Image of Raghuraman Gopalan

Raghuraman Gopalan

Senior Scientist @ AT&T Labs-Research

Principal Scientist - Machine Learning at AT&T Research

San Francisco Bay Area

Ranked #1,093 out of 21,860 for Senior Scientist in United States

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Raghuraman Gopalan's Email Addresses & Phone Numbers

Raghuraman Gopalan's Work Experience

AT&T Labs-Research

Senior Scientist

2011 to Present

Greater New York City Area

University of Maryland

Graduate Research Assistant

2005 to 2011

Washington D.C. Metro Area

Honda Research Institute USA, Inc.

Research Intern

June 2008 to August 2008

San Francisco Bay Area

Raghuraman Gopalan's Education

University of Maryland, College Park, USA

Ph.D. Electrical and Computer Engineering

2005 to 2011

College of Engg., Guindy, Anna University, Chennai, India

Bachelor of Engineering Electronics and Communication

2001 to 2005

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Raghuraman Gopalan's Estimated Salary Range

About Raghuraman Gopalan's Current Company

AT&T Labs-Research

Research on heterogeneous data analytics, predictive modeling from big data, and large-scale classification problems.

Frequently Asked Questions about Raghuraman Gopalan

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Raghuraman Gopalan's colleagues are Binnur Altiok, Barry Reynolds, Ingrid Nunez, Blair Johnson, Garry Mack, Michael J. Weinstein, Asha Holla, Will Kline, Eduard Lysak, and William Rice


About Raghuraman Gopalan

📖 Summary

My work is centered around large-scale unstructured data analytics, which spans the broad areas of machine learning, pattern recognition, AI and computer vision. I am specifically working on problems related to big data in the Internet-of-Things (IoT) space, which involves understanding heterogeneous data modalities such as video, voice and chat to perform tasks related to prediction, regression, and classification in general. The following is a list of selected projects I have worked on: 1) Anomaly detection - identifying outlier/novel patterns to enable earlier detection of customer service quality problems, network outage issues, new visitors to a home or retail store, and customer fraud. 2) Predictive analytics - learning prediction models to suggest relevant content/products based on the user's prior history, placing advertisements, estimating service churn and willingness to recommend. 3) Big data domain adaptation - accommodating new data characteristics to actively update the learner to perform tasks such as object/scene classification, indoor-outdoor speech/activity recognition, heterogeneous geo-location, and multi-product sentiment analysis. 4) Face analysis - detection, recognition, and multi-modal biometric verification of human faces with applications to active authentication in smartphones, wearables, and tablets. Personalizing the modules to the user's data over time to improve performance accuracy. 5) Intelligent vehicles - road scene analysis using machine learning for detecting people, lane markings and global road layout to enable autonomous transportation. 6) Robotic gestures - Interpreting active gestures using learning and shape theoretic methods to enable prosthetic robotic grasping, and N-dimensional object segmentation for graphics.Senior Scientist @ Research on heterogeneous data analytics, predictive modeling from big data, and large-scale classification problems. From 2011 to Present (4 years) Greater New York City AreaGraduate Research Assistant @ Investigated model-driven, and data-driven approaches for object recognition problems. Application areas include, articulation-invariant shape representation, face recognition across blur and lighting, maximum margin clustering, unsupervised domain adaptation for statistical classifiers, and contextual models for generic object recognition. From 2005 to 2011 (6 years) Washington D.C. Metro AreaResearch Intern @ Developed algorithms and a system for real-time hand gesture recognition. From June 2008 to August 2008 (3 months) San Francisco Bay AreaResearch Intern @ Algorithm development for human detection under occlusion. From June 2007 to August 2007 (3 months) Greater Minneapolis-St. Paul AreaPh.D., Electrical and Computer Engineering @ University of Maryland, College Park, USA From 2005 to 2011 Bachelor of Engineering, Electronics and Communication @ College of Engg., Guindy, Anna University, Chennai, India From 2001 to 2005 Raghuraman Gopalan is skilled in: Machine Learning, Algorithms, Optimization, Big Data Analytics, Predictive Analytics, IoT, Pattern Recognition, Computer Vision, Signal Processing, Object Recognition, Computer Science, Artificial Intelligence, Domain Adaptation, Transfer Learning, Image Processing


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Raghuraman Gopalan's Personality Type

Extraversion (E), Sensing (S), Feeling (F), Judging (J)

Average Tenure

2 year(s), 7 month(s)

Raghuraman Gopalan's Willingness to Change Jobs

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