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DC 37 Education Fund Classes

Professional Development Hours Workshop for Engineers and Registered Architects

Scheduled seminars throughout the DC 37 Education Fund provide licensed Professional Engineers and Registered Architects the opportunity to earn Professional Development Hours for license renewal. Engineers are required to have a minimum of 36 development hours as part of the renewal process; 18 of which must be in an interactive classroom setting. These seminars are open to licensed engineers and architects only.

Winter 2020 – January/February:

January and February 2020 – Seminars and Instructors’ biographies.

ME-179 Artificial Intelligence and Robotics (Pt 1)
Artificial Intelligence [AI] encompasses several quantitative disciplines that include mathematical decision theory, image analysis, and computer science. Together the synergy of these separate disciplines and mechanical device designs have resulted in the development of computational algorithms and machine components that are capable of performing complex analysis more efficiently and faster than humans. Moreover, these algorithms, like the human brain, include the ability to learn from their analysis results to self-improve themselves with minimal or no programmer intervention. Historically, AI concepts have been investigated initially using mechanical devices in the 19th century by Charles Babbage, and later in the early 20th century using electrical computers such as the one invented by Alan Turing, to help decipher the codes created by the German enigma machine. With the publication of Turing’s seminal paper in 1950 “Computing Machinery and Intelligence” the theoretical concepts of AI was introduced as a discipline for advanced investigations. Our current technology, that includes fast and inexpensive electronic digital microprocessors, memory and sensors, has facilitated and accelerated the development of the digital self-learning algorithms now implemented and that appear in a variety of commercial and health care applications and devices. The specific aims for this continuing ed course for PE practitioners is to provide a useful, practical introduction to AI that will encourage them to explore the use of AI for their specific discipline and work responsibilities. Part 1 of this course will:

Briefly introduce AI history and then describe our current understanding of intelligence and learning in the human brain and then distinguish these in vivo processes within silico machine intelligence and learning.

Contemporary Concepts of Machine Learning that include:
Programming languages used to implement AI
Neural Networks
Multi-layered learning algorithms, i.e. “deep learning”
Big Data
Natural Language processing
Image Processing

The subject matter that will be presented will be taken from peer-reviewed publications and books, and include short videos, whenever possible, to illustrate the concepts.

Subject: ME-179 Artificial Intelligence and Robotics (Pt 1)
Time: 5:30 pm to 9:30 pm
Date: Wednesday, January 29, 2020
Location: New York, N.Y.
Instructor: Dr. Gene DiResta, Ph.D. Bio. Engr., P.E.

ME-180 Artificial Intelligence and Robotics (Pt 2)
Part 2 will present the engineering applications of AI that are used commercially and in the health care arena. The specific applications covered are extensions to the areas of AI presented in Part 1. Part 2 will introduce intelligent mobile robotic technology and distinguish it from the types of programmable fixed automata used in assembly line manufacturing. Use of AI in engineering with special focus on Electrical, Structural and Biomedical [BME] Engineering and Robotics. Specific applications will include:

Commercial use of AI in both mobile robotic technology and computer algorithms in manufacturing; safety evaluations; and military applications.

Structural Engineering examples will include mobile automata used for safety inspections in dangerous environments, e.g. nuclear power plants, underwater, etc.

Integration of sensor data to assess structural damage to structures following natural calamities, e.g. earthquakes, etc.

Earthquake prediction

Electrical Engineering examples will include the use AI in heavy current energy distribution in grid structures; comparisons between fixed and mobile intelligent robotic automata; expert systems, etc.

BME examples will introduce use of AI to analysis of patient images acquired using CT/MRI PET equipment to enhance early detection of disease using Deep Learning algorithms; Big Data analysis of genomic data for patient specific medical diagnosis, and robotic surgery.

The subject matter will be taken from peer-reviewed publications and books and include short videos, whenever possible, to illustrate the concepts.

Subject: ME-180 Artificial Intelligence and Robotics (Pt 2)
Time: 5:30 pm to 9:30 pm
Date: Wednesday, February 5, 2020
Location: New York, N.Y.
Instructor: Dr. Gene DiResta, Ph.D. Bio. Engr., P.E.

Dr. Gene DiResta, Ph.D. Bio. Engr., P.E.
Gene R. DiResta holds a BS in Biochemistry, an MS in Chemical Engineering and a PhD in Bioengineering with a minor in Mathematics and Electrical Engineering. He worked in industry for 7 years as a biochemical engineer designing reactors using enzyme technology for the production of food and beverages from bench to industrial scale. He is well versed in the theoretical and practical aspects of instrumental methods of analysis, mathematical modeling and control engineering. He received his PE in Chemical Engineering. Leaving Industry he went to work as a Medical Physicist at Memorial Sloan Kettering Cancer Center where he directed the Nuclear Medicine Research Lab and was the Technical Director of the Positron EmissionTomography Facility for 12 years. He transitioned from diagnosis to therapy by becoming the Director of the Orthopaedic Research Lab, serving for 12 years before being recruited by NYU to be the Director of their Bioengineering graduate program. Dr. DiResta currently has published over 40 papers in peer-reviewed journals and holds 7 US patents for a variety of devices and processes. He is certified by the American Board of Radiology in Medical Nuclear Physics. His particular outside interest is in the area of the engineering challenges of climate change because it leverages his expertise in chemical engineering, nuclear physics, mathematics and chemico-biologic principles. Climate change is a bioengineering problem because it affects the earth’s biosphere, i.e. its animal and plant life. He is ideally equipped to understand the complexity of the biological effects resulting from climatic effects and develop lectures to explain the phenomena to practicing professional engineers.


ME 114 Analysis of Engineering Disasters, Pt # 1
This course examines how engineering, design and management processes conspire to cause catastrophic failure and the most effective methods to avoid such events. Presented as a series of case studies, the course covers causes of failure such as poor engineering practice, design flaws, material failures, extreme operating conditions, inadequate management processes and defective construction and fabrication. Specific events covered in this segment are the Titanic, Challenger, Tacoma Narrows Bridge, Thresher submarine and Mars Climate Orbiter events.

Subject: ME 114 Analysis of Engineering Disasters, Pt # 1
Time: 5:30 pm to 9:30 pm
Date: Wednesday, February 12, 2020
Location: New York, N.Y.
Instructor: Neil Weisenfeld, M.S.E.E., P.E.

ME-115 Analysis of Engineering Disasters, (Part # 2)
Part II of this course continues the examination of how engineering, design and management processes conspire to cause catastrophic failure and the most effective methods to avoid such events. Presented as a series of case studies, the course covers causes of failure such as poor engineering practice, design flaws, material failures, extreme operating conditions, inadequate management processes and defective construction and fabrication. Specific events covered in this segment are the World Trade Center, Three Mile Island, Columbia Space Shuttle, Kansas City Hyatt Walkway and Flight 800 events. In addition, forensic investigative techniques and the legal and professional implications of such disasters will be covered.

Subject: ME-115 Analysis of Engineering Disasters, (Part # 2)
Time: 5:30 pm to 9:30 pm
Date: Wednesday, February 26, 2020
Location: New York, N.Y.
Instructor: Neil Weisenfeld, M.S.E.E., P.E.

Neil Weisenfeld, M.S.E.E., P.E.
Neil Weisenfeld is a professional engineer with a bachelor’s degree in Electrical Engineering. He has 23 years of experience in the power industry and is currently a department manager in Con Edison’s Distribution Engineering department. He has worked in the areas of Power Generation, System Operation, Engineering and Energy Services. He has served on the Executive Committee of the Power Engineering Society of IEEE for over 10 years, is a senior member of the IEEE and holds four U.S. patents.

After you apply you will receive a copy of your application. Once eligibility has been checked, you will receive an email that will require you to confirm.
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