AI Webinar Series

Artificial Intelligence (AI) What's in it for me?

Artificial Intelligence has found its way into many areas of our lives and promises to be central in the future of engineering and technology. Research and development efforts proliferate and there is a real need to acquire knowledge by those practicing in the field and by those who desire to do so. IEEE Boston’s main effort has been to provide engineers and scientists with the tools needed in their careers and AI is no exception.

IEEE Boston’s interest includes organizing, managing and producing a series of one day AI virtual events. In doing so, IEEE Boston is providing a pulpit to experts in the AI field to present their expertise and knowledge to other technologists, engineers and scientists. The goal of these one day events is to provide cost effective dissemination of AI knowledge to engineers, decision makers and concerned individuals worldwide. The format of these events are one day virtual seminars lasting approximately one hour. Access to streaming of these event during and after the seminar will be available.

Confirmed Speakers Include:

Vinton G. Cerf, Vice President & Chief Internet Evangelist of Google

Alton D. Romig, Jr., Executive Officer of the National Academy of Engineering

David Cox, IBM Director of the MIT-IBM Watson AI Lab

Manuela M. Veloso, Head of J.P. Morgan AI Research

Steve Wozniack, Co-founder, Apple Computer

Helen Greiner, Co-Founder iRobot

Session 4: April 20, 2021
12:00 - 1:30pm (EDT)

  • Price: IEEE Members: $25.; Non-members: $35.
  • When: April 20, 2021 12:00pm – 1:30pm (EDT)
  • Duration: 1.5 hours
  • Instructor:  David Cox, IBM

Current full time undergraduate and graduate students will be complimentary. However, each student must provide a valid current student ID and documentation showing enrolled as full time. Documentation and Student ID can be emailed to


Abstract: Artificial intelligence and machine learning have experienced a renaissance in the past decade, thanks largely to the success of deep learning methods. However, while deep learning has proven itself to be extremely powerful, most of today’s most successful deep learning systems suffer from a number of important limitations, ranging from the requirement for enormous training data sets to lack of interpretability to vulnerability to “hacking” via adversarial examples. In my talk, I will survey some of these limitations and propose that one path forward involves building hybrid systems that combine neural networks with techniques and ideas from symbolic AI, a parallel tradition of AI whose origins date back to the beginning of AI. I will show example neurosymbolic hybrid systems where neural networks and symbolic systems complement each other’s strengths and weaknesses, enabling systems that are accurate, sample efficient, and interpretable. Finally, I will discuss applications of neurosymbolic hybrid systems, including technologies targeting the Mayflower autonomous ship, which combines an array of neural and symbolic components to undertake the challenging task of autonomously piloting across the Atlantic Ocean.


Instructor:  David Cox

David Cox is the IBM Director of the MIT-IBM Watson AI Lab, a first of its kind industry-academic collaboration between IBM and MIT, focused on fundamental research in artificial intelligence. The Lab was founded with a $240m, 10 year commitment from IBM and brings together researchers at IBM with faculty at MIT to tackle hard problems at the vanguard of AI.
Prior to joining IBM, David was the John L. Loeb Associate Professor of the Natural Sciences and of Engineering and Applied Sciences at Harvard University, where he held appointments in Computer Science, the Department of Molecular and Cellular Biology and the Center for Brain Science. David’s ongoing research is primarily focused on bringing insights from neuroscience into AI research. His past work has spanned a variety of disciplines, from neuroscience experiments in living brains, to the development of machine learning and artificial intelligence methods, to applied machine learning and high performance computing methods.
David has been a speaker and agenda contributor at the World Economic Forum, and he was a Faculty Associate at the Berkman-Klein Center for Internet and Society at Harvard Law School. He has received a variety of honors, including the Richard and Susan Smith Foundation Award for Excellence in Biomedical Research, the Google Faculty Research Award in Computer Science, and the Roslyn Abramson Award for Excellence in Undergraduate Teaching. He taught and led the development of one of Harvard’s first massive open online courses (“The Fundamentals of Neuroscience”;, which has drawn over 750,000 students from around the world. His academic lab has spawned several startups across a range of industries, ranging from AI for healthcare to autonomous vehicles

Session 5: May 2021
More information will be posted shortly

Session 6: June 23, 2021
12:00 - 1:30pm (EDT)

  • Price: IEEE Members: $25.; Non-members: $35.
  • When: June 23, 2020 12:00pm – 1:30pm (EDT)
  • Duration: 1.5 hours
  • Instructors:  Manuela Veloso, JP Morgan

Current full time undergraduate and graduate students will be complimentary. However, each student must provide a valid current student ID and documentation showing enrolled as full time. Documentation and Student ID can be emailed to


Instructors: Manuela Veloso and JP Morgan

Manuela M. Veloso is the Head of J.P. Morgan AI Research, which pursues fundamental research in areas of core relevance to financial services, including data mining and cryptography, machine learning, explainability, and human-AI interaction. J.P. Morgan AI Research partners with applied data analytics teams across the firm as well as with leading academic institutions globally. 

Professor Veloso is on leave from Carnegie Mellon University as the Herbert A. Simon University Professor in the School of Computer Science, and the past Head of the Machine Learning Department. With her students, she had led research in AI, with a focus on robotics and machine learning, having concretely researched and developed a variety of autonomous robots, including teams of soccer robots, and mobile service robots. Her robot soccer teams have been RoboCup world champions several times, and the CoBot mobile robots have autonomously navigated for more than 1,000km in university buildings. 

Professor Veloso is the Past President of AAAI, (the Association for the Advancement of Artificial Intelligence), and the co-founder, Trustee, and Past President of RoboCup. Professor Veloso has been recognized with a multiple honors, including being a Fellow of the ACM, IEEE, AAAS, and AAAI. She is the recipient of several best paper awards, the Einstein Chair of the Chinese Academy of Science, the ACM/SIGART Autonomous Agents Research Award, an NSF Career Award, and the Allen Newell Medal for Excellence in Research. 

Professor Veloso earned a Bachelor and Master of Science degrees in Electrical and Computer Engineering from Instituto Superior Tecnico in Lisbon, Portugal, a Master of Arts in Computer Science from Boston University, and Master of Science and PhD in Computer Science from Carnegie Mellon University. See for her scientific publications.

Session 1: January 21, 2021

12:00 - 1:30pm (EDT)
  • Price: IEEE Members: $25.; Non-members: $35.
  • When: January 21, 2020 12:00pm – 1:30pm (EDT)
  • Duration: 1.5 hours
  • Instructors:  Vinton G. Cerf and A.D. Romig, Jr.

Current full time undergraduate and graduate students will be complimentary. However, each student must provide a valid current student ID and documentation showing enrolled as full time. Documentation and Student ID can be emailed to


Abstract:  We have seen dramatic examples of machine learning in a variety of applications from playing GO at grand master level, self-driving cars, machine translations and speech recognition as well as various kinds of medical diagnosis. These examples illustrate the startling power of neural networks and have sometimes led to warnings: “The Robots are Coming!” In fact, these tools are powerful enablers that extend human capacity well beyond human limits. The machine translations deal with 100+ languages – few if any humans have the capacity to cope with that many. However, we have also discovered that these systems also break in unexpected ways and are brittle. Image recognition can confuse a cat with a firetruck under some conditions, for example. This is partly because the ML system do not “see” the same way we do. Abstraction and generalization are out of reach for the most part. We are still far from Artificial General Intelligence though the computer scientists of the 1960s dreamed of this. The significant challenges ahead are to make progress on modeling, abstraction and problem solving while applying existing technology is constructive ways that do not risk harm.

Instructor: Vincent G. Cerf

Vinton G. Cerf is vice president and Chief Internet Evangelist for Google.  With Robert Kahn, Vint is the co-designer of the architecture of the Internet. In  1997 they received the U.S. National Medal of Technology and in 2005, the  Presidential Medal of Freedom and the ACM Turing Award. In April 2008 they  shared the Japan Prize for their work and in 2013, the Queen Elizabeth Prize for  Engineering. He is a member of the US National Academies of Science and  Engineering and the Legion d’Honneur.
Vint Cerf served as chairman of the board of the Internet Corporation for  Assigned Names and Numbers (ICANN) from 2000-2007 and he has been a  Visiting Scientist at the Jet Propulsion Laboratory since 1998. 
He holds a Ph.D. in Computer Science from UCLA and twenty-nine honorary  degrees. 

Abstract:  The holy grail of aerial drones is to instill in them artificial intelligence that allows them to operate in a fully autonomous mode.

First it’s important to distinguish between full autonomy and heavy automation. Aerial drones may accomplish many tasks, such as the delivery of a package, with heavy automation. Other tasks, such as a military drone’s operation with high survivability in contested or denied airspace, would be extraordinarily difficult even with the heaviest automation. These and other complex tasks require autonomous operation, which depends on artificial intelligence to act appropriately without direct human guidance.

Throughout the history of aviation—at least far back as the Greeks—humans have tried to learn about flying from nature’s aviators, birds. Bird behaviors such as sea skimming and formation flying, and the acoustic characteristics of owls, have provided insights into various aspects of aircraft design and operation.

And of course birds can make decisions, use tools, and communicate. How might these capacities also inform human-designed flight?

This lecture will review our understanding of avian behavior and examine what might be learned from birds to facilitate efforts to develop fully autonomous aerial drones.

Instructor: Alton D. Romig

Alton D. Romig, Jr. is the executive officer of the National Academy of Engineering. Under Congressional charter, the Academy provides advice to the federal government, when requested, on matters of engineering and technology. As executive officer, Dr. Romig is the chief operating officer responsible for the program, financial, and membership operations of the Academy, reporting to the NAE president.

He was previously vice president and general manager of Lockheed Martin Aeronautics Company Advanced Development Programs, better known as the Skunk
Works®. He spent the majority of his career at Sandia National Laboratories, then operated by the Lockheed Martin Corporation, having joined Sandia as a member of the technical staff in 1979. Dr. Romig moved through a succession of R&D management positions leading to his appointment as executive vice president in 2005. He served as deputy laboratories director and chief operating officer until 2010, when he transferred to the Skunk Works.

Dr. Romig serves or has served on a number of Advisory Committees including those at Univ of Washington, MIT, Ohio State, Purdue, Georgia Tech, the Colorado School of Mines and Sandia National Laboratories. He is also visiting Associate of Applied Physics and Materials Science at Cal Tech. Dr. Romig is a member of the Board of Directors of Football Research, Inc., a non-profit entity created and supported by the National Football League to review engineering technology to improve the safety of the sport. From 2003 to 2008, he served on the Board of AWE, Aldermaston, UK and chaired the Program committee.

Dr. Romig is a Fellow TMS, IEEE, AIAA and AAAS. He is also a Fellow and Honorary Member of ASM International. Dr. Romig was elected to the National Academy of Engineering in 2003 and the Council of Foreign Relations in 2008. He was awarded the ASM Silver Medal for Materials Research in 1988. Dr. Romig graduated from Lehigh University in 1975 with a BS in Materials Science and Engineering. He received his MS and PhD in Materials Science and Engineering from Lehigh University in 1977 and 1979, respectively.

Session 3: March 17, 2021

10:30 - 12:00 noon (EDT)
  • Price: IEEE Members: $25.; Non-members: $35.
  • When: March 17, 2021 10:30am – 12:00 noon (EDT)
  • Duration: 1.5 hours
  • Instructor: Dr. Ken Washington, CTO Ford Motor Company



The presentation reviews some of the main directions in AI at Ford. The focus is on the use of data, analytics, and AI as key enablers of the plan for modernizing Ford Motor Company operations. The disruptive role of AI in the digital transformation of Ford in a time of unprecedented change in vehicle technology, mobility and connectivity is discussed. Examples of applications to vehicle engineering, delivery of personalized mobility experiences and business practices are reviewed. The presentation concludes with the lessons learned and future trends in integrating AI technologies within the design of modern vehicles and services.

Speaker Bio:

Dr. Ken Washington is chief technology officer, Ford Motor Company, and part of the enterprise leadership team reporting to Hau Thai-Tang, Ford’s chief product platform and operations officer. In this role, Washington leads Ford’s global research organization, overseeing the development and implementation of the company’s technology strategy. His responsibilities include Ford’s next generation vehicle electrical architectures; sensing and computing stacks; energy, propulsion, and sustainability; advanced materials and manufacturing; and controls and automated systems. He also leads Ford’s STEM and University research programs.

Prior to joining Ford, he was vice president of the Advanced Technology Center at Lockheed Martin Space Systems, and was responsible for leading a team of scientists and engineers in performing research and development in space science and related R&D.

Previously, he served as Lockheed Martin Corporation’s first chief privacy officer, a role in which he built the company’s privacy program, set the privacy strategy direction and established a team of privacy professionals to execute the strategy.

Washington also previously served as the vice president and chief technology officer for the Lockheed Martin IT organization, where he was responsible for shaping the future of the corporation’s information technology enterprise.

Prior to joining Lockheed Martin in February 2007, Washington served as chief information officer for Sandia National Laboratories, where he previously held various other technical leadership and engineering positions.

He has a bachelor’s, master’s and doctorate degree in Nuclear Engineering from Texas A&M University, serves on the board of directors for McKesson Corporation, and is a fellow of the MIT Seminar XXI program on International Relations.Washington was inducted into the National Academy of Engineering in 2020.