Syama Prasad Chaudhuri

* **** ******** ****, *********, MA 01460

301-***-****

ad0v89@r.postjobfree.com

Reference: Senior Project Manager Consulting Position in the areas of Systems Engineering, Machine Learning and Software Engineering

Professional Summary

Objective:

Project Management and Development in the areas of Data Processing, Data Analysis, Data Visualization, Data Association/Correlation, Data Classification, Data Modeling, Data Mining, Related Algorithms, Information Extraction for Decision Making, Business Analytics, Optimization, Artificial Intelligence, Cognitive Computing, Predictive Analytic, Prescriptive Analytics, Machine Learning, Advanced Algorithms and Quantitative Analysis, Simulation Modeling Analysis, and Evaluation of engineering systems and business applications.

25 years of research and development experience in the areas of Decision Making using various statistical modeling, SQL, artificial intelligence (AI), and machine learning (ML) techniques, Neural Networks, Supervised/Unsupervised Artificial Neural Network (ANN), Convolutional Neural Networks (CNNs) and Reinforcement.

Estimation of target image characteristics/parameters from a target image using MATLAB platform for matrix manipulation, functions and data plotting, user interface creation and interfacing with programs written in C/C++ and Python, and developing image processing algorithms in applications ranging from detection, identification and classification of vehicles, to missile guidance and object recognition and reconnaissance.

Interested in building requirements based critical solutions and delivering high value AI/Client solutions that drive customer and business value.

Interested in researching and building complex, cutting edge and scalable AI algorithms, models, platforms and technologies to significantly improve customer experience and drive business results.

Familiar with agile framework for developing, delivering, and sustaining complex products involving software development, research, sales, marketing and advanced technologies. For example, SCRUM, Kanban and other similar software programs.

Candidate Brief:

Syama is an experienced Data Scientist with a PhD in Electrical Engineering and a minor in Mathematics. He has excellent experience in Artificial Intelligence (AI) and Machine Learning (ML) technology. He taught AI and ML technologies in Harvard University, Northeastern University, and Boston University. He is proficient in Python and Python Library programs including Numpy, Pandas, Scikit-Learn for developing Machine Learning systems. He has experience in developing various machine learning algorithms and statistical modeling (like classification, clustering, decision trees, regression analysis and hypothesis testing). He has an excellent background in statistics and has been using statistical analysis techniques to determine various statistical data information, parameters, and characteristics.

Technical Skills

FORTRAN, C, C++, MATLAB, MINITAB, Microsoft Excel 2013, SQL, Image Processing using MATLAB, Deep Learning and Machine Learning, Python Programming with Python Data Science libraries (numpy, pandas, and scikit-learn), Natural Language Processing (NLP), Working Experience on Java, Excellent communication and writing skills.

Security Clearance

Currently, I do not have security clearance and am able to obtain one.

The following are previously held secret clearances:

1.Sensor Data Integration, Littleton, MA from 2006 – Present (Security Clearance Application submitted to DHS and Secret Clearance is under consideration.

2.Sensor Data Integration, Inc., Concord, MA from 1988 – 1990 (approximate date)

3.Geo-Centers, Inc., Newton, MA from 1989 – 1992

4.Sperry Corporation, Waltham, MA from 1984 – 1987

5.Dynamics Research Corporation, Wilmington, MA from 1980-1984

6.Charles Stark Draper Laboratory, Inc., Cambridge, MA 1976 – 1980

Education

1.University of Florida, Gainesville, Florida, Ph.D. in Electrical Engineering (Major: Control Systems, Minor: Mathematics)

2.University of Florida, Gainesville, Florida, Master in Engineering in Electrical Engineering (M.E.E.E) (Major Control Systems and Minor: Mathematics)

3.University of Evansville, Evansville, Indiana, Bachelor of Arts (B. A) in Biology and Chemistry

4.University of Calcutta, Calcutta, India, Bachelor of Engineering in Electrical Engineering (B.E.E.E) with minor: Mathematics

Professional Experience

Sensor Data Integration, Alexandria, VA and Littleton, MA 9/2006 – Present

Senior Scientist

Developed software systems involving simulation, modeling, image processing, and statistical data processing for target classification using MATLAB, C++, and Python programs. Many research papers have been presented at conferences and published in the conference proceedings.

Worked on a project entitled Automatic Target Recognition of Personnel and Vehicles from an Unmanned Aerial System (UAS) using Image Processing Algorithms, Machine Learning Algorithms for target identification and classification. (Reference: Paper Presented at IEEE National Aerospace and Electronic Conference, Dayton, OH, July 23-26, 2018)

Managed and worked on a NLP ML application project to develop AI application for Emergency Management (EM) such as prevention, response and recovery from human-initiated emergency incidents using NLP technology, big data analytics along with Appache Hadoop/Appache Flink Stream processing technology. . (Reference: Paper Presented at IEEE National Aerospace and Electronic Conference, Dayton, OH, July 15-18, 2019)

Managing and Working on Deep Learning Architecture for a Wide Variety of Sensors for Autonomous Driving Research. The goal of this research topic is to overcome current limitation by expanding the research of deep learning to additional sensors, such as LIDAR and radar that have been less studied, but are crucial for autonomous vehicles in degraded visual environment. Additionally, this research has investigated multiple sensory inputs fused with a deep learning architecture to improve the robustness of the system. It is anticipated that harnessing a wide variety of sensors altogether will benefit the autonomous vehicles by providing a more general and robust self-driving system, especially for navigating in different types of challenging weather, environments, road conditions and traffic.

Reference: Chaudhuri, S., “Neural Networks for Automatic Target Recognition from an unmanned Aerial System,” IEEE National Aerospace and Electronics Conference, Dayton, OH, July 23 – 26, 2018.

Chaudhuri, S., “Future Emergency Management through Artificial Intelligence,” IEEE National Aerospace and Electronics Conference, Dayton, Ohio, July 15-18, 2019.

University of Virginia, Charlottesville, VA 08/09 – Present

Adjunct Faculty

Developed and taught a course entitled Business Analytics for Decision Making.

Northern Virginia Community College, Annandale Campus, Virginia 01/10 – Present

Adjunct Faculty

Taught Pre-Calculus, Calculus and Statistics courses for 53 semesters.

University of Maryland University College, College Park, Maryland 06/99 – 08/06

Collegiate Associate Professor

Developed curricula and taught MIS, Information Security Systems, Computer Forensics in Information Technology courses at the Graduate School of Management and Technology (online graduate courses); and Supervised Doctoral Dissertation Project in the areas of business management

California National University, Torrance, California 09/94 – 01/2018

Adjunct Faculty

Developed and taught online undergraduate and graduate courses in electrical, computer and environmental engineering. Supervised Master’s thesis, capstones project reports.

Sensor Data Integration, Inc., Concord, MA 1987 – 1994

Senior Scientist

Managed and completed several software projects involving electro-optical sensors, electromagnetic sensors, acoustic sensors for multitarget tracking and classification, expert systems, fuzzy neural networks for the U.S, Air Force and U. S. Navy.

References:

Chaudhuri, S., “Artificial Intelligence Applications to Command, Control, and Communications Systems/Subsystems,” Final Technical Report, U. S. Air Force Contract No. F19628-87-C-0183.

Chaudhuri, S., “Data Fusin,” Final Technical report, U. S., Navy Contract No. N66001-89-C-7084, March 1990.

Northeastern University, Boston, MA 09-78 – 12/94

Adjunct Faculty

Supervised Master’s thesis and taught graduate and undergraduate courses in the areas of electrical engineering.

University of Massachusetts, Lowell, MA 09/82 – 08/06

Adjunct Faculty

Taught electrical engineering graduate and undergraduate courses and supervised Master’s Thesis projects.

Harvard University, Cambridge, MA 09/93 – 06/95

Adjunct Faculty

Taught and supervised research projects in the following area:

Artificial Neural Networks

Geo-Centers, Inc., Newton, MA 5/89 – 10/92

Senior Scientist

Worked as a project leader for the following projects for the U. S. Army:

Developed mine detector image/discriminator using multisensor data fusion

Worked on wide area mine detection projects

Sperry Corporation, Waltham, MA 4/84 – 12/87

Principal Member of Engineering Staff

Worked as a project leader for the following projects for the U. S. Air Force and Navy:

Managed 2 R&D engineers for Multisensor data fusion program development

Dynamics Research Corporation, Wilmington, MA 8/80 – 3/84

Senior Systems Analysis Engineer

Worked as a Project Leader for the following projects for the U. S. Air Force and Navy:

Development of Multitarget Multisensor data correlation and fusion algorithm alternatives

Data fusion-based target identification and classification projects

Charles Stark Draper Laboratory, Inc., Cambridge, MA 6/76 – 8/80

Member of Technical Staff

Worked on the following projects for the U. S. Air Force and Navy:

Adaptive estimator for inertial navigation system

Guidance, navigation and control systems design for missile systems

Publications (A list publication will be forwarded on request)

Many technical publications in the areas of Data Processing, Decision Making, Target Tracking and Target Classification using Model Development with Modern Statistical Methods, Data Mining and Machine Learning Algorithms; Regression, Decision Tree, and Time Series Analysis techniques; Natural Language Processing (NLP), Integrated Text Analytics; and Model Assessment and Scoring for Decision Making.

Worked on a project to develop AI application for Emergency Management (EM) functions such as prevention, response and recovery from human-initiated emergency incidents.

Contact this candidate