IEEE Boston Section

Upcoming Events!

May
13
Thu
Electronic Reliability Tutorial Spring Series @ Webinar
May 13 @ 11:00 am – 1:00 pm
May
14
Fri
Digital Signal Processing for Wireless Communications (DSP) – Webinar Course @ Webinar
May 14 @ 7:00 pm – 8:00 pm

Registration – click here:

Course Start Date:  May 14, 2021, videos released weekly 2×1.5 hours

Workshops:  Thursdays:  May 20, 27, June 3, 10,17, 2021

Each workshop is scheduled from 7:00PM – 8:00PM

Speaker:  Dan Boschen

IEEE Member Fee:  $190.00

Non-Member Fee:  $210.00

Decision to run/cancel course:  Tuesday, May 11, 2021

COURSE DESCRIPTION

New Format Combining Live Workshops with Pre-recorded Video

This is a hands-on course providing pre-recorded lectures that students can watch on their own schedule and an unlimited number of times prior to live Q&A/Workshop sessions with the instructor. Ten 1.5 hour videos released 2 per week while the course is in session will be available for up to two months after the conclusion of the course.

Course Summary

This course is a fresh view of the fundamental and practical concepts of digital signal processing applicable to the design of mixed signal design with A/D conversion, digital filters, operations with the FFT, and multi-rate signal processing.  This course will build an intuitive understanding of the underlying mathematics through the use of graphics, visual demonstrations, and applications in GPS and mixed signal (analog/digital) modern transceivers. This course is applicable to DSP algorithm development with a focus on meeting practical hardware development challenges in both the analog and digital domains, and not a tutorial on working with specific DSP processor hardware.

Now with Jupyter Notebooks!

This long-running IEEE Course has been updated to include Jupyter Notebooks which incorporates graphics together with Python simulation code to provide a “take-it-with-you” interactive user experience. No knowledge of Python is required but the notebooks will provide a basic framework for proceeding with further signal processing development using that tools for those that have interest in doing so.

This course will not be teaching Python, but using it for demonstration. A more detailed course on Python itself is covered in a separate IEEE Course “Python Applications for Digital Design and Signal Processing”.

Students will be encouraged but not required to load all the Python tools needed, and all set-up information for installation will be provided prior to the start of class.

Target Audience:

All engineers involved in or interested in signal processing applications. Engineers with significant experience with DSP will also appreciate this opportunity for an in-depth review of the fundamental DSP concepts from a different perspective than that given in a traditional introductory DSP course.

Benefits of Attending/ Goals of Course:

Attendees will build a stronger intuitive understanding of the fundamental signal processing concepts involved with digital filtering and mixed signal analog and digital design. With this, attendees will be able to implement more creative and efficient signal processing architectures in both the analog and digital domains. The knowledge gained from this course will have immediate practical value for any work in the signal processing field.

Topics / Schedule:

Class 1: Correlation, Fourier Transform, Laplace Transform

Class 2: Sampling and A/D Conversion, Z –transform, D/A Conversion

Class 3: IIR and FIR Digital filters, Direct Fourier Transform

Class 4: Windowing, Digital Filter Design, Fixed Point vs Floating Point

Class 5: Fast Fourier Transform, Multi-rate Signal Processing, Multi-rate Filters

Speaker’s Bio:

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems. Dan is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions.

For more background information, please view Dan’s Linked-In page at: http://www.linkedin.com/in/danboschen

May
20
Thu
Electronic Reliability Tutorial Spring Series @ Webinar
May 20 @ 11:00 am – 1:00 pm
Digital Signal Processing for Wireless Communications (DSP) – Webinar Course @ Webinar
May 20 @ 7:00 pm – 8:00 pm

Registration – click here:

Course Start Date:  May 14, 2021, videos released weekly 2×1.5 hours

Workshops:  Thursdays:  May 20, 27, June 3, 10,17, 2021

Each workshop is scheduled from 7:00PM – 8:00PM

Speaker:  Dan Boschen

IEEE Member Fee:  $190.00

Non-Member Fee:  $210.00

Decision to run/cancel course:  Tuesday, May 11, 2021

COURSE DESCRIPTION

New Format Combining Live Workshops with Pre-recorded Video

This is a hands-on course providing pre-recorded lectures that students can watch on their own schedule and an unlimited number of times prior to live Q&A/Workshop sessions with the instructor. Ten 1.5 hour videos released 2 per week while the course is in session will be available for up to two months after the conclusion of the course.

Course Summary

This course is a fresh view of the fundamental and practical concepts of digital signal processing applicable to the design of mixed signal design with A/D conversion, digital filters, operations with the FFT, and multi-rate signal processing.  This course will build an intuitive understanding of the underlying mathematics through the use of graphics, visual demonstrations, and applications in GPS and mixed signal (analog/digital) modern transceivers. This course is applicable to DSP algorithm development with a focus on meeting practical hardware development challenges in both the analog and digital domains, and not a tutorial on working with specific DSP processor hardware.

Now with Jupyter Notebooks!

This long-running IEEE Course has been updated to include Jupyter Notebooks which incorporates graphics together with Python simulation code to provide a “take-it-with-you” interactive user experience. No knowledge of Python is required but the notebooks will provide a basic framework for proceeding with further signal processing development using that tools for those that have interest in doing so.

This course will not be teaching Python, but using it for demonstration. A more detailed course on Python itself is covered in a separate IEEE Course “Python Applications for Digital Design and Signal Processing”.

Students will be encouraged but not required to load all the Python tools needed, and all set-up information for installation will be provided prior to the start of class.

Target Audience:

All engineers involved in or interested in signal processing applications. Engineers with significant experience with DSP will also appreciate this opportunity for an in-depth review of the fundamental DSP concepts from a different perspective than that given in a traditional introductory DSP course.

Benefits of Attending/ Goals of Course:

Attendees will build a stronger intuitive understanding of the fundamental signal processing concepts involved with digital filtering and mixed signal analog and digital design. With this, attendees will be able to implement more creative and efficient signal processing architectures in both the analog and digital domains. The knowledge gained from this course will have immediate practical value for any work in the signal processing field.

Topics / Schedule:

Class 1: Correlation, Fourier Transform, Laplace Transform

Class 2: Sampling and A/D Conversion, Z –transform, D/A Conversion

Class 3: IIR and FIR Digital filters, Direct Fourier Transform

Class 4: Windowing, Digital Filter Design, Fixed Point vs Floating Point

Class 5: Fast Fourier Transform, Multi-rate Signal Processing, Multi-rate Filters

Speaker’s Bio:

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems. Dan is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions.

For more background information, please view Dan’s Linked-In page at: http://www.linkedin.com/in/danboschen

May
25
Tue
Electronic Reliability Tutorial Spring Series @ Webinar
May 25 @ 11:00 am – 1:00 pm
May
27
Thu
Digital Signal Processing for Wireless Communications (DSP) – Webinar Course @ Webinar
May 27 @ 7:00 pm – 8:00 pm

Registration – click here:

Course Start Date:  May 14, 2021, videos released weekly 2×1.5 hours

Workshops:  Thursdays:  May 20, 27, June 3, 10,17, 2021

Each workshop is scheduled from 7:00PM – 8:00PM

Speaker:  Dan Boschen

IEEE Member Fee:  $190.00

Non-Member Fee:  $210.00

Decision to run/cancel course:  Tuesday, May 11, 2021

COURSE DESCRIPTION

New Format Combining Live Workshops with Pre-recorded Video

This is a hands-on course providing pre-recorded lectures that students can watch on their own schedule and an unlimited number of times prior to live Q&A/Workshop sessions with the instructor. Ten 1.5 hour videos released 2 per week while the course is in session will be available for up to two months after the conclusion of the course.

Course Summary

This course is a fresh view of the fundamental and practical concepts of digital signal processing applicable to the design of mixed signal design with A/D conversion, digital filters, operations with the FFT, and multi-rate signal processing.  This course will build an intuitive understanding of the underlying mathematics through the use of graphics, visual demonstrations, and applications in GPS and mixed signal (analog/digital) modern transceivers. This course is applicable to DSP algorithm development with a focus on meeting practical hardware development challenges in both the analog and digital domains, and not a tutorial on working with specific DSP processor hardware.

Now with Jupyter Notebooks!

This long-running IEEE Course has been updated to include Jupyter Notebooks which incorporates graphics together with Python simulation code to provide a “take-it-with-you” interactive user experience. No knowledge of Python is required but the notebooks will provide a basic framework for proceeding with further signal processing development using that tools for those that have interest in doing so.

This course will not be teaching Python, but using it for demonstration. A more detailed course on Python itself is covered in a separate IEEE Course “Python Applications for Digital Design and Signal Processing”.

Students will be encouraged but not required to load all the Python tools needed, and all set-up information for installation will be provided prior to the start of class.

Target Audience:

All engineers involved in or interested in signal processing applications. Engineers with significant experience with DSP will also appreciate this opportunity for an in-depth review of the fundamental DSP concepts from a different perspective than that given in a traditional introductory DSP course.

Benefits of Attending/ Goals of Course:

Attendees will build a stronger intuitive understanding of the fundamental signal processing concepts involved with digital filtering and mixed signal analog and digital design. With this, attendees will be able to implement more creative and efficient signal processing architectures in both the analog and digital domains. The knowledge gained from this course will have immediate practical value for any work in the signal processing field.

Topics / Schedule:

Class 1: Correlation, Fourier Transform, Laplace Transform

Class 2: Sampling and A/D Conversion, Z –transform, D/A Conversion

Class 3: IIR and FIR Digital filters, Direct Fourier Transform

Class 4: Windowing, Digital Filter Design, Fixed Point vs Floating Point

Class 5: Fast Fourier Transform, Multi-rate Signal Processing, Multi-rate Filters

Speaker’s Bio:

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems. Dan is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions.

For more background information, please view Dan’s Linked-In page at: http://www.linkedin.com/in/danboschen

Jun
3
Thu
Digital Signal Processing for Wireless Communications (DSP) – Webinar Course @ Webinar
Jun 3 @ 7:00 pm – 8:00 pm

Registration – click here:

Course Start Date:  May 14, 2021, videos released weekly 2×1.5 hours

Workshops:  Thursdays:  May 20, 27, June 3, 10,17, 2021

Each workshop is scheduled from 7:00PM – 8:00PM

Speaker:  Dan Boschen

IEEE Member Fee:  $190.00

Non-Member Fee:  $210.00

Decision to run/cancel course:  Tuesday, May 11, 2021

COURSE DESCRIPTION

New Format Combining Live Workshops with Pre-recorded Video

This is a hands-on course providing pre-recorded lectures that students can watch on their own schedule and an unlimited number of times prior to live Q&A/Workshop sessions with the instructor. Ten 1.5 hour videos released 2 per week while the course is in session will be available for up to two months after the conclusion of the course.

Course Summary

This course is a fresh view of the fundamental and practical concepts of digital signal processing applicable to the design of mixed signal design with A/D conversion, digital filters, operations with the FFT, and multi-rate signal processing.  This course will build an intuitive understanding of the underlying mathematics through the use of graphics, visual demonstrations, and applications in GPS and mixed signal (analog/digital) modern transceivers. This course is applicable to DSP algorithm development with a focus on meeting practical hardware development challenges in both the analog and digital domains, and not a tutorial on working with specific DSP processor hardware.

Now with Jupyter Notebooks!

This long-running IEEE Course has been updated to include Jupyter Notebooks which incorporates graphics together with Python simulation code to provide a “take-it-with-you” interactive user experience. No knowledge of Python is required but the notebooks will provide a basic framework for proceeding with further signal processing development using that tools for those that have interest in doing so.

This course will not be teaching Python, but using it for demonstration. A more detailed course on Python itself is covered in a separate IEEE Course “Python Applications for Digital Design and Signal Processing”.

Students will be encouraged but not required to load all the Python tools needed, and all set-up information for installation will be provided prior to the start of class.

Target Audience:

All engineers involved in or interested in signal processing applications. Engineers with significant experience with DSP will also appreciate this opportunity for an in-depth review of the fundamental DSP concepts from a different perspective than that given in a traditional introductory DSP course.

Benefits of Attending/ Goals of Course:

Attendees will build a stronger intuitive understanding of the fundamental signal processing concepts involved with digital filtering and mixed signal analog and digital design. With this, attendees will be able to implement more creative and efficient signal processing architectures in both the analog and digital domains. The knowledge gained from this course will have immediate practical value for any work in the signal processing field.

Topics / Schedule:

Class 1: Correlation, Fourier Transform, Laplace Transform

Class 2: Sampling and A/D Conversion, Z –transform, D/A Conversion

Class 3: IIR and FIR Digital filters, Direct Fourier Transform

Class 4: Windowing, Digital Filter Design, Fixed Point vs Floating Point

Class 5: Fast Fourier Transform, Multi-rate Signal Processing, Multi-rate Filters

Speaker’s Bio:

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems. Dan is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions.

For more background information, please view Dan’s Linked-In page at: http://www.linkedin.com/in/danboschen

Jun
10
Thu
Digital Signal Processing for Wireless Communications (DSP) – Webinar Course @ Webinar
Jun 10 @ 7:00 pm – 8:00 pm

Registration – click here:

Course Start Date:  May 14, 2021, videos released weekly 2×1.5 hours

Workshops:  Thursdays:  May 20, 27, June 3, 10,17, 2021

Each workshop is scheduled from 7:00PM – 8:00PM

Speaker:  Dan Boschen

IEEE Member Fee:  $190.00

Non-Member Fee:  $210.00

Decision to run/cancel course:  Tuesday, May 11, 2021

COURSE DESCRIPTION

New Format Combining Live Workshops with Pre-recorded Video

This is a hands-on course providing pre-recorded lectures that students can watch on their own schedule and an unlimited number of times prior to live Q&A/Workshop sessions with the instructor. Ten 1.5 hour videos released 2 per week while the course is in session will be available for up to two months after the conclusion of the course.

Course Summary

This course is a fresh view of the fundamental and practical concepts of digital signal processing applicable to the design of mixed signal design with A/D conversion, digital filters, operations with the FFT, and multi-rate signal processing.  This course will build an intuitive understanding of the underlying mathematics through the use of graphics, visual demonstrations, and applications in GPS and mixed signal (analog/digital) modern transceivers. This course is applicable to DSP algorithm development with a focus on meeting practical hardware development challenges in both the analog and digital domains, and not a tutorial on working with specific DSP processor hardware.

Now with Jupyter Notebooks!

This long-running IEEE Course has been updated to include Jupyter Notebooks which incorporates graphics together with Python simulation code to provide a “take-it-with-you” interactive user experience. No knowledge of Python is required but the notebooks will provide a basic framework for proceeding with further signal processing development using that tools for those that have interest in doing so.

This course will not be teaching Python, but using it for demonstration. A more detailed course on Python itself is covered in a separate IEEE Course “Python Applications for Digital Design and Signal Processing”.

Students will be encouraged but not required to load all the Python tools needed, and all set-up information for installation will be provided prior to the start of class.

Target Audience:

All engineers involved in or interested in signal processing applications. Engineers with significant experience with DSP will also appreciate this opportunity for an in-depth review of the fundamental DSP concepts from a different perspective than that given in a traditional introductory DSP course.

Benefits of Attending/ Goals of Course:

Attendees will build a stronger intuitive understanding of the fundamental signal processing concepts involved with digital filtering and mixed signal analog and digital design. With this, attendees will be able to implement more creative and efficient signal processing architectures in both the analog and digital domains. The knowledge gained from this course will have immediate practical value for any work in the signal processing field.

Topics / Schedule:

Class 1: Correlation, Fourier Transform, Laplace Transform

Class 2: Sampling and A/D Conversion, Z –transform, D/A Conversion

Class 3: IIR and FIR Digital filters, Direct Fourier Transform

Class 4: Windowing, Digital Filter Design, Fixed Point vs Floating Point

Class 5: Fast Fourier Transform, Multi-rate Signal Processing, Multi-rate Filters

Speaker’s Bio:

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems. Dan is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions.

For more background information, please view Dan’s Linked-In page at: http://www.linkedin.com/in/danboschen

Jun
15
Tue
Forward Error-Correcting Codes with MATLAB Applications and Their Use for Communication Systems @ Live Webinar
Jun 15 @ 10:00 pm – 11:30 pm

Speaker:   Orhan Gazi, Cankaya University, Ankara-Turkey

Course Format: Live Webinar, 8 sessions, 1.5 hours per session

Times and Dates: 10 AM – 11:30 AM ET, June 15, 17, 22, 25, 29, July 1, 13, 15

Decision (Run/Cancel) Date for this course is:  Thursday, June 10, 2021

Registration Fees:

IEEE Member:  $250.00

Non-Member:  $300.00

 

 

Introduction:  Communication systems employ channel codes for the correction of errors occurring during transmission. Channel codes are used in almost every data communication and storage devices. For instance, channel codes are used in mobile phones, network elements, satellites, flash memories, RAMs etc.  Any engineer working in the communication industry should have an idea about the error correcting codes. In this course, an introductory information will be provided about forward error correcting codes. The one who takes this course will get an idea about the construction of channel codes, how error correction is achieved, and some of simple preliminary channel codes used for error correction. We will also provide some applications of channel codes using MATLAB environment. We will teach how to perform computer simulations to measure the performance of communication systems and see the effect of channel codes on the performance of communication systems.

Prerequisite: The one who is interested in taking this course should have basic knowledge of linear algebra.

  • Introduction to Forward Error Correction and Channel Codes
  • Review of Linear Algebra, Groups, Fields, and Vector Spaces
  • Linear Block Codes, Generator and Parity Check Matrices, Encoding Operation
  • Syndrome Decoding and Some Important Linear Codes
  • Forward Error Correction Using MATLAB
  • Cyclic Codes, Encoding and Decoding of Cyclic Codes
  • Galois Fields, Algebraic Code Construction
  • Galois Fields Using MATLAB
  • BCH Codes, Encoding and Decoding of BCH Codes
  • BCH Encoding and Decoding Using MATLAB
  • Reed Solomon Codes, Encoding and Decoding of Reed Solomon Codes
  • Convolutional Codes, Viterbi Decoding Algorithm
  • Convolutional Encoding and Decoding Using MATLAB

Target Audience:  Electronic and Communication Engineers, electronic engineers, computer engineers, engineers working in communication industry

Benefits of Attending Course: 

1) The participant will have an idea about forward error correction.

2) The participant will have an idea about the construction of channel codes.

3) The participant will learn how to make computer simulation using channel codes.

4) The participant will learn how to encode information bits using channel codes and how to decode them using decoding methods.

Speaker Bio:  Prof. Orhan Gazi is the author of the book “Forward Error Correction via Channel Coding” https://www.springer.com/gp/book/9783030333799. Prof. Orhan Gazi is the sole author of 10 books written in electrical engineering subjects.

He is also the author of the book “Polar Codes.  A Non-Trivial Approach to Channel Coding” which can be reached from https://www.springer.com/gp/book/9789811307362

The book is selected by IEEE COMSOC as one of the best readings in polar codes, https://www.comsoc.org/publications/best-readings/polar-coding

He is also the single author of the book “Information Theory for Electrical Engineers” https://www.springer.com/gp/book/9789811084317.

The research area of Prof. Orhan Gazi involves “channel coding”, and “digital communication subjects”.  Recently, he focuses on over capacity data transmission using polar codes. He is also interested in practical applications of communication systems involving FPGA devices. He is delivering courses with titles “VHDL circuit design”, “interface design using VHDL for FPGA devices” and “system on chip design”.

Materials to be included:  Lecture slides will be provided.

Registration Fees:

IEEE Member:   $250.00

Non-Member:  $300.00

Jun
17
Thu
Digital Signal Processing for Wireless Communications (DSP) – Webinar Course @ Webinar
Jun 17 @ 7:00 pm – 8:00 pm

Registration – click here:

Course Start Date:  May 14, 2021, videos released weekly 2×1.5 hours

Workshops:  Thursdays:  May 20, 27, June 3, 10,17, 2021

Each workshop is scheduled from 7:00PM – 8:00PM

Speaker:  Dan Boschen

IEEE Member Fee:  $190.00

Non-Member Fee:  $210.00

Decision to run/cancel course:  Tuesday, May 11, 2021

COURSE DESCRIPTION

New Format Combining Live Workshops with Pre-recorded Video

This is a hands-on course providing pre-recorded lectures that students can watch on their own schedule and an unlimited number of times prior to live Q&A/Workshop sessions with the instructor. Ten 1.5 hour videos released 2 per week while the course is in session will be available for up to two months after the conclusion of the course.

Course Summary

This course is a fresh view of the fundamental and practical concepts of digital signal processing applicable to the design of mixed signal design with A/D conversion, digital filters, operations with the FFT, and multi-rate signal processing.  This course will build an intuitive understanding of the underlying mathematics through the use of graphics, visual demonstrations, and applications in GPS and mixed signal (analog/digital) modern transceivers. This course is applicable to DSP algorithm development with a focus on meeting practical hardware development challenges in both the analog and digital domains, and not a tutorial on working with specific DSP processor hardware.

Now with Jupyter Notebooks!

This long-running IEEE Course has been updated to include Jupyter Notebooks which incorporates graphics together with Python simulation code to provide a “take-it-with-you” interactive user experience. No knowledge of Python is required but the notebooks will provide a basic framework for proceeding with further signal processing development using that tools for those that have interest in doing so.

This course will not be teaching Python, but using it for demonstration. A more detailed course on Python itself is covered in a separate IEEE Course “Python Applications for Digital Design and Signal Processing”.

Students will be encouraged but not required to load all the Python tools needed, and all set-up information for installation will be provided prior to the start of class.

Target Audience:

All engineers involved in or interested in signal processing applications. Engineers with significant experience with DSP will also appreciate this opportunity for an in-depth review of the fundamental DSP concepts from a different perspective than that given in a traditional introductory DSP course.

Benefits of Attending/ Goals of Course:

Attendees will build a stronger intuitive understanding of the fundamental signal processing concepts involved with digital filtering and mixed signal analog and digital design. With this, attendees will be able to implement more creative and efficient signal processing architectures in both the analog and digital domains. The knowledge gained from this course will have immediate practical value for any work in the signal processing field.

Topics / Schedule:

Class 1: Correlation, Fourier Transform, Laplace Transform

Class 2: Sampling and A/D Conversion, Z –transform, D/A Conversion

Class 3: IIR and FIR Digital filters, Direct Fourier Transform

Class 4: Windowing, Digital Filter Design, Fixed Point vs Floating Point

Class 5: Fast Fourier Transform, Multi-rate Signal Processing, Multi-rate Filters

Speaker’s Bio:

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems. Dan is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions.

For more background information, please view Dan’s Linked-In page at: http://www.linkedin.com/in/danboschen

SPECIAL NOTICE – CORONAVIRUS (COVID-19)

IEEE Boston Section recognized for Excellence in Membership Recruitment Performance

 

IEEE HKN Ceremony

2021 Elected Officers

IEEE Boston Section was founded Feb 13, 1903, and serves more than 8,500 members of the IEEE. There are 29 chapters and affinity groups covering topics of interest from Aerospace & Electronic Systems, to Entrepreneur Network to Women in Engineering to Young Professionals. The chapters and affinity groups organize more than 100 meetings a year. In addition to the IEEE organization activities, the Boston Section organizes and sponsors up to seven conferences in any given year, as well as more than 45 short courses. The Boston Section publishes a bi-weekly newsletter and, currently, a monthly Digital Reflector newspaper included in IEEE membership.

The IEEE Boston Section also offers social programs such as the section annual meeting, Milestone events, and other non-technical professional activities to round out the local events. The Section also hosts one of the largest and longest running entrepreneurial support groups in IEEE.

More than 150 volunteers help create and coordinate events throughout the year.