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Ashish Gupta

Postdoctoral Researcher

Senior Research Scientist : Machine & Deep Learning | Computer Vision

Cleveland, Ohio

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Ashish Gupta's Work Experience

The Ohio State University

Postdoctoral Researcher

February 2015 to Present

Columbus, Ohio Area

Université de Caen Basse-Normandie

Postdoctoral Research Fellow

September 2013 to December 2014

Caen Area, France

University of Surrey

PhD Candidate

July 2008 to August 2013

Guildford, United Kingdom

Ashish Gupta's Education

University of Surrey

PhD Machine Learning, Computer Vision

2008 to 2013

Indian Institute of Technology, Kanpur

M.Tech. Electrical Engineering

2004 to 2006

University of Mumbai

B.E. Electrical and Electronics Engineering First Class

1999 to 2003

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About Ashish Gupta's Current Company

The Ohio State University

Research in computer vision applied to trajectory estimation and localization using camera on a mobile platform. Directing work in the Photogrammetry and Computer Vision lab within the department of civil, environment, and geodetics engineering at the Ohio State University.

Frequently Asked Questions about Ashish Gupta

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Ashish Gupta works for The Ohio State University

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Ashish Gupta is Postdoctoral Researcher

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Ashish Gupta's phone (216) ***-*222

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Ashish Gupta works in the Research industry.

About Ashish Gupta

📖 Summary

Pattern recognition is a treasure hunt for the chest of information in a sea of data. There is a beauty to the simplest accurately predictive model, which is a reward in itself - for a data scientist. This has been my vision for over the past ten years as I have explored the fields of Machine Learning, Computer Vision, Signal and Image Processing, and Data Analysis. My first significant project was noise reduction using Wavelet techniques and computation of novel wavelets optimized to the data using Genetic Algorithms. Next, I built an OCR engine using Artificial Neural Networks. Later, I developed algorithms for analysis and synthesis of unconstrained handwriting and also signature verification with focus on statistical analysis for anomaly detection. Image data analysis and machine learning make an effective combination that I have utilized in several short term projects including image Super-resolution, Biometric authentication, EO/IR video fusion, and video stabilization using Kalman filters. Subsequently, I researched Content Based Image Retrieval and Classification. I worked with huge volumes of high-dimensional and noisy data to harvest semantic relations. I explored dimensionality reduction, Clustering, incorporated Fuzzy Logic into image models, and combined Co-clustering inspired by Bioinformatics and Sparse Coding inspired by Neurosciences to learn a structured semantic model. Moving beyond structure and semantics to a perceptual layer, I currently analyze images to learn descriptors and models for aesthetics and interestingness in photographs. Besides R&D, I have been teaching assistant in mathematics courses, electronics labs, and leadership workshops. Contributions to the editorial and management committees at IEEE have fostered leadership and entrepreneurship skills used subsequently in academia and industry. I am a machine vision and learning scientist and developer looking for my next pattern recognition in big data challenge.Postdoctoral Researcher @ Research in computer vision applied to trajectory estimation and localization using camera on a mobile platform. Directing work in the Photogrammetry and Computer Vision lab within the department of civil, environment, and geodetics engineering at the Ohio State University. From February 2015 to Present (9 months) Columbus, Ohio AreaPostdoctoral Research Fellow @ This research is funded by "Q-Compare" project. The objective of my research is analysis of large personal collection of photographs to automatically select 'interesting' and 'aesthetic' exemplars from the corpus. I am working on multiple modules of a typical image analysis pipeline for such a task. One module focusses on analysis of images and research on quality photography guidelines to build novel image descriptors that can represent perceptual qualities, whereas standard descriptor represent structural properties of texture and color. Second module is development of machine learning appraoch to model images descriptors using clustering techniques. The third module is training classifiers to predict image perceptual quality. From September 2013 to December 2014 (1 year 4 months) Caen Area, FrancePhD Candidate @ Developing novel machine learning algorithms for generic object category recognition in the wild. This work is within the framework of the EPSRC funded project DIPLECS, which aims at developing an automated driver assistance system. The work entails research and development of methods for object recognition, feature selection, dimensionality reduction, data mining, and classifiers. It leads to a doctoral degree from the University of Surrey. Thesis: Learning a Structured Model for Visual Category Recognition Advisor: Prof. Josef Kittler, Prof. Richard Bowden (CVSSP) From July 2008 to August 2013 (5 years 2 months) Guildford, United KingdomTeaching Assistant @ Teaching undergraduate students in courses: Electronics Lab project (1st and 2nd Year); Engineering Mathematics (1st and 2nd Year); Teamwork & Leadership (2nd and 3rd Year). The work includes class-room teaching, demonstration in laboratory, regular assessment of mid-term work, and final grading of semester work. From October 2008 to June 2013 (4 years 9 months) Guildford, United KingdomR&D Software Engineer @ Research and Development in the Applied Vision Group. Algorithm and software solutions for advanced computer vision industrial applications. Medium term projects worked on included: (1) Video stabilization using Kalman filters, contribution focussed on extending Kalman filters for video stabilization during camera panning and zooming. (2) Visible and Infra-Red video fusion, contributed to EO/IR camera installation and calibration and image registration and video synchronization. (3) Biometrics based authentication for mobile phones, surveyed image based biometrics for mobile platform with focus on face recognition. (4) Image super-resolution for mobile phones, researched several methods with focus on single image super-resolution. Short term projects worked on included: (1) Number plate detection, implemented car number plate detection for low-light parking lots. (2) Large scale surveillance camera system, involved operational research methods for optimizing surveillance camera system for large scale, low-cost applications. Work on the biometrics project lead to application for patent “Biometric based client authentication for mobile phone value added services.” Inventors: Ashish Gupta, Arvind Lakshmikumar. Assignee: Sarnoff Corp. From August 2006 to July 2008 (2 years) Bangalore, IndiaTeaching Assistant @ Laboratory demonstration, teaching, and student assessment for: (1) Speech & Signal Processing on ADSP 2101 using Artificial Neural Networks. (2) Analog and Digital Electronics Lab for course ESC102. From August 2004 to June 2006 (1 year 11 months) Kanpur Area, IndiaPhD, Machine Learning, Computer Vision @ University of Surrey From 2008 to 2013 M.Tech., Electrical Engineering @ Indian Institute of Technology, Kanpur From 2004 to 2006 B.E., Electrical and Electronics Engineering, First Class @ University of Mumbai From 1999 to 2003 HSC, Electrical and Electronics Engineering, First Class Honors @ K.C. College From 1997 to 1999 Secondary School Certificate, First Class @ St. Joseph's High School From 1990 to 1997 Ashish Gupta is skilled in: Computer Vision, Machine Learning, Image Processing, Signal Processing, C++, Pattern Recognition, Matlab, Python, Data Analysis, Artificial Intelligence, Research, LaTeX, Mathematical Modeling, Linux, Java, Embedded Systems, Data Mining, Optimization, Statistical Modeling, Poetry, R&D, OpenCV, Image Analysis, Video Processing, Computer Science, Teaching, Creative Writing, Leadership, Simulink, CUDA, Information Retrieval, Image Segmentation, Object Recognition, Digital Signal..., Applied Mathematics, Information Theory, Numerical Analysis, R, OpenGL, JavaScript, HTML 5, Big Data, NoSQL, Algorithms, Statistics, SQL, C, Robotics, Programming, Software Development

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Introversion (I), Sensing (S), Thinking (T), Perceiving (P)

Average Tenure

2 year(s), 7 month(s)

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