Author: karenjoh

Husky Games Takes Honorable Mention at Design Expo 2020

Husky Game Development (HGD), a student Enterprise focused on video game development, won Honorable Mention accolades at Michigan Tech’s Design Expo 2020, presented virtually this April.

The HGD winning project, “Lost in Mazie Mansion,” is a 2D mystery-puzzle game. To win, you’ll need the help of Mazie. But you’ll have to play by the house’s rules, dodge monsters patrolling the halls, solve puzzles, and find the keys to get Mazie’s memory back.

Husky Games Group

HGD team leads are CS undergraduates Colin Arkens and Xixi Tian; faculty advisor is Scott Kuhl, Computer Science. The team was sponsored by the Pavlis Honors College’s Enterprise Program. View a video about the game here.

HGD teams experience a full game development cycle, including ideation, design, and end product. Students explore a wide variety of video game engines and platforms, including Windows, Android, Xbox, and an experimental Display Wall.

Visit the HGD website here.


Health Informatics Adds Stackable Certificates in Healthcare AI, Security and Privacy

The College of Computing’s Health Informatics graduate program recently announced the addition of stackable graduate certificates in two high-growth areas: the Artificial Intelligence in Healthcare Certificate and the Security and Privacy in Healthcare Certificate.

Designed for working professionals, as well as full-time students, the new certificates can be completed entirely online using a rich learning environment designed by Health Informatics’ faculty experts certified in online learning.

The certificates’ courses have been developed to build critical skills in healthcare, artificial intelligence, and security and privacy, thus there are no prerequisites to get started, says Guy Hembroff, director of the Health Informatics program (pictured)

Each certificate requires the completion of three courses (9 credits). Students who complete both certificates will earn 18 credits towards the required 30 credits for a Health Informatics master of science degree, which can also be completed entirely online.

For emerging details about these new certificate programs, please visit the Health Informatics website.


The Artificial Intelligence (AI) in Healthcare Certificate provides individuals with the ability to optimize resources and clinical workflow, enhance clinical quality and safety, detect healthcare fraud, and improve patient outcomes and access to care while decreasing costs. Careers in this area use the vast volume of digital health data to improve healthcare operations, safety, and delivery.


The Security and Privacy in Healthcare Certificate provides individuals with the ability to secure and protect the privacy of health information, comply with state and federal healthcare data regulations, ensure interoperability in the exchange of healthcare data, and ensure healthcare systems are capable of successfully adopting new technologies to improve the quality and efficiency of patient care.


Computing Students Participate in DesignExpo 2020

College of Computing students participated widely at Michigan Tech’s Design Expo 2020, which was held virtually in April.

Participating Enterprise Teams included Humane Interface Design Enterprise (HIDE), IT Oxygen, and Husky Game Development.

College Senior Design Teams developed a cybersecurity “Penetration Testing Course,”a “Cloud Computing Cost Analysis,” and an “Automated Distributed Configuration Management Systems.”

See project details below. Learn more about Design Expo here.


Senior Design Team: Penetration Testing Course

Team Members: Chris Koch, Joe Bartkowiak, Kelson Rose, Austin Clark, Computer Network and System Administration
Advisor: Yu Cai, College of Computing

Project Overview: To meet the need for new courses in the new Cybersecurity degree program, our team was tasked with developing a Penetration Testing course, which includes the business how-to as well as technical skills necessary to succeed in the field as a professional ethical hacker. We delivered a completed course, including a chosen course textbook, slides, an online lab set with accompanying lab manuals, and exams. GenCyber is a Michigan Tech summer program for local younger students. We provided instructional material, utilized Google Interland activities for younger students, and created the GenCyber camp curriculum to further develop and improve this course—another step toward the future of cybersecurity.


Senior Design Team: Cloud Computing Cost Analysis

Team Members: Alex Kuhn, Austin Walhof, Ryan Jacobson, and Stephen Grobbel, Computer Network and System Administration
Advisor: Todd Arney, College of Computing

Project Overview: Our team compared the cost of running services in a cloud environment between the three largest service providers: Amazon Web Service, Google Cloud Platform, and Microsoft Azure.


Senior Design Team: Automated Distributed Configuration Management Systems

Team Members: Andrew Hitchcock, Tim Graham and Derek Laker, Computer Network and System Administration
Advisor: Tim Wagner, College of Computing
Sponsor: College of Computing

Project Overview: Systems administrators working in environments of all sizes are rapidly adopting configuration management systems to automate provisioning and deployment, enforce system configuration, and streamline their work. However, it can be difficult to figure out which product to choose. Our project consisted of deploying three of the most popular products on the market today— Puppet, Ansible, and Saltstack—and comparing the computing resources that they used, their ease of use, and the scenarios that they would be most fit for.


Enterprise Team: Husky Game Development (HGD)

Team Leaders: Colin Arkens and Xixi Tian, Computer Science
Advisor: Scott Kuhl, Computer Science
Sponsor: Michigan Technological University Pavlis Honors College’s Enterprise

Program Background: Husky Game Development (HGD) is a student-run Enterprise focused on developing video games. Each year, Husky Game Development breaks up into subteams of around six students who experience a full game development cycle, including ideation, design, and end product. HGD explores a wide variety of video game engines and platforms, including Windows, Android, Xbox, and an experimental Display Wall.
Overview: Do you know that old mansion down on the corner? Of course you do. Everyone does. No one who’s entered it was ever seen again. Will you be? Lost in Mazie Mansion is a 2D mystery-puzzle game. To reform the mansion and escape, you’ll need the help of Mazie, the only one to nearly solve the mystery. Play by the house’s rules, dodge monsters patrolling the halls, solve puzzles, and find the keys to get Mazie’s memory back.


Enterprise Team: IT Oxygen

Team Leaders: Calvin Voss, Computer Science; Zack Metiva, Computer Network and System Administration
Advisors: Nagesh Hatti, Electrical and Computer Engineering; James Walker, Computer Science
Sponsors: DENSO, Ford Motor Company, Little Brothers Friends of the Elderly, Mel and Gloria Visser, Northern Specialty Health, Michigan Technological University Pavlis Honors College’s Enterprise Program, Milan and Shailee Lathia

Background: IT Oxygen is a cross-disciplinary, student-run Enterprise that specializes in Information Technology (IT) for student organizations and businesses, with a focus on developing Information System and Information Technology solutions. Team members work on real-world projects that foster skill development and utilize business intelligence. Areas of interest include systems and information analysis, software development, database design, data sciences, cybersecurity, and web-based application development.

Overview: This year, the IT Oxygen Enterprise is working on projects sponsored by Ford, Little Brothers Friends of the Elderly, Northern Specialty Health, and DENSO. In the area of data analytics, IT Oxygen is building predictive models and applying statistical analyses to understand the relationship between technical obsolescence and purchasing strategy for automotive electronics—thanks to support from DENSO. For Ford, a team has been working with the Wireless Communication Enterprise (WCE) to provide data analysis and storage for a smart home energy management system. Finally, IT Oxygen is also collaborating with WCE on continued efforts to improve Little Brothers’ holiday resource management and medical transportation scheduling systems.



Enterprise Team: Human Interface Design Enterprise (HIDE)

Team Leaders: Christopher Ward and Justin Martin, Computer Science
Advisor: Robert Pastel, Computer Science
Sponsor: CCDC Ground Vehicle Systems Center (US Army)

Background: The members of Humane Interface Design Enterprise (HIDE) come together to design, develop, and evaluate user interfaces. The goal is to make daily work more efficient and easier to manage. As a whole, the team works together to design and test different applications for industry sponsors that can be used on Android, iPhone, and other devices. HIDE accomplishes these projects by combining knowledge from multiple disciplines, such as computer science, psychology, and human factors. HIDE team members can get involved in various stages of the design process, from developing an app by programming, to evaluation by designing usability tests and analyzing data.

Overview: Tempi.st is a project from the Ground Vehicle Systems Center, a research center for the US Army located in Warren, Michigan. Tempi.st is a program designed to provide students with the opportunity to work on a real-world project, and is aimed to connect the students to an industry where they can actively participate in research in order to expand their knowledge base and deliver new ideas to the industry in return.

Our objective is to utilize Raspberry Pis to collect weather data in real time for its given location, and to send the collected data to a user through a device such as a phone, computer, or tablet in the form of an alert or by the user opening a web page. How this will be implemented is purely up to our team. We will take these basic specifications and put our own twist to it.




College of Computing Announces New Faculty Hires

The College of Computing is pleased to announce the hiring of six new faculty members. They will all start at Michigan Tech this fall.

Briana Bettin, Computer Science and Cognitive Learning Sciences, will teach computing education courses. Bettin’s research interests span education, experiential design, and human factors. She completed her Ph.D. at Michigan Tech this spring.

Flyer announcing faculty candidate lecture

Sidike Paheding, Applied Computing, will teach MERET courses. He comes to Michigan Tech from Purdue University Northwest. Paheding’s research interests include topics in image/video processing, machine learning, deep learning, computer vision, and remote sensing. He received his Ph.D. from University of Dayton, Ohio.

Junqiao Qiu, Computer Science, will teach compiler courses. His research interests are in programming systems and runtime support for parallel computing and scalable data processing. Qiu completed his Ph.D. at University of California Riverside this spring.

Ashraf Saleem, Applied Computing, will teach MERET courses. Saleem comes to Michigan Tech from Sultan Qaboos University, Oman. He received his Ph.D. at DeMontfort University, UK.

Leo Ureel III, Computer Science and Cognitive Learning Sciences, will teach computing education courses. Ureel’s research focuses on a constructionist approach to introductory computer science that leverages code critiquers to motivate students to learn computer programming. Ureel completed his Ph.D. at Michigan Tech this spring.

Brian Yuan, Applied Computing and Computer Science, will teach cybersecurity courses. His research interests span the fields of deep learning, machine learning, security and privacy, and cloud computing. He received his Ph.D. from University of Florida.


Online Book Buyback

The University Bookstore has arranged an Online Book Buyback event.

Two used book wholesalers, Nebraska Book Company and MBS Textbook Exchange, will buy your books.

Search for your books and compare buyback prices using the links above. The book wholesalers will provide you with a USPS label and free shipping.

If you have questions, please contact Jennifer Cowan, Textbook Manager, 906-487-2410 or campusstore@mtu.edu.


Register for Summer 2020 Classes by April 20

NEW CLASSES ADDED!

Students, for best course selection, please register by April 20.

Access the Summer 2020 full schedule of classes and start registration through the Registrar’s website: https://www.mtu.edu/registrar/.

View undergraduate class descriptions here.

Please visit with an academic advisor if you have questions about what classes to take.

NEW CLASSES ADDED!

CS 1121 | Intro to Programming I
3 Credits | 05/11-06/25 | Instructed by: TBA

CS 1122 | Intro to Programming II
0-3 Credits | 05/11-06/25 | Instructed by: Pomerville 

CS 1142 | Programming at HW/SW Interface
3 Credits | 05/11-06/25 | Instructed by: Vertanen 

CS 3331 | Concurrent Computing | NEW
3 Credits | 05/11-06/25 | Instructed by: Hiebel

CS 3411 | Systems Programming | NEW
3 Credits |Instructed by: Asilioglu

CS 3421 Computer Organization | NEW
3 Credits | Track A

CS4321 | Intro to Algorithms
05/11-06/25 | Instructed by: Zhenlin Wang (Online)

CS 4461 | Computer Networks
3 Credits | 05/11-06/25 | Instructed by: Jalooli 

CS 4710 | Model-Driven Software Development
3 Credits | 06/29-08/13 | Instructed by: Ebnenasir 

CS 4821 | Data Mining
3 Credits | 05/11-06/25 | Instructed by: Kakula 

EET 1120 | Circuits I
3 Credits | 05/11-06/25 | Instructed by: Hazaveh

EET 2233 | Electrical Machinery
4 Credits | 05/11-06/25 | Instructed by: Sergeyev 

EET 2241 | C++ and MATLAB Programming 
3 Credits | 05/11-06/25 | Instructed by: Hazaveh

EET 3373 | Intro to Prog Controllers
3 Credits | 05/11-06/25 | Instructed by: Sergeyev 

EET 4144 | Real-Time Robotics Systems
4 Credits | 05/04-05/15 | Instructed by: Sergeyev  

EET 4147 | Industrial Robotic Vision Syst
4 Credits | 06/29-08/13 | Instructed by: Sergeyev 

EET 4460 | Senior Project I
3 Credits | 05/11-08/13 | Instructed by: TBA

EET 4480 | Senior Project II
3 Credits | 05/11-08/13 | Instructed by: TBA

EET 5144 | Real-Time Robotics Systems
4 Credits | 05/04-05/15 | Instructed by: Sergeyev 

EET 5147 | Industrial Robotic Vision Syst
4 Credits | 06/29-08/13 | Instructed by: Sergeyev 

SAT 2343 | Network Administration I
4 Credits | 05/11-06/25 | Instructed by: TBA 

SAT 2511 | Microsoft System Administration
4 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 2711 | Linux System Administration
4 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 3310 | Scripting Administration & Automation
3 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 3611 | Infrastructure Service Administration
3 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 3812 | Cyber Security I
3 Credits | 05/11-06/25 | Instructed by: Cai 

SAT 3820 | Wireless System Administration
4 Credits | 05/11-06/25 | Instructed by: TBA

SAT 4480 | Senior Project I
3 Credits | 05/11-08/13 | Instructed by: TBA

SAT 4812 | Cyber Security II
3 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 4816 | Digital Forensics
3 Credits | 05/11-06/25 | Instructed by: TBA

SAT 4880 | Senior Project II
3 Credits | 05/11-08/13 | Instructed by: TBA

SAT 4996 | Big Data: Tools & Techniques
3 Credits | 06/29-08/13 | Instructed by: Tang 

SAT 5990 | Big Data: Tools & Techniques
3 Credits | 06/29-08/13 | Instructed by: Tang 

SAT 5998 | Experience in Med Informatics
3 Credits | 06/29-08/13 | Instructed by: TBA


Register for Summer 2020 Classes by April 20

NEW CLASSES ADDED!

Students, for best course selection, please register as soon as possible.

Access the Summer 2020 full schedule of classes through the Registrar’s website: https://www.mtu.edu/registrar/.

View undergraduate class descriptions here.

Please visit with an academic advisor if you have questions about what classes to take.

NEW CLASSES ADDED!

CS 1121 | Intro to Programming I
3 Credits | 05/11-06/25 | Instructed by: TBA

CS 1122 | Intro to Programming II
0-3 Credits | 05/11-06/25 | Instructed by: Pomerville 

CS 1142 | Programming at HW/SW Interface
3 Credits | 05/11-06/25 | Instructed by: Vertanen 

CS 3331 | Concurrent Computing | NEW
3 Credits | 05/11-06/25 | Instructed by: Hiebel

CS 3411 | Systems Programming | NEW
3 Credits |Instructed by: Asilioglu

CS4321 | Intro to Algorithms
05/11-06/25 | Instructed by: Zhenlin Wang (Online)

CS 4461 | Computer Networks
3 Credits | 05/11-06/25 | Instructed by: Jalooli 

CS 4710 | Model-Driven Software Development
3 Credits | 06/29-08/13 | Instructed by: Ebnenasir 

CS 4821 | Data Mining
3 Credits | 05/11-06/25 | Instructed by: Kakula 

EET 1120 | Circuits I
3 Credits | 05/11-06/25 | Instructed by: Hazaveh

EET 2233 | Electrical Machinery
4 Credits | 05/11-06/25 | Instructed by: Sergeyev 

EET 2241 | C++ and MATLAB Programming 
3 Credits | 05/11-06/25 | Instructed by: Hazaveh

EET 3373 | Intro to Prog Controllers
3 Credits | 05/11-06/25 | Instructed by: Sergeyev 

EET 4144 | Real-Time Robotics Systems
4 Credits | 05/04-05/15 | Instructed by: Sergeyev  

EET 4147 | Industrial Robotic Vision Syst
4 Credits | 06/29-08/13 | Instructed by: Sergeyev 

EET 4460 | Senior Project I
3 Credits | 05/11-08/13 | Instructed by: TBA

EET 4480 | Senior Project II
3 Credits | 05/11-08/13 | Instructed by: TBA

EET 5144 | Real-Time Robotics Systems
4 Credits | 05/04-05/15 | Instructed by: Sergeyev 

EET 5147 | Industrial Robotic Vision Syst
4 Credits | 06/29-08/13 | Instructed by: Sergeyev 

SAT 2343 | Network Administration I
4 Credits | 05/11-06/25 | Instructed by: TBA 

SAT 2511 | Microsoft System Administration
4 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 2711 | Linux System Administration
4 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 3310 | Scripting Administration & Automation
3 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 3611 | Infrastructure Service Administration
3 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 3812 | Cyber Security I
3 Credits | 05/11-06/25 | Instructed by: Cai 

SAT 3820 | Wireless System Administration
4 Credits | 05/11-06/25 | Instructed by: TBA

SAT 4480 | Senior Project I
3 Credits | 05/11-08/13 | Instructed by: TBA

SAT 4812 | Cyber Security II
3 Credits | 05/11-06/25 | Instructed by: Arney 

SAT 4816 | Digital Forensics
3 Credits | 05/11-06/25 | Instructed by: TBA

SAT 4880 | Senior Project II
3 Credits | 05/11-08/13 | Instructed by: TBA

SAT 4996 | Big Data: Tools & Techniques
3 Credits | 06/29-08/13 | Instructed by: Tang 

SAT 5990 | Big Data: Tools & Techniques
3 Credits | 06/29-08/13 | Instructed by: Tang 

SAT 5998 | Experience in Med Informatics
3 Credits | 06/29-08/13 | Instructed by: TBA


Faculty Candidate Lecture: Sidike Paheding

Flyer announcing faculty candidate lecture

The College of Computing’s Department of Applied Computing invites the campus community to lecture by MERET faculty candidate Dr. Sidike Paheding, Friday, April 10, 2020, at 3:30 p.m., via an online Zoom meeting. The title of Paheding’s lecture is, “Machine Learning in Multiscale and Multimodal Remote Sensing: From Ground to UAV with a stop at Satellite through Different Sensors.”

Link to the Zoom meeting here.

Paheding is currently a visiting assistant professor in the ECE department at Purdue University Northwest. His research interests cover a variety of topics in image/video processing, machine learning, deep learning, computer vision, and remote sensing.

 Abstract: Remote sensing data provide timely, non-destructive, instantaneous estimates of the earth’s surface over a large area, and has been accepted as a valuable tool for agriculture, weather, forestry, defense, biodiversity, etc. In recent years, machine learning for remote sensing has gained significant momentum due to advances in algorithm development, computing power, sensor systems, and data availability.

In his talk, Paheding will discuss the potential applications of machine learning in remote sensing from the aspects of different scales and modalities. Research topics such as multimodal data fusion and machine learning for yield prediction, plant phenotyping, augmented reality and heterogeneous agricultural landscape mapping will be covered.

Paheding earned his M.S. and Ph.D. degrees in electrical engineering at the University of South Alabama, Mobile, and University of Dayton, Ohio, respectively. He was a postdoctoral research associate and and assistant research professor in the Remote Sensing Lab at Saint Louis University from 2017 to 2019, prior to joining Purdue University Northwest.

He has advised students at the undergraduate, master’s, and doctoral levels, and authored or co-authored close to 100 research articles, including in several top peer-review journal papers.

He is an associate editor of the Springer journal Signal, Image, and Video Processing, a guest editor/reviewer for a number of reputed journals, and he has served on international conference committees. He is an invited member of Tau Beta Pi (Engineering Honor Society). 


Faculty Candidate Saleem Ashraf

The College of Computing Department of Applied Computing invites the campus community to a lecture by faculty candidate Saleem Ashraf on, April 7, 2020, at p.m., via an online Zoom meeting.

Dr. Ashraf is currently an assistant professor of mechatronics engineering in the ECE department at Sultan Qaboos University, Oman. He received his Ph.D. and MSc. degrees in mechatronics engineering from DeMontfort University, UK, in 2006 and 2003, respectively, and his BSc. in electrical and computer engineering from Philadelphia University, Pa., in 2000.

Ashraf’s research interests are unified under the theme, “developing real-time smart controllers for different engineering systems,” and his research investigates electromechanical, electro-pneumatic, and piezoelectric based systems. 

Advancements in field of unmanned vehicle system, artificial intelligence, and computer vision have empowered the integration of solutions that would potentially automate many processes. 

Ashraf’s seminar presents his research experience in the field of smart and vision-based unmanned vehicle systems, and how this technology has been employed to solve real-life problems in Oman.

The talk will present a selection of Ashraf’s fundamental research work focused on the modeling and control of long-stroke piezoelectric actuators, which are being used widely in micro positioning systems. He will also share his experience in the establishment of the “Embedded & Interconnected Vision Systems” (EIVS) lab. 

The second part of Ashraf’s talk will cover his teaching experience, including philosophy, courses, new courses, extracurricular activities, and practical projects. He will present his methodology in supervising multi-disciplinary final year projects with some examples of completed projects. Finally, Ashraf will discuss his ideas about how he can contribute to the Michigan Tech curriculum at all levels, undergraduate and graduate.

Ashraf has been awarded external research grants totaling more than $450K, and three internal grants totaling $58K; he attributes his success in this regard to his development of excellent relations with local industry and the Omani research council (TRC). The common aim of these research projects is to develop vision-based unmanned vehicles to solve real life problems such as oil spill in seawater. 

He has published more than 45 peer-reviewed papers in reputable journals and at international conferences. He is one of the founders of the “Embedded & Interconnected Vision Systems” (EIVS) lab at Sultan Qaboos University, which was inaugurated this March and funded by BP Oman. The lab hosts equipment for Embedded Vision Systems, Artificial Intelligence (UVS / Robotics), and IoT.


Faculty Candidate Muhammad Fahad to Present Lecture April 9

The College of Computing’s Department of Applied Computing invites the campus community to a lecture by MERET faculty candidate Muhammad Fahad on Thursday, April 9, 2020, at 3:30 p.m., via an online Zoom meeting. His talk is titled, “Motion Planning and Control of Autonomous Mobile using Model Free Method.”

Link to the Zoom meeting here.

Dr. Fahad currently works as a robotics engineer at National Oil Well Varco. He received his M.S. and Ph.D. in electrical engineering from Stevens Institute of Technology, Hoboken, NJ, and his B.S in EE at University of Engineering and Technology, Lahore, Pakistan.

Fahad has extensive experience designing control and automation systems for the process industry using traditional control methods and robots. His research interests include cooperative distributed localization, human robot interaction (HRI), deep reinforcement learning (DRL), deep inverse reinforcement learning (DIRL) and generative adversarial imitation learning (GAIL), simulation tools design, parallel simulation frameworks and multi-agent learning.

Lecture Abstract. Robots are playing an increasingly important part in our daily lives. This increasing involvement of robots in our everyday lives has highlighted the importance of human-robot interaction, specifically, robot navigation of environments occupied by humans, such as offices, malls and airports. Navigation in complex environments is an important research topic in robotics.

The human motion model consists of several complex behaviors that are difficult to capture using analytical models. Existing analytical models, such as the social force model, although commonly used, are unable to generate realistic human motion and do not fully capture behaviors exhibited by humans. These models are also dependent on various parameters that are required to be identified and customized for each new simulation environment. 

Artificial intelligence has received booming research interest in recent years. Solving problems that are easy for people to perform but difficult to describe formally is one of the main challenges for artificial intelligence. The human navigation problem falls directly in this category, where it is hard to define a universal set of rules to navigate in an environment with other humans and static obstacles.

Reinforcement learning has been used to learn model-free navigation, but it requires a reward function that captures the behaviors intended to be inculcated in the learned navigation policy. Designing such a reward function for human like navigation is not possible due to complex nature of human navigation behaviors. The speaker proposes to use measured human trajectories to learn both the reward function and navigation policy that drives the human behavior.

Using a database of real-world human trajectories–collected over a period of 90 days inside a mall–we have developed a deep inverse reinforcement learning approach that learns the reward function capturing human motion behaviors. Further, this dataset was visualized in a robot simulator to generate 3D sensor measurement using a simulated LIDAR sensor onboard the robot. A generative adversarial imitation learning based method is developed to learn the human navigation policy using these human trajectories as expert demonstration. The learned navigation policy is shown to be able to replicate human trajectories both quantitatively, for similarity in traversed trajectories, and qualitatively, in the ability to capture complex human navigation behaviors. These navigation behaviors include leader follower behavior, collision avoidance behavior, and group behavior.