Summary
George Mason University’s data analytics engineering programs at Volgenau prepare students for their future careers in a growing discipline.
All of our programs are taught by our industry-leading faculty members across schools and colleges in Mason, giving our students the ability to see the numerous possibilities a data-driven degree can offer.
- Master of Science –– The MS in data analytics engineering is a multidisciplinary degree program at the Volgenau School of Engineering. It provides students with an understanding of the technologies and methodologies necessary for data-driven decision-making.
- Certificate –– The graduate certificate in data analytics engineering gives students a foundation of basic data analytics and data science principles.
- Master of Science Online –– The online MS program gives students the flexibility to earn an advanced degree and expand their knowledge in data analytics in an asynchronous format.
- Certificate Online –– The online graduate certificate in data analytics engineering gives students a foundation of basic data analytics and data science principles with the flexibility of an online asynchronous format.
Data analytics engineering is an expanding field. Therefore, all our programs instruct students on current and innovative tools and prepare them to be adaptable to the future of the field.
Source: GMU
Mason_GAPSA – 22/02/2024 (01:02)
GAPSA’s Mason GradEchoes had the pleasure of interviewing Akash Manjunath Tulahalli, a master’s student majoring in Data Analytics Engineering at George Mason University. Originally from Bengaluru, India, Akash embarked on a journey to pursue his dream of studying in the USA. Now, on his 190th day in the country, he is documenting his experience through daily vlogs on his YouTube channel (https://www.youtube.com/@gotechakash?…. For Akash, coming to GMU and studying data analytics engineering is more than just an academic pursuit – it’s a dream come true. He expresses gratitude for the support he receives from his friends, family, and the broader community back in India, who have cheered him on every step of the way. At GMU, Akash finds himself immersed in a vibrant academic environment supported by a dedicated faculty and a diverse community of fellow students. He speaks highly of the Data Analytics Engineering program, emphasizing its comprehensive curriculum and the invaluable guidance and resources provided by professors and peers alike.
But Akash’s aspirations go beyond the classroom. He is passionate about leveraging his skills to make a positive impact and is committed to building a strong community centered around data-driven insights. Through his YouTube channel, he aims to engage and educate others, sharing his journey and inspiring fellow students to pursue their dreams.
OnAir Post: DAEN – Data Analytics Engineering @GMU
News
Mason News, – January 17, 2025
Tim McAliley has navigated a successful career in IT by staying agile and embracing continuous learning. Now, he’s teaching a course at George Mason University to connect data analytics engineering students with challenges set forth by local technology companies, facilitating their professional development alongside their academic growth.
McAliley’s journey from the Marine Corps to academia is a testament to his diverse experiences and dedication to continuous learning. Currently an adjunct professor at George Mason University, McAliley teaches a graduate capstone course in the Master’s in Data Analytics Engineering program, where his extensive real-world experience significantly enhances his teaching.
McAliley’s career began in the Marine Corps before he earned a degree in political science and military science from Florida State University (FSU), graduating in December 1994. In 1999, he transitioned into the information technology (IT) field, earning his Microsoft Certified Systems Engineer certification while working at FSU’s Center for Academic and Professional Development. This certification marked the beginning of a successful career in IT, which included roles in enterprise file storage, network printing, and cloud solutions. Since 2012, he has worked at Microsoft as a cloud solution architect. His role involves various aspects of cloud deployments, including Azure and hybrid solutions.
In addition to his professional career, McAliley has continued to pursue academic success, earning a master’s degree in information management systems from Harvard Extension School in 2023 and enrolling in George Mason’s Information Technology doctoral program this spring. He began teaching the data analytics engineering graduate capstone course in fall 2024. Balancing his full-time job at Microsoft, his teaching responsibilities, and his doctoral studies is no small feat, but McAliley approaches it with the same determination that has characterized his entire career.
Earlier this week, students from George Mason University’s data analytics engineering program competed in the 2023 FAA Data Challenge Forum, using AI strategies to navigate air travel solutions and improvements.
Led by advisor Isaac Gang, associate professor in Mason’s College of Engineering and Computing (CEC), the team tied second place alongside Duke University for their proposal called Modernized Flight Risk Assessment Tool for General Aviation Pre-Flight Planning.
“Congratulations to the Mason data analytics engineering program student team – Hunter Walden, Kathleen Hill, Chi Quinn, Erick Torres – and their advisor Dr. Isaac Gang for being one of 10 finalists selected to compete for the $25,000 top prize in the 2023 FAA Data Challenge Forum,” said Bernard Schmidt, acting director of the MS data analytics engineering program within CEC.
The FAA Data Challenge focuses on the use of AI/Machine Learning and advanced analytics to address aviation-related problems and opportunities. The challenge provides an opportunity for university students to be involved in FAA’s mission, and offer creative, unique solutions for current and future challenges and serve as a pathway for students to become future transportation leaders.
The challenge this year was held at the MITRE campus in McLean, Va.
About
A Message From the Director
Hi, my name is Jim Baldo, and I am the director of the George Mason University College of Engineering and Computing Data Analytics Engineering Program (DAEN). Our multidisciplinary program provides its students with knowledge and experience across a broad range of data analytics methods, tools, and processes, and focuses on a flexible and broad set of courses intended to prepare our graduates to solve a wide range of real-world problems.
In the area of data analytics methods, the DAEN program targets a foundation of existing algorithms that have widespread applications in both research and industry as well as emerging algorithms that have recently been introduced. Students study algorithms to acquire an understanding of the algorithm and how to use the algorithm on real-world problems. This insight enables our students to select the correct algorithm(s) for the specific problem.
The DAEN program exposes its students to both state-of-the-art and state-of-the-practice tools. These tools available to our students are either commercial or open-source and range from programming language libraries to commercial cloud-based data science workbenches.
Our faculty have many years of industry experience as practicing data analysts/engineers and most of the faculty are currently engaged as data analytics practitioners. Since it is a multidisciplinary program, the merging of multiple disciplines can be leveraged for innovative problem-solving. This unique combination provides an innovation engine that supports a rich learning experience.
Our experienced faculty also prepare students to work on problems in a team environment. Most data analytics teams today are extremely diverse to knowledge, skills, and team members, and we prioritize teaching our students how to work together quickly towards a solution.
Like the current data analytics industry, our student population is diverse with respect to degrees (undergraduate and graduate), nationalities, and culture. Data analytics problem solving is performed in diverse teams that are necessary to drive both innovative solutions and enable teams the freedom to apply creativity to problem-solving.
Near the end of their studies, all students participate in capstone projects that are increasingly based on industry partner projects that enable students to work on problems as a team. This provides students with a realistic experience of the working environments they will be practicing in after graduation and enable students to apply for data analytics positions with confidence.
The program provides all students with the ability to create a plan of study that is flexible enough to cater to their unique career goals and objectives.
I encourage you to review our program and feel free to contact me or any of our DAEN faculty and staff for additional information about the program.
Best,
Jim Baldo
Director, Data Analytics Engineering
Associate Professor
Source: DAEN website
Contact
Email: School
Locations
Fairfax Campus
Phone: 703-993-6269
Web Links
Faculty
James Baldo
Associate Professor, Director of MS in Data Analytics Engineering at George Mason University
James Baldo’s engineering career has provided him with a broad foundation of knowledge and experience in engineering systems responsible for detecting, identifying, tracking, and predicting the behavior of objects based on multiple sources of data. The environment that Baldo works in has been greatly affected by big data which has resulted in utilizing new technologies and analytical methods. Baldo’s engineering team leadership skills have been instrumental in interacting with business owner needs and expectations as well as managing, galvanizing, and synergizing teams of talented engineers.
Baldo’s experience as a practicing engineer has provided him with a great appreciation for educating engineers with a solid foundation in mathematics, science, statistics, and engineering. As an instructor Baldo packages theory and practice in his courses to prepare students for addressing real-world problems.
OnAir Post: James Baldo
Bernard Schmidt
Instructor, Assistant Director MS Data Analytics Engineering Program
Bernard Schmidt is an Instructor at George Mason University’s College of Engineering and Computing, Data Analytics Engineering master’s program. He is also the Assistant Director of the MS Data Analytics Engineering Program. He joined Mason’s CEC Faculty in the Fall of 2020 from Northern Virginia Community College where he served as a professor of Information Technology as well as an Assistant Dean for Information Technology and Computer Science at the NVCC Manassas campus.
OnAir Post: Bernard Schmidt
Isaac Gang
Isaac Gang is an Associate Professor in the College of Engineering and Computing, MS Data Analytics Program at George Mason University. He joined the CEC faculty in the Fall of 2020 from Texas A&M University-Commerce where he served as an assistant professor of computer science as well as the department’s outreach coordinator. Before coming to TAMUC, Gang was an assistant professor of computer science and engineering at the University of Mary Hardin-Baylor and an adjunct professor of computer science at the University of Southern Mississippi’s School of Computing before joining UMHB. His current and primary teaching responsibilities at Mason largely involves data analytics graduate capstones and a mix of computer science and applied information technology courses.
Gang is a former DOE grant winner, president, and board member of the Association of Computer Educators in Texas (ACET), Industry Advisory Board (IAB) coordinator, and the director of CS for all. His primary research agenda involves big data/analytics, cybersecurity (ransomware and steganography), and image/signal processing.
OnAir Post: Isaac Gang
Data Analytics Research Projects
A collection of research projects lead by Dr. Isaac Gang at George Mason University Volgenau School of Engineering
Data Governance
Source: DAEN webpage
Comprehensive guide on the application of Data Governance strategies in an organization.
Data Bias
Analysis the current state-of-the-art and two use-cases demonstrating bias and bias-free Machine Learning models.
ML/OPS
Research into ML/OPS developemnt, testing, production, deployement, and team skills
