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Abdolreza Abdolhosseini Moghadam

from San Jose, CA
Age ~44
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Also known as:
Abdolreza A Moghad, Abdolreza Abdolhosseini, Abdolreza M
Related to:
Nima Moghadam
Connected to:
Ahmad A Moghadam, 76Amir Z Moghadam, 67Jahanfar Moghadam, 61Julie A Moghadam, 52Lida Moghadam, 78Mitra R Moghadam, 59Mohsen Moghadasi, 34Peyman S Moghadam, 54Valentine M Moghadam, 72Alfiya F Moghaddam, 52

Abdolreza Moghadam Phones & Addresses

  • San Jose, CA
  • Lansing, MI
  • Okemos, MI
  • East Lansing, MI

Work

Company: Michigan state university Jun 2007 Position: Research assistant

Education

School / High School: Michigan State University- East Lansing, MI 2007 Specialities: Phd in Electrical and Computer Engineering

Skills

Solid understanding of advanced digital ... • most notably compressed sensing and affi... • video representation/modeling and MPEG s... • system modeling and algorithm developmen... • debugging and simulation for both embedd... • UNIX) • shell programming and developing device ... • debugging • verification flows and methodologies for... • as well as FPGA targets. Solid knowled...

Resumes

Resumes

Abdolreza Moghadam Photo 1

Abdolreza Moghadam Lansing, MI

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Work:
Michigan State University

Jun 2007 to Present
Research Assistant
Eastman Kodak
Rochester, NY
Jun 2011 to Aug 2011
Research Intern
Technicolor (Thomson)
Princeton, NJ
Jun 2010 to Aug 2010
Summer Intern
Tehran Municipality
Tehrn
2004 to 2007
team lead, system designer
Sharif University of Technology
Tehrn
2003 to 2007
research assistant
Semiconductor industries of Iran
Tehrn
2003 to 2004
team lead, consultant
Education:
Michigan State University
East Lansing, MI
2007
Phd in Electrical and Computer Engineering
Sharif University of Technology
Tehrn
2003 to 2006
Bachelor of Science in Computer Engineering/Hardware
Sharif University of Technology
Tehrn
MSc in Computer Engineering
Skills:
Solid understanding of advanced digital signal processing techniques and theories, most notably compressed sensing and affine constraint rank minimization. Solid understanding of advanced image and video processing techniques such as color image demosaicing, video representation/modeling and MPEG standard. Solid knowledge in simulations, system modeling and algorithm development of complex systems with MATLAB and Mathematica (6+ years). Proficient in C/C++ (4+ years) coding, debugging and simulation for both embedded as well as desktop platforms. Knowledge of OS (Windows, UNIX), shell programming and developing device drivers. Experience with Verilog/VHDL (2+ years) code development, debugging, verification flows and methodologies for both ASICs, as well as FPGA targets. Solid knowledge of digital hardware design and embedded systems (3+ years).

Publications

Us Patents

Scene Boundary Determination Using Sparsity-Based Model

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US Patent:
20130235275, Sep 12, 2013
Filed:
Mar 7, 2012
Appl. No.:
13/413982
Inventors:
Mrityunjay Kumar - Rochester NY, US
Abdolreza Abdolhosseini Moghadam - Okemos MI, US
Alexander C. Loui - Penfield NY, US
Jiebo Luo - Pittsford NY, US
International Classification:
H04N 5/14
US Classification:
348700, 348E05062
Abstract:
A method for determining a scene boundary location dividing a first scene and a second scene in an input video sequence. The scene boundary location is determined responsive to a merit function value, which is a function of the candidate scene boundary location. The merit function value for a particular candidate scene boundary location is determined by representing the dynamic scene content for the input video frames before and after candidate scene boundary using sparse combinations of a set of basis functions, wherein the sparse combinations of the basis functions are determined by finding a sparse vector of weighting coefficients for each of the basis functions. The weighting coefficients determined for each of the input video frames are combined to determine the merit function value. The candidate scene boundary providing the smallest merit function value is designated to be the scene boundary location.

Video Representation Using A Sparsity-Based Model

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US Patent:
20130235939, Sep 12, 2013
Filed:
Mar 7, 2012
Appl. No.:
13/413962
Inventors:
Mrityunjay Kumar - Rochester NY, US
Abdolreza Abdolhosseini Moghadam - Okemos MI, US
Alexander C. Loui - Penfield NY, US
Jiebo Luo - Pittsford NY, US
International Classification:
H04N 7/30
US Classification:
37524018, 375E07226
Abstract:
A method for representing a video sequence including a time sequence of input video frames, the input video frames including some common scene content that is common to all of the input video frames and some dynamic scene content that changes between at least some of the input video frames. Affine transform are determined to align the common scene content in the input video frames. A common video frame including the common scene content is determined by forming a sparse combination of a first basis functions. A dynamic video frame is determined for each input video frame by forming a sparse combination of a second basis functions, wherein the dynamic video frames can be combined with the respective affine transforms and the common video frame to provide reconstructed video frames.

Methods And Apparatus For Video Encoding And Decoding Using Motion Matrix

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US Patent:
20130223523, Aug 29, 2013
Filed:
Oct 10, 2011
Appl. No.:
13/879349
Inventors:
Abdolreza Moghadam - Okemos MI, US
Joel Sole - La Jolla CA, US
Xiaoan Lu - Princeton NJ, US
Assignee:
Thomson Licensing - Issy Les Moulineaux
International Classification:
H04N 7/26
US Classification:
37524003, 37524016
Abstract:
Methods and apparatus are provided for video encoding and decoding using a motion matrix. An apparatus includes a video encoder for encoding a picture in a video sequence using a motion matrix. The motion matrix has a rank below a given threshold and a sparse representation with respect to a dictionary. The dictionary includes a set of atoms and basis vectors for representing the picture and for permitting the picture to be derived at a corresponding decoder using only the set. The dictionary formed from a set of reference pictures in the video sequence.

Systems And Methods For Dynamic Pricing Of Food Items

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US Patent:
20210241338, Aug 5, 2021
Filed:
Jan 12, 2021
Appl. No.:
17/248170
Inventors:
Abdolreza Abdolhosseini MOGHADAM - San Jose CA, US
Sara SOHRABI - San Jose CA, US
International Classification:
G06Q 30/06
G06Q 30/02
Abstract:
A system and method for dynamic pricing of food items that are configured to apply one or more algorithms to prepare adjustments in the food item ingredient composition (e.g., the recipe of a food item) to accommodate a desired price, caloric content, dietary restriction requirement, and/or nutritional value. The system will process the customer-user's inputs of a modification of the ingredients for the food item. System processes for recipe modifications can be made in real-time, and may be locally processed or remotely processed, e.g., via access to a network server. Optionally, some or all of the system processes for recipe modifications may be preprocessed and stored in a system-accessible database. In some embodiments, a custom designed secure hardware component is deployed in the system in order to protect confidential pricing data, and gives a tool for managing the dynamic sales for a food retail establishment.

Systems And Methods For Dynamic Pricing Of Food Items

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US Patent:
20180218414, Aug 2, 2018
Filed:
Oct 7, 2016
Appl. No.:
15/747556
Inventors:
Abdolreza Abdolhosseini MOGHADAM - San Jose CA, US
Sara SOHRABI - San Jose CA, US
International Classification:
G06Q 30/02
G06Q 30/06
G06Q 50/12
Abstract:
A system and method for dynamic pricing of food items that are configured to apply one or more algorithms to prepare adjustments in the food item ingredient composition (e.g., the recipe of a food item) to accommodate a desired price, caloric content, dietary restriction requirement, and/or nutritional value. The system will process the customer-user's inputs of a modification of the ingredients for the food item. System processes for recipe modifications can be made in real-time, and may be locally processed or remotely processed, e.g., via access to a network server. Optionally, some or all of the system processes for recipe modifications may be preprocessed and stored in a system-accessible database. In some embodiments, a custom designed secure hardware component is deployed in the system in order to protect confidential pricing data, and gives a tool for managing the dynamic sales for a food retail establishment.
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Abdolreza Abdolhosseini Moghadam from San Jose, CA, age ~44 Get Report