Aerospace & Electronic Systems Society Short Course Program
AESS Chapters, IEEE Sections, Industry, Government, and Academia are encouraged to take advantage of the AESS Short Course Program. This program allows for the selection from an outstanding list of lecturers who are experts in their field and have delivered successful courses in the past. The courses cover a growing list of topics relevant to the technical areas of interest to AESS.
The course organization is generally expected to be performed through a local AESS Chapter. In most cases, funds for the course are to be raised via registration fees or training budgets of supporting organizations. The AESS will advance reasonable seed funds to support travel costs of the lecturer. Course revenues are expected to cover lecturer costs, the lecturer honorarium, and venue and related course expenses. The surplus will generally be split 80/20 between the local AESS Chapter and AESS.
The procedure for obtaining a lecturer is as follows. If a Chapter or Section has an interest in inviting one of the lecturers, it should first contact the lecturer directly in order to obtain his or her agreement to give the course on a particular date. Note that the course durations listed below are nominal and can be modified by mutual agreement. After this is accomplished, the Chapter or Section must notify the AESS Short Course Initiative Chair. If financial support (seed funds) from the AESS is required for the lecturer’s expenses, he or she must submit an estimate to the AESS Short Course Initiative Chair before incurring any expenses. This estimate must be provided at least 45 days before the planned meeting to provide time for feedback and for changes if needed. Written authorization from AESS must be received before proceeding.
Short Course Lecturers are ambassadors of the AESS, who serve as an important demonstration of the value of membership in IEEE and AESS in particular. A short presentation on the benefits of Society membership is available and is to be included at the start of each Short Course. Lecturers should contact the AESS Operations Manager well in advance of each course to arrange for shipping AESS and IEEE Membership brochures and copies of society publications to hand out.
Following the course, the speaker and/or host are asked to prepare a short report suitable for publication and posting on the AESS web site. Pictures taken during the course are highly desirable.
The AESS Short Course Committee prepared a Short Course Program Guide, a comprehensive guide to assist in the organization of an AESS Short Course.
The Short Course Initiative was conceived back in May 2015 by then VP Education, Joe Fabrizio. It was presented to the AESS Board of Governors as a new initiative. His thought was that Chapters had no mechanism to raise revenue to benefit members. He was convinced that Chapters could raise funds by empowering members to offer fee-paying AESS short courses. He ran a pilot program in November of 2015 by giving a one-day workshop himself, drawing in many participants and proved his idea as successful, raising around $15,000 for the local chapter. The South Australia Chapter ran a second “pilot” in 2017, bringing AESS Distinguished Lecturer, Lorenzo Lo Monte in to give a multi-day course, with equal success. The idea gained the support of the AESS Board of Governors, and a committee was put together (Lorenzo Lo Monte, Luke Rosenberg, Jason Williams) to create a Short Course Program Guide as a resource for all AESS Chapters.
The activities of many local AESS Chapters are often constrained by insufficient revenue, and they do not have an effective mechanism to improve this. The AESS has an excellent core of mature members willing to contribute to educational activities. By empowering members to offer fee-paying AESS short courses, chapters can raise funds and better engage with the local community. These courses can be offered to industry, Government, and academia that have training budgets for staff professional development.
This Short Course Initiative will require input from both the AESS Industry Relations and Education Committees, who can work with the local chapters to help identify training needs. The Technical Panels Committee and the Education Committee can then help identify course presenters in the AESS Fields of Interest. The Membership Committee and Chapters will organize the course and local arrangements. This initiative has been proven twice with pilot programs run by the AESS South Australia Section Chapter. The success was astounding, and now the process will be shared and developed with the rest of the AESS Chapters.
Short Courses can provide the following benefits:
- Training: Many IEEE members are more interested in tutorials or short courses, rather than a single lecture. This is because IEEE members are typically engineers, students, or researchers who prefer to spend a block of time developing skills as part of a training course. Also, local industry is more willing to pay to send their employees for training/tutorial classes rather than a single lecture.
- Income for Chapters: Chapters that are willing to host a Short Course, provide local support, manage logistics, manage attendees, etc. will be able to raise some revenue for future IEEE activities.
- Serving the society membership: The Short Course Initiative will bring together many areas in the society: Membership, Education, Technical Panels, and Industry.
AESS Short Course Instructors
Click on Course Details for each instructor to learn more about each short course and instructor.
Glue Technologies for Space Systems Technical Panel Chair
Softwarization and Virtualization for Satellite Communications and Services
Duration: 1 day
As softwarization and virtualization are emerging as key components of modern networking architectures, application and extension of those concepts towards satellite communication systems represents a promising field, opening unprecedented opportunities. Indeed, adaptability and on-the-fly reconfigurability will represent the major functionalities enabled by satellite systems softwarization.
The course will aim at addressing the basic concepts and opportunities provided by Software Defined Networking (SDN) and Network Function Virtualization (NFV) in order to integrate them in the design of future satellite communication systems. The course will be divided into three sections. Section I will describe the softwarization and virtualization concepts and enabling technologies. In this section, after briefly describing the current state-of-the-art and directions in satellite communications, the course will focus on analyzing three basic concepts: Software Defined Radios (SDR), Software Defined Networks (SDN) and Network Function Virtualization (NFV). Section II will address the issues related to applying the previous concepts to the satellites architecture, describing several potential steps forward on satellite communications and networking - including flexible and programmable Radio-Frequency interfaces, network slicing, micro-services and containers over satellites, satellite network in a cloud. Finally, Section III will present some scenarios and examples, including the possibility to split the 5G Base Station (gNB) using Cubesat platforms, the design of highly reconfigurable satellites, 5G-satellites integration. All presented concepts will be associated with examples and when possible also short demonstrations using software emulators/simulators.
Overall objective and learning outcomes of the Short Course
Overall objective of the course is to make attendees familiar with concepts of softwarization and virtualization applied to the satellite environment.
Attendees will gain basic knowledge about the concepts of SDR, SDN, NFV
Attendees will understand the potential benefits and requirements of SDR, SDN, NFV
Attendees will understand how to integrate virtualization and softwarization within satellite communication systems
Attendees will be exposed to cutting edge technology and future scenarios in satellite communications
Attendees will learn how to experiment with the presented concepts by the usage of proper tools (e.g. mininet, Matlab, etc.)
The course is addressed to an audience familiar with the basics of communications and in particular satellite communications.
The course will be useful either for young attendees (M.Sc./Ph.D./Young Professional) interested in learning modern communication concepts and in understanding how satellite communication might evolve in the future, as well as for professionals and industry interested in knowing novel emerging paradigms in satellite communications.
Outline and Timeframe of the Short Course
The instructors of the course will be Prof. Fabrizio Granelli and Prof. Claudio Sacchi, that will alternatively address the audience. The level of detail in the different sections can be adapted to the background of the audience as well as the requests from the course organizers.
The table of contents (including indicative time-frame) of the course is the following:
Section I (Concepts and technologies) [3-4 hours]:
- Satellite communications: overview of present and current technologies
- Software Defined Radio
- Software Defined Networks (w/ hands-on on SDN using mininet)
- Network Function Virtualization
Section II (SDN/SDR and NFV in satellites) [2 hours]:
- Flexible RF interfaces
- Network Slicing (w/ hands-on examples using mininet)
- Micro-services and containers on satellites (w/ hands-on examples on docker environment)
- satellite network in a cloud
Section III (scenarios and examples) [2 hours]:
- 5G-satellites integration
- RRH-BBU split on Cubesats (w/ Matlab software examples on design of the link budget)
- Highly reconfigurable satellites
Instructor Short Course History
This course represents a novel initiative by the two instructors, based on joint research activities and ongoing lecturing efforts, in local courses as well as conference seminars.
The two instructors are well-known experts in their respective fields (F. Granelli in networking and C. Sacchi in satellite communications).
Prof. Sacchi is an expert speaker and gave several seminars on satellite communications around the world. He served as lead guest editor for the special issue of PROCEEDINGS OF THE IEEE, entitled: "Aerospace communications and networking in the next two decades: current trends and future perspectives" (issue published in November 2011) and for IEEE COMMUNICATIONS MAGAZINE for the Featured-Topic Special Issue: "Toward the Space 2.0 Era" (first part: published in March 2015).
Prof. Granelli was IEEE ComSoc Distinguished Lecturer for two terms (2012-2015) and visited several areas of the world discussing about recent developments in wireless networking. He gave several courses and tutorials in top level international conferences, including a very successful tutorial on "Softwarization and Virtualization in 5G - Concepts and Practice", which was held at IEEE WCNC 2018, IEEE ICC 2018, IEEE NFV SDN 2018, IEEE BlackSeaCom 2019 and 5G World Forum 2019 (Dresden, Germany). Based on the success of such tutorial series, which are being continued in IEEE Globecom 2019, he is co-writing a book by Elsevier due in 2020, called "Computing in Communication Networks".
Part of the content of the course will be based on such book and hands-on will be supported by a properly developed Virtual Machine developed to provide examples for the book reader - which will be freely distributed.
Artificial Intelligence / Autonomous Systems and Human Autonomy Teaming
Duration: 1-3 Days
The course is designed to appeal to scientific and engineering professionals who wish to obtain and or increase knowledge in Artificial Intelligence / Autonomous Systems and Human Autonomy Teaming. Introduction to the main foundational concepts and techniques used in Artificial Intelligence (AI); including decision making, planning, machine learning, and cognition. Includes a range of real-world applications in which AI is currently used in aeronautical and aerospace systems. Presentation of theoretical concepts occurs. Systematic study of methods and research findings in the field of human perception, with an evaluation of theoretical interpretations.
Provides a basis for the understanding of these perceptual capabilities as components in Artificial Intelligence in aviation/aerospace systems. The field of human-autonomy teaming (HAT) is fast becoming a significant area of research, especially in aviation. HAT is highly interdisciplinary, bringing together methodologies and techniques from robotics, artificial intelligence, human-computer interaction, cognitive psychology, neuroscience, neuroergonomics, and other fields. The topics covered will include technologies that enable human-machine interactions, the psychology of interaction between people and machines, how to design and conduct HAT studies, and real-world applications such as assistive machines.
Covered are the advanced systematic study of methods and research findings in the field of human and computer perception, with an evaluation of theoretical interpretations. Algorithmic foundations of AI / ML. Additionally, introduction to Autonomous Systems will be covered. Surveys the fundamentals of autonomous aircraft system operations, from sensors, controls, and automation to safety procedures, human factors. Presentation of advanced theoretical concepts for artificial intelligence in the areas of knowledge representation and search techniques. The concept of the perceptron and neuron will be covered along with 1st, 2nd, and 3rd generation neural networks.
Machine Learning is also covered: hands-on, live and in-action machine learning problems will be solved: utilizing regression analysis, ANNs, RNNs, CNNs (Deep Learning), SNNs, RELs, SVMs, and Bayesian Belief Networks. This course presents the latest major commercial uses of UAS, and manned aircraft that will be going from 2-pilot operations to 1-pilot operations to unmanned operations.
President (2022-2023); BoG (2018-2020) (2015-2017); President-Elect (2020-2021); VP Conferences (2016-2018); AESS Distinguished Lecturer (2020-2022); IEEE Fellow
Ultra Wide Band Surveillance Radar
Ultra Wide Band Surveillance Radar is an emerging technology for detecting and characterizing targets and cultural features for military and geosciences applications. It is essential to have fine range and cross-range resolution to characterize objects near and under severe clutter. This Short Course is divided into two parts.
Part I - Basic Surveillance Radar Design and Technology: (1-day)
• The Early History of Battlefield Surveillance Radar: There were some very interesting developments in radar technology that enabled our ability to detect fixed and moving objects in dense clutter. Examples of airborne phased array antennas and UWB radars will be summarized.
• Surveillance Radar Target Detection: A summary of the radar range equation and target statistics is presented. Of particular interest is the use of frequency agility and ultra-wide band signals for limiting the statistical variation of target returns.
• Surveillance Radar Modes: Analysis for Displaced Phase Center Array, Doppler Beam Sharpening, Ground Moving Rarget Indication are illustrated from early phased array antenna radars.
• UWB Phased Array Antenna: Electronically scanned antennas (ESA) are widely used for surveillance of large areas. Wideband waveforms place a significant demand on the ESA design to maintain gain and sidelobe characteristics.
Part II - Advanced Surveillance Radar Architectures: (1 day)
• UWB Synthetic Aperture Radar (SAR): A brief description of several UWB surveillance SAR systems will be provided, along with illustrations of the SAR image and fixed object detection capability.
• Interferometric SAR Designs: They use of multiple channels for SAR have provided terrain height measurements and improved detection of moving targets with UWB waveforms.
• UWB Ground Moving Target Indication: Space time adaptive processing (STAP) has been used for detecting and tracking moving targets in clutter. This section will discuss two approaches for increasing the bandwidth and maintaining geolocation accuracy: wideband STAP and Along Track Interferometry.
• Ultra Wideband Frequency Allocation Issues: A summary of worldwide regulation on waveform design and processing for spectrum compliance.
• New research in Multi-mode Ultra-Wideband Radar: Illustration fo new technologies that have promise for future multimode operation: simultaneous SAR and GMTI in a multichannel radar.
BoG (2022-2024) (2018-2020); President (2012-2013); AESS Short Course Instructor; Constitution and Bylaws Chair; Student Activities Co-Chair; History Chair; AESS Distinguished Lecturer (2020-2022);IEEE Fellow
Introduction to Airborne Radar
Duration: 3 Days
The third edition of Stimson’s Introduction to Airborne Radar has been acclaimed as ‘an absolute must have for all radar enthusiasts …. widely acknowledged as the only book to offer a complete overview of modern airborne radar principles of the last 15-20 years’. This three day course covers all of the material in the book in the same graphical style, explaining complex concepts in a clear and easily-understood manner, with numerous examples of modern systems and results.
- Basic concepts
- Essential groundwork
- Choice of radar frequency
- Pulsed operation
- The radar equation
- FMCW radar
- Pulse Doppler
- Air-to-air operation
- Imaging radar
- Electronic warfare
- Special topics and advanced concepts
- Representative radar systems
Hugh Griffiths holds the Thales/Royal Academy of Engineering Chair of RF Sensors at University College London, UK. He served as President of the IEEE AES Society for 2012/13, is a member of the IEEE AES Radar Systems Panel, and is Editor-in-Chief of the IET Radar, Sonar and Navigation journal. He has won numerous awards including the 2017 IEEE Picard Medal and the 2013 IET A F Harvey Prize.
BoG (2021-2023) (2018-2020); VP Education (2019-2021); AESS Short Course Instructor; AESS Rep to the Sensors Council (2016-2017), Young Professionals Program Representative (2018); AESS Distinguished Lecturer (2020-2022)
Introduction to Electronic Warfare
Duration: The course can be offered at different levels of depth, from half-day to five full days.
This short course gives an introduction to Electronic Warfare, ranging from Electronic Attack, Electronic Support, to Electronic Protection techniques, including STAP. The course continues with Electronic Intelligence, radar reverse engineering, and signal analysis, followed by basic direction finding and principles of stealth and low observables. The course can be offered at different levels of depth, from half-day to five full days. The targeted audiences are industry professionals, government technical personnel, defense research institutions, and Radar/EW practitioners. The course is taught at an unclassified level.
Radar Systems Prototyping
Duration: half-day, full-day or two-day
Whether you are a student seeking real data to prove your Ph.D. thesis, or a researcher planning for experimentation in your grant proposal, or a system engineer in need of a radar prototype to demonstrate your innovative idea to a customer, you will be faced with prototyping a radar system with limited time and budget. There exist many books and tutorials on radar signal processing, but little is found on how to build your radar prototype that can support and run these algorithms.
This short course will provide you with practical skills and techniques needed to build your advanced radar prototype. The focus is not on how devices/algorithms work, but on how to relate the choice of microwave devices and signal processing algorithms to the desired radar specifications. You will learn how to interpret datasheets, how components/algorithms affect each other, and how signal processing dictates RF constraints, and how signal processing can fix your RF limitations.
The course will end with a step-by-step MIMO radar design example, starting from the requirements and ending with a schematic and bill of material. The short course can be offered as an half-day, full-day or two-day class.
Past President (2020-2021); President (2018-2019); Short Course Committee Chair (2020); AESS Short Course Instructor; AESS Distinguished Lecturer (2020-2022); IEEE Fellow
Duration: 1 day
Skywave OTH radars operate in the high frequency (HF) band (3-30 MHz) and exploit signal reflection from the ionosphere to detect and track targets at ranges of 1000 to 3000 km. The long-standing interest in OTH radar technology stems from its ability to provide persistent and cost-effective early-warning surveillance over vast geographical areas (millions of square kilometres). Specifically, the chief advantages of OTH radar are to cover geographical areas where it is not possible or convenient to site conventional microwave radars and to provide early-warning and wide-area surveillance that may be used for cueing line-of-sight sensors. Owing to the relatively lower signal bandwidths and large computing infrastructure relative to conventional line-of-sight radars on mobile military platforms, OTH radar is often at the forefront of demonstrating the operational effectiveness of advanced radar processing techniques before it is possible to implement these techniques in radar systems operating at higher frequencies.
The tutorial is organized into three parts. The first introduces the fundamental principles of OTH radar design and operation in the challenging HF environment. This serves to motivate and explain the architecture and nominal capabilities of modern OTH radar systems. The second describes experimentally-validated models of the skywave propagation channel as well as adaptive processing techniques for clutter and interference mitigation. The third delves into emerging applications, including OTH passive radar, blind signal separation, and multipath-driven geolocation for target echoes and HF emitters of interest. A highlight of the tutorial is the prolific inclusion of experimental results illustrating the practical application of robust signal processing techniques to real-world systems. Participants will receive a complimentary text book “High Frequency OTH Radar” McGraw-Hill, NY, 2013.
AESS Short Course Instructor
Basic Algorithms for Target Tracking
Duration: 2 Days
This course goes through a variety of components that arise in target tracking algorithms, with a focus on single-scan algorithms. In many areas, reference is made to functions in the open-source copy leftfree Tracker Component Library (available online) so that attendees can rapidly apply the algorithms that are discussed. The presentation slides containing additional derivations will be made available.
2) Basic Estimation
• Mathematical Concepts
• Mathematical Coordinate Systems
• Signal Processing Topics
• Measurement Conversion
• Parameter Estimation
• Bayesian Estimation
• Assessing Estimator Performance
• Nonlinear Measurement Updates
• Track Initiation
• Linear Dynamic Models
3) Nonlinear Dynamics
• Deterministic Differential Equations
• Stochastic Dynamic Models
• Nonlinear Continuous-Time Propagation
• Celestial and Terrestrial Coordinate Systems
• Basic Orbital Dynamics
4) Estimation with Model Mismatches
• Simple Robustness Techniques
• Alternative Filters
• Multiple Model Algorithms
5) Target-Measurement Association
• Cost Functions for Measurement Assignment
• Single-Scan Assignment Algorithms
• Comments on Beams
• Single Scan Track Confirmation and Termination
• Offline Performance Prediction
• Multiframe Assignment
6) Estimation with High Nonlinearity
• Particle Filtering
• Particle Flow Filtering
• Track Initiation with Any Type of Measurement
BoG (2022-2024) (2017-2019) (2014-2016);Treasurer (2014-2022); AESS President (2008-2009); AUTOTESTCON Rep (2020-2022); AESS Short Course Instructor; Student Activities Co-Chair; NDIA Liaison; AESS Distinguished Lecturer (2020-2022); IEEE Fellow
Introduction to Systems Engineering
Duration: The course can be delivered in 1 day, or 2 days The 2-day course will include some practical exercises
Systems Engineering has emerged as being one of the most important and sought-after disciplines in the engineering world today as our systems under development become ever more complex. And engineering here means not only electrical & electronics engineering, but also mechanical engineering, civil engineering, manufacturing engineering, chemical engineering and similar. It applies to commercial systems as well as military and defense systems. Systems Engineering also applies to other than engineering, as other systems are in need of this discipline, such as banking and finance systems, IT systems, health-care systems, insurance management systems, even “help-desk” systems.
This course covers the essentials of systems engineering, starting with the basic requirements development and management, requirements validation, concept exploration & development, engineering development, risk management, testing, production planning, manufacturing implementation, operations, logistics planning (storage & shipping, upgrades, maintenance & repair, disposal) and interactions with program management.
BoG (2022-2024) (2019-2021); President-Elect (2022-2023); VP Publications (2019-2020); AESS Distinguished Lecturer (2020-2022); IEEE Fellow
- Good background in Mathematics, Physics.
- Some background in probability, random variables, and stochastic processes.
- Basic knowledge of signal analysis, Fourier analysis, digital filter design, statistical decision theory, and estimation theory.
- Basic knowledge of MATLAB programming.
- Course format and dates
The course is given in five days over a week period, intensive format.
During the intensive five-day course, practical sessions also with the use of MATLAB will be interleaved with classic lectures. Practical sessions are intended to strengthen the understanding of the theory and are based on programming and running routines that implement algorithms that are explained during the lectures. The attendees will familiarize with the problems and will understand how to set system parameters to achieve desired performances.
The course can be reduced to two intensive days with a selection of the arguments offered in the five-day course.
Prof. Maria Sabrina Greco – University of Pisa – email@example.com
- Course description
The course starts with an introductory description of basic radar concepts and terms. The radar equation needed for the basic understanding of radar is then developed, along with the concept of radar cross-section. The lectures then focus on the general schemes of coherent and incoherent radar systems and on the statistical models of the target received signals. Some fundamentals on the detection theory and the Neyman-Pearson criterion are provided and the detection strategies of target signals embedded in correlated Gaussian disturbance are developed along with their performance.
After a lecture on the statistical modeling of clutter, the course will focus on the radar ambiguity function, pulse compression and Doppler processing (MTI and MTD).
The course is concluded by some basic concept on tracking and Kalman filtering.
Principles of Modern Radar, Mark A. Richards, James A. Scheer, William A. Holm (Editors), Scitech, Raleigh, 2010.
BoG (2020-2022) (2017-2019); VP Technical Operations (2022); VP Conferences (2019-2021); IEEE/ION Position, Location & Navigation Symposium Rep; Navigation Systems Panel Chair; AESS Distinguished Lecturer (2020-2022)
Inertial Navigation Systems and Aiding
Duration: The course can be offered at different levels of depth, from one to five full days.
Inertial navigation systems (INS) are modern technologically sophisticated implementations of the age-old concept of dead reckoning. The basic philosophy is to begin with a knowledge of initial position, keep track of speed and direction, and thus be able to determine position continually as time progresses. Perhaps surprisingly, the rise of GNSS has actually expanded the need for inertial-based systems. Accelerometers and gyroscopes are the basic sensors utilized and since INS are essentially self-contained, they do not suffer from interference or unavailability that can affect radio-based systems such as GNSS. Furthermore, INS are highly complementary to GNSS since they provide high data rates, low data latencies and attitude-determination along with position and velocity.
We will start by highlighting the basic principles of operation of an inertial navigation system. We will focus initially on the concepts underlying the algorithms used to determine position, velocity and attitude from inertial sensor measurements. Key error characteristics will then be described as well such as the Schuler oscillation and vertical channel instability. We will also consider the impact of various sensor errors on system performance.
Navigation-grade inertial systems are characterized by so-called “free inertial” position error drift rates on the order of one nautical mile-per-hour of operation. Such performance implies a certain class of gyros and accelerometers and thus certain specifications on biases, scale factor errors and noise. For more than five decades, the Kalman filter has been the primary tool used to reduce inertial drift through the integration of various sensors. Specifically, the aiding sources (e.g., stellar, Doppler, GPS, etc) are used by the filter to estimate the errors in the free inertial processing. Thus, the heart of any aided-inertial Kalman filter is the inertial error model including, specifically, sensor errors. We will discuss these models and will proceed to explain how aiding source observations are then used by the filter, in conjunction with the models, to estimate the inertial errors. For example, a given aiding source may provide an independent measurement of position, yet somehow the filter is able to use this in order to estimate gyro biases in the inertial system.
The daunting matrix mathematics involved in the full algorithm can be extremely intimidating to the newcomer. In this course, the basic concepts of estimation theory will be reviewed and the Kalman Filter will be described first in terms of simple one-dimensional problems for which the full algorithm reduces to an approachable set of scalar equations. We will look at the performance of the filter in some simple case studies and by the end will have an intuitive feel for how the full filter operates. We will then apply the Kalman filter to the aiding of inertial systems. We will see how external sources of position and velocity (such as GPS) can be used first to measure inertial system error and then, with the aid of the Kalman filter, to estimate and correct inertial sensor error as well as system error.
Machine and Deep Learning for Data Fusion
Duration: 1-2 days
In this short course, I will present some techniques for fusion and analytics to process big centralized warehouse data, inherently distributed data, and data residing on the cloud. The broad range of artificial intelligence and machine and deep learning techniques to be discussed will handle both structured transactional and sensor data as well as unstructured textual data such as human intelligence, emails, blogs, surveys, etc., and image data. Specifically, the Short Course will explore Deep Fusion to solve multi-sensor big data fusion problems applying deep learning and artificial intelligence technologies.
As a background, this short course is intended to provide an account of both the cutting-edge and the most commonly used approaches to high-level data fusion and predictive and text analytics. The demos to be presented are in the areas of distributed search and situation assessment, information extraction and classification, and sentiment analyses. There will be some hands-on exercises.
Some of the short course materials are based on the following two books by the speaker: 1) Subrata Das. (2008). “High-Level Data Fusion,” Artech House, Norwell, MA; and 2) Subrata Das. (2014). “Computational Business Analytics,” Chapman & Hall/CRC Press.
Topics include the following: High-Level Fusion, Traditional Machine Learning Algorithms, Popular Deep Learning Algorithms (e.g. Convolutional & Recursive Neural Networks, Deep Belief Networks and Restricted Boltzmann Machine, Stacked Autoencoder, ResNet, LSTM), Bagging and Boosting, Descriptive and Predictive Analytics, Text Analytics, Decision Support and Prescriptive Analytics, Cloud Computing, Distributed Fusion, Hadoop and MapReduce, Natural Language Query, Graphical Probabilistic Models, Bayesian Belief Networks, Text Classification, Supervised and Unsupervised Classification, Information Extraction, Natural Language Processing, Demos in R and Python.
Overall objective and learning outcomes of the Short Course: Prepare students, researchers, and industry practitioners with cutting-edge tools and technologies to face the new wave of data science challenges for data fusion.
Intended Audience: The intended audience include designers and developers of analytics systems for any vertical (e.g., defense, healthcare, finance and accounting, human resources, customer support, transportation) who work within business organizations around the world. They will find the course useful as a vehicle for moving towards a new generation of big data fusion and analytics approaches.