Soumyabrata Dey

Biography

Soumyabrata received his M.S. and Ph.D. in Computer Science from the University of Central Florida in the years of 2011 and 2014. During his Ph.D., his main research focus was on biomedical image and video data analysis. Additionally, he worked on topics such as moving objects detection from a moving camera and multi-object tracking. His research on ADHD detection from brain imaging data produced the state-of-the-art result at the time of publication, and it was among the first few works on the topic. Before joining Clarkson, he worked at Samsung Research Institute, Bangalore as a chief engineer and Carl Zeiss as the research lead. During his industry period, he has worked on many interesting and challenging research problems like biometric authentication, mobile sensor data analysis for predictive healthcare, and 3D image analysis for defect identification in industrial parts. Soumyabrata’s active research tracks at Clarkson include gesture-based human-computer interaction, scene understanding from multi-modal sensor data, optimization of 3D reconstruction pipeline, biometric authentication, and biomedical & healthcare data analytics. Soumyabrata also likes playing outdoor sports, travelling and spending time with his family.

Education Background

Computer Vision Ph.D. - 2014 University of Central Florida
Computer Science M.S. - 2011 University of Central Florida
Computer Science and Engineering B.T. - 2005 West Bengal University of Technology

Experience

Postdoctoral Researcher Associate and Lecturer Clarkson University,
Research Lead Carl Zeiss, IMT R&D,
Chief Engineer Samsung Research Institute, Bangalore,

Research Interests

• Context awareness: automatic scene learning including real-time 3D digital reconstruction, detection of objects and their 3D locations, and understanding object characteristics
• Sensor data analytics: intelligent decision making and action performance through ML, DL, RL techniques on multi-modal sensor data
• Biometric authentication
• Healthcare & biomedical data analysis

Grants

• Principal Investigator: NSF, CITeR 2022: A Study to Benchmark Smartphone Hardware and Software for High Quality Iris Data Collection ($50,000).
• Principal Investigator: NSF, CITeR 2021: Presentation Attack Detection for Noncontact Fingerprint Systems ($50,000).
• Co-Principal Investigator: NSF, CITeR 2021: A Deep End-to-End Iris Matcher for Simultaneous Segmentation and Matching ($50,000).

Patents

• V. N. Tiwari, S. Dey, R Narayanan, S Sahoo, A. De, “Method and mobile device for determining Ultraviolet (UV) dose using non-UV sensor''. Filing No. in 201641031912
• R. Rao, S. Dey, M. Shah, B. Solmaz, “Method and system for modeling and processing fMRI image data using a bag-of-words approach”. Publication No. US9072496 B2

Publications

• X. Zhang, M. Li, A. Hilton, A. Pal, S. Dey, S. Debroy, "End-to-End Latency Optimization of Multiview 3D Reconstruction for Disaster Response", MobileCloud 2022.
• S. Li, S. Banerjee, N. Banerjee, S. Dey, "Simultaneous Prediction of Hand Gestures, Handedness, and Hand Keypoints using Thermal Images", ICDEC 2022.
• M. Nguyen, J. Gately, S. Kar, S. Dey, S. Debroy, "DNN-based Denial of Quality of Service Attack on Software-defined Hybrid Edge-Cloud Systems",WAMICON 2022.
• M. Babaeianjelodar, G. P. Prudhvi, S. Lorenz, K. Chen, S. Mondal, S. Dey, N. Kumar, "Explainable and High-Performance Hate and Offensive Speech Detection", HCII 2022.
• J. Bellow, S. Banerjee, N. Banerjee, S. Dey, "Real-Time Hand Gesture Identification in Thermal Images", ICIAP 2021.
• A. R. Rao, S. Garai, S. Dey, H. Peng, "PIKS: A Technique to Identify Actionable Trends for Policy- Makers Through Open Healthcare Data", SN Computer Science 2021.
• P. Athavale, S. Dey, S. Dharmatti, A. S. Mathew, “A Novel Entropy-Based Texture Inpainting Algorithm”, Signal, Image and Video Processing – Springer, 2020 (impact factor 2.157).
• A. R. Rao, S. Garai, S. Dey, H. Peng, "Building predictive models of healthcare costs with open healthcare data", ICHI 2020.
• J. Gately, Y. Liang, M. K.Wright, N. Banerjee, S. Banerjee, S. Dey, "Automatic Material Classification using Thermal Finger Impression", MMM 2020 (oral).
• A. Rao, D. Clarke, S. Garai, S. Dey, "A system for exploring big data: an iterative k-means searchlight for outlier detection on open health data", IJCNN 2018 (oral, rank A).
• S. Dey, S. Sahoo, H. Agrawal, A. Mondal, T. Bhowmik, V. N. Tiwari, "Personalized Cumulative UV Tracking on Mobile &Wearables", EMBC 2017 (rank B).
• S. Karmakar, S. Dey, S. Sahoo, "Towards Semantic Image Search", ICSC-SMM 2016.
• S. Dey, R. Rao, M. Shah, “Attributed graph distance measure for automatic detection of attention deficit hyperactive disordered subjects”, Frontiers in Neural Circuit June 2014 (impact factor 3.492).
• S. Dey, R. Rao, M. Shah, “Exploiting Brain’s Network Structure in Classifying ADHD”, Frontiers in Systems Neuroscience Nov 2012 (impact factor 3.289).
• S. Dey, V. Reilly, I. Saleemi, M. Shah, “Detection of Independently Moving Objects in Non-planar Scenes via Multi-Frame Monocular Epipolar Constraint”, ECCV 2012 (rank A).
• B. Solmaz, S. Dey, R. Rao, M. Shah, “ADHD Classification Using Bag of Words Approach on Network Features”, SPIE 2012.
• S. Basu, S.S. Seth, P. Sarkar, B. Das, S. Dey, S. Ghosh, "Development of a Multilingual Recognition Engine for Automatic Interpretation of Handwritten Form Documents", Computer Processing of Bangla 2005.