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Click here or scroll down to respond to this candidateCandidate's Name , PH.D.Email: EMAIL AVAILABLE, LinkedIn: LINKEDIN LINK AVAILABLESUMMARYSenior-level research scientist specializing in formulating and executing complex multidisciplinary R&D projects across various industries, including manufacturing, biometrics, personalized medicine and applied science. Expert in employing modern and classic tools of Applied Math and Computer Science such as Artificial Intelligence, Machine Learning, Computer Vision, and Pattern Recognition. A proactive problem solver with flexible approach, able to quickly adjust strategies when necessary. My scientific methodology is rooted in the belief that a deep understanding of problems is essential for devising effective solutions. Hold a PhD in applied math; have published in peer-reviewed journals, presented at major scientific conferences, and authored US patents and applications.SKILLS HIGHLIGHTSExpertise: Artificial Intelligence, Machine/Deep Learning, Pattern Recognition, Computer Vision, Image Analysis, Data Science, Iris Recognition, Personalized Medicine, Computational Fluid Dynamics.Analytical Skills: Modeling & Simulation, Statistical Signal Processing, Spectral Analysis, Statistical Modeling, Stochastic Processes, Time Series.Data Analysis: Supervised/Unsupervised/Active Learning, Feature Selection, Classification, Linear and Non-Linear Regression, Bayesian, Statistics Hypothesis Testing.Tools: MATLAB, PYTHON, TensorFlow, OpenCV, SCIKIT-LEARN, SCIPY, NUMPY, SimPy, GIT, SHAPELY, TRIMESH.PROFESSIONAL EXPERIENCEFraunhofer-USA CMA, Riverdale MD, Senior Research Scientist 11/2021 4/2024Fraunhofer USA, Inc. is an R&D organization working with industry, and state and federal governments on research projects. Working at the Data Science and AI group, leveraged my expertise in feature selection-based machine learning modeling techniques, Python coding, and research to drive advancements in several key projects:Predictive Maintenance: Formulated and successfully completed key project objective: creation of a statistical model that a) identifies instant loads acting on the bearings using signals from vibration sensors, and b) issues a warning when the loads attain extreme levels. Submitted and presented a technical report.3D Printing: Played a constructive role in the project design; analyzed and visualized experimental data; offered and implemented a novel method (regression modeling) how to determine printer parameters to obtain parts with desired mechanical properties. Submitted and presented a technical report.AI-Based Quality Control in Laser Cutting and Welding: Worked on the core development AI control module in the multidisciplinary complex project; created an efficient method to monitor the hot zone (image segmentation region detection feature computing). Trained a machine learning model to predict post-process quality.AI-based Control of Optical Micro-Assembly: Instrumental in the project design, conceptualized counter-collision approach; created a critical to the project automated inspection method that combines a 3D scene geometry with shape and orientation analysis of parts prepared for an assembly.Intelligent Quality Control Systems: Comprehensive research of state-of-the-art quality control systems.CrowdDoing Organization, San Francisco, CA, Pro Bono Chief Data Science Officer 03/2020 PresentCrowdDoing is a non-profit dedicated to mitigating wildfire perils through the selection of preventive solutions that minimize regional wildfire losses. Accomplished contributions in the following areas:Wildfire R&D: Lead data scientists and college students in identifying patterns in weather, vegetation, and terrain that raise the risk of anomalous wildfire events. Employed machine learning, time series analysis, and statistical methods to explore and visualize extensive datasets. Conducted a detailed analysis of historic air pollution data to pinpoint major contributors (particulate matter, carbon monoxide, ozone) resulting from wildfires, aiding in the identification and mitigation of pollution sources.Management: Facilitate organization's strategic planning, contributing to grant writing, delivering presentations, and collaborating with pro bono teams from leading US and Canada universities to further the foundation's mission.ImageSignal R&D Consulting, Stamford, CT, Chief Scientific Officer 07/2010 10/2021ISRND, my private consulting firm, merges the design and application of image/signal processing algorithms across medical and engineering fields. Key accomplishments include:Deep Learning: Customized MaskRCNN (object detection and segmentation) training to function in environments with constrained computing resources.Dynamic Image Clustering: Created dynamic image cluster algorithm by integrating an autoencoder with k-means clustering for scenarios when the number of clusters is unknown.Genome mutations on pathology images: Conceptualized prediction of genome mutations in lung-cancer images, enhancing diagnostic precision.Cancer Aggressiveness: Conducted a study in collaboration with Memorial Sloan Kettering Cancer Center to evaluate tumor aggressiveness using lesion boundary geometry, applying fractal geometry and texture analysis to MRI breast images.Cancer Survival in Precision Medicine: Collaborated with Cleveland Clinic to develop an advanced statistical model aimed at improving survival prediction rates for colon cancer patients. The model integrates quantitative imaging features with clinical records, focusing on active learning to identify informationally rich tumor sub-regions maximizing survival prediction. Presented at scientific conferences and submitted for a US patent.Siemens Corp., Research Group, Princeton NJ, Senior Key Expert 04/2021 09/2021Computer Vision in Beverage Production: Developed an efficient computer vision algorithm to correctly orient beverage cans placed randomly on a moving conveyor belt.AI in Battery Manufacturing: Proposed an innovative concept for an AI-driven quality control system specifically for Lithium-Ion battery production. This concept was pivotal in filing a US Patent Application.Genentech, Digital Pathology, San Fransisco, CA, Senior Research Scientist 10/2019 03/2020Medical Imaging: Engineered and coded image analysis techniques for processing exceptionally large images.Trove Predictive Data Science, Buffalo, NY, Senior Data Scientist 10/2018 04/2019Customer Segmentation: Devised customer segmentation technique to analyze energy consumption.Forecasting: Created a forecasting model for businesses by utilizing energy demand patterns in time series.EyeLock Corp., New York NY, Senior Research Scientist 09/2013 04/2018Contributed to key R&D projects on enhancing iris recognition software, developing identity management solutions, and creating counter-spoofing measures; filed two US Patent Applications. Major accomplishments include:Deep Learning in Iris Recognition: Designed a Convolutional Neural Network (CNN) for iris recognition, effectively navigating through constraints of limited computing resources and available labeled images.Stochastic Iris Model: Initiated and executed a research project to understand the origins of iris biometric signal. Created a stochastic model for the iris image intensity field, significantly enhancing biometric signal detection in noise. The model replaced traditional thresholds used in iris recognition. Efficiency was validated through rigorous matching experiments. Invented Biometric-Signal-To-Noise-Ratio, a novel metric to evaluate an iris recognition systems performance, analogous to the Signal-To-Noise Ratio in Digital Signal Processing.Biometrics in Financial Transactions: Analyzed a set of biometric measures minimizing financial losses due to erroneous identity verification. Employed the Kalman filter for identity estimation from previous biometric checks.Iris Counter-Spoofing Method: Developed an innovative method for iris recognition counter-spoofing, effectively distinguishing live iris images from those printed on paper, enhancing security against fraudulent access attempts.Novetta Solutions, New York, NY, Senior Researcher, Manager of Computer Vision 06/2011 09/2012Conceptualized and supervised development of an innovative computer system designed to generate synthetic biometric images of fingerprints, irises, and faces. Submitted R&D plans, technical reports to government agencies.Aureon Laboratories Inc., Yonkers, NY, Manager, Senior Bio-Imaging Scientist 10/2002 01/2009Machine Vision Technology: Led the successful development of a machine vision component for a prostate cancer outcome predictive test from inception to commercialization. This component was integral to a bio-statistical model within the systems biology framework, contributing to the advancement of personalized (precision) medicine.Prostate Tumor Recognition and Grading: Directed and developed computer vision methods combining supervised learning with feature selections from pathology images for accurate prostate tumor identification and grading.Biomarker Research: Created multivariate regression model for precise localization and measurements of biomarker signals in bio-images, enhancing signal discrimination from background noise.Management: Produced R&D plans, technical documentation, reports for board and executive management, presentations and papers, brainstormed meetings.Case Western Reserve University, Cleveland, OH, Research Scientist 03/1998 10/2000Modeled turbulent polymer flows using ANSYS Computational Fluid Dynamics package on a supercomputer. Created spatial meshing technology to accurately model the sophisticated 3D geometry of the flow chamber.EDUCATIONPhD - Computational Fluid & Gas Dynamics, Lomonosov Moscow State University, Moscow, RussiaMS - Applied Mathematics, Moscow Institute of Electronics and Mathematics, Moscow, RussiaPROFESSIONAL AFFILIATION: Senior Member of IEEE. |
