Artificial Intelligence at FAU's College of Engineering and Computer Science

F L O R I DA

AT L A N T I C

U N I V E R S I T Y

COLLEGE OF ENGINEERING AND COMPUTER SCIENCE

These are our stories THE AI ECOSYSTEM O U R FAC U LT Y & ST U D E N T R E S E A R C H E N G AG E M E N T I N A I

• Smart Health • Clinical Data Analytics • Fraud Detection

• Cyber-physical Energy Systems • Sensor Nets • Internet of Things (IoT)

• Emergency Planning & Response

FOUNDATIONS OF AI • Sensing • Machine Learning • Connected Autonomy

• Intelligent Transportation • Logistics & Supply Chain

• Infrastructure Resilience • Robotics/Drones (air, ground & sea) • Bio-robotics

CAN YOU IMAGINE…

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Imagine if in a world of connected autonomous devices, the behavior of robots is inconsistent and unpredictable… How do robots get rewarded for proper behavior? How do robots learn and generalize as humans do?

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Imagine if your autonomous car doesn’t trust you…

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Imagine if you could talk on the phone while diving underwater… Imagine if you had “Google Maps” for navigating the world’s oceans, underwater caves, and coral reefs…

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Do you think it’s important to know in real time, but sufficiently in advance, the onset of a medical condition that can be fatal but preventable, like a seizure or atrial fibrillation episode that may appear in combination with Alzheimer’s or Parkinson’s? What if such tragedies could be avoided by a wearable device like a bracelet that uses the latest AI technology at minimal cost and maximum safety? How can we reduce hospital re-admissions and improve patient care?

ASK YOURSELF… •

What can we learn from the behavior of marine life to create an artificial school of fish for successful search and rescue operations?

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How can our robots help us reach sea depths that humans cannot, to monitor environmental changes and protect our coastlines?

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Would you think that being able to harvest wave and solar energy to recharge power of our drone fleets in the middle of the ocean at $0 cost is important?

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Can artificial neural networks help us reduce energy consumption of underwater transport systems?

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What if an armada of flying robots could autonomously restore wireless connectivity in the event of an emergency by forming a wireless multi-hop communications backbone to the Internet?

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Our wireless air-waves are full! How can we ensure interference-free and secure spectrum sharing among users for 5G wireless communications?

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When you hear the term “Big Data,” what do you think of? For some, it might conjure up images of numbers and statistics, and others might picture big computer screens with lots of information.

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How is FAU introducing cutting-edge infrastructure and innovative educational programs at the College of Engineering & Computer Science?

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How many times have you bought something because an appealing ad popped up on your phone at just the right time? How many times have you bought something because an appealing ad popped up on your phone at just the right time?

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What if we could use electrical stimulation in the brain to help amputees autonomously control artificial limbs?

These are the stories of our experts -

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AI + Data Analytics for Autonomy

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01.

Imagine if in a world of connected autonomous devices, the behavior of robots is inconsistent and unpredictable…

How do robots get rewarded for proper behavior? How do robots learn and generalize as humans do?

One of our goals at FAU is to accelerate scientific discovery and research in the most efficient way possible.

However, challenges can arise when intelligent physical systems interact with one another. Thanks to a grant from the National Science Foundation, researchers at FAU’s College of Engineering and Computer Science are exploring Reinforcement Learning (RL) strategies in cyber-physical systems, where systems are rewarded for behaving correctly even when they engage with systems that are reacting inconsistently. Our developments will contribute to a new self-learning intelligent control framework, where systems can decide how to interact with their inconsistent neighbors in a way that will improve how they learn.

The proposed system will minimize the risk of transferring inaccurate or negative information, while enhancing the learning speed. Our system will be integrated into multi-unmanned aerial vehicles (UAV) platforms.

The recent wave of artificial intelligence (AI) has resulted in tremendous advancements in research, but also presents challenges to the community.

Among many of the AI techniques, adaptive dynamic programming and reinforcement learning is considered one of the key methods for learning-based intelligent decision-making process. Researchers at the College of Engineering and Computer Science, with a grant from the National Science Foundation, are developing an innovative autonomous approach for decision making in complex environments. By advancing the foundations, architectures, and algorithms for autonomous learning, they will facilitate the capability of learning and generalization for decision-making.

This project will also provide unique opportunities to attract and educate future professionals to the field of engineering, particularly women. The team will collaborate with the FAU Women in Engineering program, as well as the Community College of Rhode Island, the largest community college in New England with a 62% female student population. An integrated research and education plan, including a “Real-Time Decision-Making Workshop” and a new related curriculum will help promote excellence in education while also enriching the participation of students with diverse backgrounds.

PI: Xiangnan Zhong, Asst. Prof.

Sponsor: National Science Foundation, $237K, 08/2019 – 08/2022

PI: Xiangnan Zhong, Asst. Prof.

Sponsor: National Science Foundation, $174K, 07/2019 – 02/2021 These are the stories of our experts -

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02.

Imagine if your autonomous car doesn’t trust you…

Imagine if your autonomous car does not trust you… Thinking back just a few years, we never could have imagined owing a car that drives on its own, but technology has advanced in unprecedented ways. While autonomous systems such as self-driving cars and care-giving robots are highly efficient, recent studies have shown that people have negative attitudes about using them. Researchers at the College of Engineering and Computer Science are studying the evolution of trust between humans and growing autonomous technologies. In the study, funded by a seed grant from FAU, they explore how to establish, sustain, and rebuild trust between humans and autonomous systems.

PI: Mehrdad Nojoumian, Asst. Prof.

Sponsor: Florida Atlantic University, $25K, 2017 – 2018

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03.

Imagine if you could talk on the phone while diving underwater…

Imagine if you had “Google Maps” for navigating the world’s oceans, underwater caves, and coral reefs…

Underwater robot navigation has traditionally relied on different kinds of power-hungry, expensive sensor systems that are difficult to deploy and scale. Researchers at FAU’s College of Engineering and Computer Science are developing game-changing algorithms and prototype technology for rapid deployment and validation of inexpensive acoustic localization systems that offer superior resistance to environmental disturbance and faulty sensor measurements.

With an overall goal of building adaptive-precision localization systems that can on-the-fly trade-off accuracy for computational complexity, these new systems will enable the deployment of distributed swarms of robots, vessels, or divers that can rapidly map the world’s oceans. Researchers are in the process of developing a low-cost self-programmable acoustic array to quantify the localization range and accuracy of underwater robots relatively to two acoustic sources/ beacons that are deployed in known locations (similar to how GPS works, but for underwater). Tests will first be conducted in a 30-foot deep acoustic test tank at FAU’s Boca Raton campus, and then in the Atlantic Ocean off the coast of Dania Beach at FAU’s Institute for Ocean and Systems Engineering (SeaTech).

PIs: Stella Batalama, Prof. and Dimitris Pados, Prof.

Sponsor: National Science Foundation, $500K, 2017 – 2020 These are the stories of our experts -

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04.

How can our robots help us reach sea depths that humans cannot, to monitor environmental changes and protect our coastlines?

Fish use specialized organs to detect obstacles, track prey, and sense attacks from predators.

Researchers at FAU are examining the role that fluid-mechanics plays in the behavior of fish.

By using reinforcement learning algorithms, they were able to determine optimal behavior to achieve specific goals, including obstacle-avoidance and energy-efficiency. This allowed them to train individual smart-agents with independent ‘brains,� enabling the fish to sense and respond more effectively to others.

PI: Siddhartha Verma, Asst. Prof.

Sponsor: Florida Atlantic University, $46K, 07/2019 – 06/2021

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05.

What can we learn from the behavior of marine life to create an artificial school of fish for successful search and rescue operations?

You may be joined by a robot on your next scuba diving adventure! Researchers at FAU’s College of Engineering and Computer Science are training independent robotic vehicles to perform underwater tasks such as pollution detection, coastal reconnaissance, structural inspections, and long-term environmental monitoring.

While conventional marine vehicles already exist, the FAU team is going one step further by designing bio-inspired propulsion mechanisms. By using a fin-like structure instead of a typical propeller, they move with peak efficiency and stealth. And, through deep reinforcement learning, the researchers also discovered the optimal fin motions necessary to achieve a variety of goals including swimming, minimizing power consumption, and increased agility.

PIs: Siddhartha Verma, Asst. Prof.; Oscar Curet; Assoc. Prof.; Dimitris Pados, Prof.; Georgios Sklivanitis, Asst. Prof.; and Yufei Tang, Asst. Prof.

Sponsor: Florida Atlantic University, $35K, 05/2018 – 04/2019

These are the stories of our experts -

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06.

Would you think that being able to harvest wave and solar energy to recharge power of our drone fleets in the middle of the ocean at $0 cost is important?

College of Engineering and Computer Science for autonomous navigation, intelligent tracking of boats, and automated launch and recovery of an aerial drone.

With a $1.1M grant from the Office of Naval Research, FAU scientists will explore strategies to provide accurate geolocation while searching for underwater targets, as well as improve collision avoidance and control. The research efforts involve graduate and undergraduate students, specifically in creating 3D surveillance maps to enable improved detection, classification, and tracking of floating objects of interest that would trigger video streaming to a shore station for potential human intervention.

PI: Manhar Dhanak, Prof.

Sponsor: Office of Naval Research, $1.1M, 2018 – 2023

Sounds too good to be true, but that reality may be closer than you think. Researchers at FAU’s College of Engineering and Computer Science have developed a prototype turbine that uses marine energy and solar wind as renewable sources of power for a floating atsea recharge station, thanks to a $1.25M grant from the Department of Energy.

These maritime charging stations are designed for unmanned aerial drones, which are used to enhance coastal surveillance, protection of at-sea assets, and aiding in search and rescue operations.

PIs: Manhar Dhanak, Asst. Prof. and Pierre Beaujean, Prof.

Sponsor: Department of Energy, $1.25M, 2019 – 2022

Another group of researchers at FAU’s College of Engineering and Computer Science is using reinforcement learning to implement navigation control for fully autonomous USVs. The controller independently determines the desired speed, heading, power expenditure, or navigation trajectory of the USV, and the optimal low-level actions needed to accomplish these goals. The algorithms being introduced are able to compensate for unforeseen circumstances, such as environmental disturbances, allowing the USVs to be more effective in their applications for area-mapping, search-and-rescue operations, and coastal surveillance.

PI: Siddhartha Verma, Asst. Prof.

Sponsor: Florida Atlantic University, $24K, 07/2019 – 06/2021

At-sea charging stations can also power monitoring instruments or recharge other unmanned surface vehicle (USVs), such as one being developed by FAU’s These are the stories of our experts -

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07.

Can artificial neural networks help us reduce energy consumption of underwater transport systems?

In an effort to mitigate this energy loss, researchers at the College of Engineering and Computer Science are using artificial neural networks to classify, control, and regulate the structures in turbulent flows. By using artificial neural networks, as opposed to a traditional analytical approach, they can more easily identify non-linear correlations in both space and in time and thereby implement autonomous control mechanisms to suppress fuel loss.

PI: Dr. Siddhartha Verma, Asst. Prof.

Sponsor: Florida Atlantic University, $69K, 07/2019 – 06/2021

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08.

What if an armada of flying robots could autonomously restore wireless connectivity in the event of an emergency by forming a wireless multi-hop communications backbone to the Internet?

Researchers at the College of Engineering and Computer Science are working with researchers from GE Aviation’s Advanced and Special Projects Division to build fieldready, small size, low weight and power avionics platforms with embedded communication and mesh networking capabilities. FAU researchers are currently working toward the implementation of high-speed (510 Mbps) interference-avoiding links that can operate over long range (approximately 2 km) using GE’s Mxxx family of multi-antenna programmable computing and radio platforms.

PIs: Dimitris Pados, Prof. and Georgios Sklivanitis, Asst. Prof.

Sponsor: GE Aviation; Advanced and Special Projects Division, $285K, 2018 – 2020

These are the stories of our experts -

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09.

Our wireless air-waves are full! How can we ensure interference-free and secure spectrum sharing among users for 5G wireless communications?

Wireless carriers are expected to start boosting LTE speeds and augment their 5G rollouts later this year. However, to ensure efficient interference-free and secure spectrum sharing among all radio spectrum users, researchers at FAU’s College of Engineering and Computer Science developed algorithms for rapid high-confidence spectrum characterization using AI and machine learning.

Existing approaches for spectrum characterization require expensive, high-maintenance, expert systems that rely on prior knowledge of signal properties, thus incurring significant cost before taking further action.

FAU’s researchers developed data analytics algorithms that can rapidly recognize unlicensed spectrum users by evaluating the quality of radio-spectrum data captured with low-cost software-defined radios.

The performance of the proposed algorithms will be tested across numerous types of signals (such as phase, amplitude, and frequency modulated signals) that experience different effects due to channel propagation and hardware impairments.

PIs: Dimitris Pados, Prof. and Georgios Sklivanitis, Asst. Prof.

Sponsor: Air Force Research Laboratory, $52K, 2019 – 2020

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10.

When you hear the term “Big Data,” what do you think of? For some, it might conjure up images of numbers and statistics, and others might picture big computer screens with lots of information.

PIs: Taghi Khoshgoftaar, Prof.; Xingquan Zhu, Prof.; Hari Kalva, Prof.; Pierre Beaujean, Prof; and Ramesh Teegavarapu, Prof.

Sponsor: National Science Foundation, $600K, 08/2014 – 07/2017

The study of Big Data encompasses the analysis of extremely large data sets with vast numbers of instances and features in order to make reliable predictions and connections. This is critical in several fields including bioinformatics, ocean energy, social media mining, climate monitoring, emergency response, medicine, national security, and commerce.

At FAU, our research across all these fields is ongoing.

It’s great that we have access to all this data, but how do we store and secure them, and also ensure that we have the proper tools to analyze them? Thanks to a $600,000 grant from the National Science Foundation, researchers at FAU’s College of Engineering and Computer Science now have access to large-scale computational infrastructure capable of solving big data challenges.

These are the stories of our experts -

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11.

How is FAU introducing cuttingedge infrastructure and innovative educational programs at the College of Engineering & Computer Science?

FAU is proud to be a leader in field of Artificial Intelligence.

In addition to offering the first master’s degree program in AI in the entire state of Florida, researchers at the College of Engineering and Computer Science are now establishing an Artificial Intelligence and Deep Learning (AIDL) laboratory at FAU to support computational tasks in numerous research disciplines. This lab, thanks to a grant from the National Science Foundation, will significantly advance FAU’s standing in AI and analytics, while stimulating South Florida’s technical innovations.

The creation of AIDL at FAU will help build a crosscampus computing platform, with immediate AI and deep learning core support for research, training, and development purposes.

PIs: Xingquan Zhu, Prof.; Dimitris Pados, Prof.; Laurent Cherubin, Assoc. Prof.; Hanqi Zhuang, Prof.; and Taghi Khoshgoftaar, Prof.

Sponsor: National Science Foundation, $653K, 10/2018 – 09 /2021

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12.

How many times have you bought something because an appealing ad popped up on your phone at just the right time?

Targeted digital ads are playing an increasingly influential role when it comes to consumer shopping habits. What you may not realize is that the most relevant ads are able to come across your screen at a certain time due to a tremendous amount of scientific research. And, this demand for accurate computational advertising is rapidly growing!

The goal of computational advertising is to accurately display ads on users’ devices. But this includes several challenges, such as how to identify the potential value of an ad impression, how to estimate the probability of a user clicking on an ad, and how to determine the optimal bidding price of an impression, especially when bidding is triggered thousands of times every second!

To address these challenges, researchers at FAU’s College of Engineering and Computer Science have teamed up with Bidtellect Inc., a real-time bidding platform that allows brands to activate advertising campaigns. Their goal is to design a set of real-time pricing tools and algorithms for bid engines to optimize the bid price of any incoming ad impression, with less than 100 millisecond response time.

Their research focuses on collecting data, implementing big data analytics platforms to support realtime data analysis, and designing new machine learning algorithms to support online advertising and real-time bidding.

PI: Dr. Xingquan Zhu, Prof.

Sponsor: Bidtellect Inc., $90K, 08/2016 – 07/2019 These are the stories of our experts -

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13.

What if we could use electrical stimulation in the brain to help amputees autonomously control artificial limbs? with human subjects at a fraction of the cost, while accumulating data much more quickly, which will be a significant breakthrough. This innovative approach can be applied to amputees, as well as other people who suffer from neurotrauma or neuromuscular degeneration. By reconnecting the previously severed sense of touch, neuroprosthetics can substantially improve the lives of millions of disabled people around the world.

PIs: Erik Engeberg, Assoc. Prof.; Emmanuelle Tognoli, Prof.; Jianning Wei, Assoc. Prof.; and Sarah Du, Assoc. Prof.

Sponsor: National Institutes of Health, $1.4M, 07/2017 – 06/2021

It sounds impossible, but with advances in an emerging field called virtual neuroprosthesis, we can do exactly that! And researchers at FAU’s College of Engineering and Computer Science are making unprecedented progress in this area, thanks to a $1.4 million grant from the National Institutes of Health.

Currently, there is no systematic understanding of how tactile feedback signals can help restore sensation and improve motor function in amputees with neuroprosthetic limbs. Since the research involving neural implants with human subjects is very expensive, the progress to develop neuroprosthetic limbs has been slow compared to other areas of robotics. It’s also a lengthy process to obtain FDA approval to implant electrodes in human subjects.

Therefore, FAU is focused on developing a virtual neuroprosthesis and conducting meaningful experiments

These are the stories of our experts -

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AI + Data Analytics for Smart Health

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14.

Do you think it’s important to know in real time, but sufficiently in advance, the onset of a medical condition that can be fatal but preventable like a seizure or atrial fibrillation episode that may appear in combination with Alzheimer’s or Parkinson’s? What if such tragedies can be avoided by a wearable device like a bracelet that uses the latest AI technology at minimal cost and maximum safety? What if such wearable devices are used for long-term in-house monitoring and cognitive screening of patients for the detection of developing chronic medical conditions? How can we reduce hospital re-admissions and improve patient care?

We use advanced sensor technology, data analytics, and AI to (i) prevent onset of medical conditions, (ii) do prognosis of cognitive medical conditions, and (iii) support remote therapy management.

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These are the stories of our experts -

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i.

Researchers at the College of Engineering and Computer Science are aiming to do just that, by developing a wearable device with innovative methodologies and algorithms that can monitor patients outside of a hospital and help detect and manage these diseases more effectively. When a patient wears the device, high resolution data can be transmitted and monitored to detect the onset of a disease and also predict the future risk of onset. With a grant from the National Science Foundation, researchers are developing an algorithm and software toolkit to facilitate long-term health monitoring to support early detection. This novel approach is part of an emerging field called disease risk prediction research, and we are excited to be at the forefront of this effort.

PI: Behnaz Ghoraani, Asst. Prof.

Sponsor: National Science Foundation, $322K, 09/2019 – 09/2022

Atrial fibrillation (AF) is the most common heart rhythm disorder in the country, affecting 2.3 million Americans. As a progressive disease, AF worsens over time and becomes more resistant to therapy, eventually leading to increased strokes and heart failure to threaten early mortality. A team of researchers at the College of Engineering and Computer Science is hoping to change that. With a grant of almost $500,000 from the National Institutes of Health, they are designing software tools that use sensors and data analytics to dramatically improve detection of AF sources inside the atria, at no additional cost or safety risk to the patient. In fact, this data would even reduce the need for multiple procedures of expensive AF therapy and mitigate complications for the patient! The data would enable researchers to analyze the progression of AF for each patient in real time, and would significantly improve the success of AF treatment before the disease progresses to the permanent and often fatal stage, literally saving lives.

ii.

While patients with MCI are typically evaluated by cognitive testing and neurological exams to estimate risk and rate of decline, these tests may not accurately predict progression and are generally in the primary care setting, which is why there is often a delay in diagnosis. What we need is an objective, at-home way to detect who is most at-risk, so that early intervention or prevention strategies can be initiated. We’re excited to share that with a grant from the Florida Department of Health, researchers at the College of Engineering and Computer Science have developed a system of wearable sensors for a home-based cognitive screening system that can detect early stages of MCI and Alzheimer’s. These sensors are inexpensive and intrinsically easy to use, and have great potential to improve how we monitor the older population. By using tools that will infer a patient’s cognitive decline before they advance to Alzheimer’s, we can reduce the number of patients with Alzheimer’s.

PIs: Behnaz Ghoraani, Asst. Prof. and James Galvin, Prof.

Sponsor: Florida Department of Health, $95K, 01/2019 – 12/2020

iii. As

more people each year are diagnosed with Parkinson’s, a debilitating cognitive disease, we at the College of Engineering and Computer Science are committed to finding ways to expedite treatment and early intervention. We are proud to share that we have created an innovative sensor-based system for collecting data to support remote therapy management.

The sensor uses algorithms to record body motion and detect patterns of Parkinson’s symptoms and their severity. The sensors then provide advanced analytics that are capable of forming a reliable, remote therapeutic management system for immediate use by patients suffering from troubling motor fluctuation, thereby facilitating treatment.

PI: Behnaz Ghoraani, Assist. Prof.

Sponsor: National Institutes of Health, $456K, 04/15 - 03/19

PI: Behnaz Ghoraani, Asst. Prof.

Sponsor: Florida Atlantic University – Seed Funding, $15K, 04/2019 – 04/2020

We all know that South Florida is the ideal destination for retirement. What you may not know is that of the 5 million Americans affected by Alzheimer’s disease, 10% are Florida residents! For those over age 65, the prevalence of mild cognitive impairment (MCI) is an estimated 21%, of which 75% will progress to Alzheimer’s. The sooner we are able to detect MCI, the sooner we can slow, or even stop, the progression to Alzheimer’s.

South Florida is ranked 4th in the country for highest concentration of populations, and over 19% of Florida’s population is 65 and older. The complication of the health conditions of seniors, combined with limited resources, have significantly increased medical spending and severely impact quality of life.

For example, hospital re-admission – when a patient who was discharged returns within a short period of time – is a major challenge of the healthcare system.

A re-admission is particularly expensive for insurance

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companies, it adds an extra burden to healthcare facilities, and also downgrades the patient’s quality of life. Re-admissions can be triggered by many factors, such as medication side effects, or change of lifestyle or medical conditions.

Therefore, complex analytical modeling and better coordination is needed among hospitals, primary care, and home health providers to help identify patients who are more likely to be re-admitted and provide additional care to reduce avoidable readmissions. To try to mitigate this issue, researchers at the College of Engineering and Computer Science are designing a learning platform to analyze health data more effectively so it can be used to achieve better quality of life for these seniors. While existing systems are unable to support the integration and analysis of this data, FAU’s new platform provides a way to harness the relevant data and facilitate more effective care.

PIs: Xingquan Zhu, Prof.; Ankur Agarwal, Assoc. Prof.; and Dingding Wang, Asst. Prof.

Sponsor: National Science Foundation, $599K, 2018 – 2021

These are the stories of our experts -

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Please contact: 777 Glades Road EE 308 Boca Raton, FL 33431-0991 561.297.3400 | info@eng.fau.edu eng.fau.edu

Mr. Michael Miller Director of Development Phone: 561.297.2083 Cell: 805.448.5430 Email: millermichael@fau.edu