Displays with 70% Reflectance and Greatly
Improved Color saturation” IDW’14, Niigata, Japan, Dec 3rd
2014.
o Sayantika Mukherjee, Jason Heikenfeld, Nathan Smith, Mark Goulding, Claire Topping, Sarah Norman, Qin
Liu, Laura Kramer, 59.4L: Late-News Paper: The Biprimary Color System for E-Paper: Doubling Color Performance
Compared to RGBW, SID Symposium Digest of Technical Papers, 2014, 45, 1
o A. Fraiwan S. Mukherjee, S. Sundermeir, and S. Choi, A Microfabricated Paper-based Microbial Fuel Cell, IEEE
MEMS Conference, Taipei, Taiwan, 2013.
Patent
o S. Mukherjee and J. Heikenfeld Easily Scalable and Grayscale Capable Two-particle Electrophoretic Optical Device,
UC 114-061, United States, 2014
RELEVANT GRADUATE COURSEWORK
Optoelectronics Optics for Engineers
Microfabrication Electrofluidics
Biomicrosystems Linear Systems theory
Fundamentals of MEMS Plasma Processing
Silicon Microfabrication Laboratory
Biomedical MEMS
Bio Lab-on-Chips
Biosensors and Bioelectronics
Biomicrofluidics
AWARDS AND HONORS
University Graduate Scholarship, University of Cincinnati, Ohio (Fall 2011 – Summer 2015)
NSF Tuition sponsorship, National Science Foundation, GOALI # 1231668 (Fall 2012-Summer 2015)
PROFESSIONAL SERVICES
Mentored 3 undergraduate Research Co-op Students in microfabrication, photolithography and optical characterization,
University of Cincinnati
Mr. Senal Kularatne, Electrical Engineering (2017), University of Cincinnati, August 2013-Dec 2013
Mr. Hyuen Thinh Nguyen, Electrical Engineering (2017), University of Cincinnati Jan 2014-April 2014
Ms. Desiree Sanchez, Electrical Engineering (2017), University of Cincinnati, May 2014-August 2014
Teaching Assistant:
Introduction to Digital Design: Spring 2012
Solid State Electronics: Summer 2012
Optics for Engineers: Fall 2013
Memberships
Student Member of Society for Information Display (SID) Feb 2014- present
REFERENCES: Dr. Jason C. Heikenfeld (Advisor) Professor, School of Electrical and Computing Systems, University of
Cincinnati. Email: heikenjc@ucmail.uc.edu
