Hamed Mohebbi Email & Phone Number

Boston, MA, US

Boston, Massachusetts, United States

Cambridge, Massachusetts, United States

Boston, Massachusetts

- Machine learning application in acoustic signal analysis. Worked on development of a large-aperture coherent hydrophone array, data processing and analysis software system for real-time instantaneous wide-area passive acoustic monitoring of marine mammals, including beamforming, detection, DoA estimation, and classification of marine mammals sounds..

Greater Boston

During this co-op experience, I worked on a variety of projects including:- Worked on audio event detection project pipeline design, including data gathering, preprocessing, labeling, and storing pipeline, and implementing Deep Learning model (CNN+attention) as a baseline for audio event detector - Analyzed regression approaches for multi-sensor clocks.

Tehran Province, Iran

- Developed a system for media content analysis using deep learning to monitor and analyze the statistics of contents, in which the Machine Learning module interacts with data in JSON format data packets using Flask RESTful API- Trained deep CNN models in Tensorflow and Keras frameworks to classify the contents of images, including scene recognition, sport.

Tehran Province, Iran

I lectured and taught the TA classes about Deep Learning. The materials are mainly about teaching python programming (Numpy, sci-kit learn, matplotlib, scipy,...), Keras Deep Learning library combined with some theoretical basics of deep learning (network initialization, batch norm, different optimizations, different network architectures). Concepts like.

Tehran Province, Iran

- Worked on bio-metric and identity verification using facial image processing, which implemented on a Raspberry-Pi used in an identity verification system in the entrance door to enter the office- Applied both the classical computer vision methods (SIFT features + Fisher vector representation) and Deep Learning based methods (MTCNN face detection +.

Biomedical Signal And Image Processing Laboratory (BiSIPL)

- Worked on pain level estimation using facial expression in video as a regression problem by applying time-series analysis in video using Kalman filter and Particle filter- Conducted research on medical images processing, including MRI brain image segmentation utilizing fuzzy c-means and Total Variation based methods- Applied image denoising methods such.

Doctor Of Philosophy - Phd, Electrical, Electronics And Communications Engineering, 4.0/4.0

Master’S Degree, Biomedical Engineering /Bioelectric, 17.86 / 20

Bachelor’S Degree, Biomedical Engineering / Bioelectric, 17.94 / 20