2 Month Sublet (June, July)

Name: Manogna Rayasam

Pronouns: She/Her

Semester of Internship: Fall 2025

Major: Data Science

Current Class Level: Masters Student

This semester I completed a(n)...: Internship

Internship, Co-op, or Research Site (Company/Organization Name): UMBC Career Center

Location of the Organization (City, State): Baltimore County

Title of position: Data Visualization & Reporting Analyst

Tell us about your internship, co-op, or research opportunity, including your day-to-day responsibilities:

In my internship as a Data Visualization & Reporting Analyst with UMBC's Career Center, I work closely with student data to support decision-making and improve the visibility of student career outcomes. My day-to-day responsibilities include analyzing career outcomes data, preparing accurate metrics for the center's outreach materials, and assisting in the migration of reporting processes. I also build interactive Tableau dashboards that help staff easily understand trends, employer engagement through Handshake, and overall student success after graduation. Through this role, I've been able to combine data analysis with visualization to create tools that make a meaningful impact across campus.

Describe the process of obtaining your position. When did you hear of the position and submit your application?

I learned about this position through Handshake and quickly submitted my application because the role aligned well with my interests in data analysis and visualization. In addition to applying online, I reached out to Christine Routzahn with a cold email to express my enthusiasm for the position and to learn more about the opportunity. Shortly after, I was invited for an interview. The interview went well, and I was selected for the role, giving me the opportunity to join the team this semester.

What resources did you use to find your current experience?

UMBC Career Center, Handshake

What have you enjoyed the most about your position and organization?

What I've enjoyed most about my position is the strong guidance and mentorship I receive, especially from Christine Routzahn. Her clear expectations and weekly task planning help me stay organized and confident in my work. I also appreciate the flexibility within the role, which allows me to approach tasks in an innovative and unique way while still having support whenever needed. This combination of structure, clarity, and creative freedom has made the experience both meaningful and motivating.

How do you believe you have made an impact through your work?

I believe I've made a meaningful impact through my work by transforming complex career outcomes data into clear, accessible insights that support decision-making across campus. The Tableau dashboards I created help staff quickly understand trends, employer engagement, and student success, enabling them to better communicate UMBC's career outcomes. I've also contributed to improving reporting processes and ensuring accurate data for flyers and outreach materials. By combining analysis with effective visualization, I've helped the Career Center present information in a way that is both actionable and easy to interpret.

What advice would you give to another student who is seeking an internship or similar experience?

My advice to another student seeking an internship is to be proactive and intentional throughout the process. Most importantly, stay confident and open to feedback. Opportunities often come to those who take initiative, show curiosity, and aren't afraid to put themselves out there.

Please provide a short reflection or quote about what you liked most about your position / earning internship credit / working with the Career Center.

The Career Center guided me at every step, helping me grow both technically and professionally.

UMBC has been designated as one of only three institutions in Maryland dually recognized with Carnegie R1 status—among the top 5 percent of research universities in the nation—and the Carnegie Community Engagement classification, which recognizes universities who systematically share knowledge and resources with those of the public and private sectors to enrich scholarship, research, and creative activity in order to contribute to the public good. Following an extensive full campus self-study demonstrating increased depth, breadth, and integration of engagement, this week UMBC was classified as a Carnegie Community Engaged Campus for a second six-year period.

“As a public university for the public good, community engagement is at the heart of UMBC’s mission to provide world class education and research that directly supports our students, community, and partners in an inclusive environment,” says Provost Manfred H. M. van Dulmen. “The Carnegie Community Engagement Classification is an acknowledgement of the dedication and excellent work of the UMBC faculty, staff, and students to engage and serve the city of Baltimore and the state of Maryland.”

Community engagement at UMBC flows from the university’s vision of a culture of inclusive excellence, explains Joby Taylor, Ph.D. ’05, assistant vice provost and co-leader of The Shriver Center for Public Service and Community Engagement. Taylor and Preminda Jacob, associate dean of the College of Arts, Humanities, and Social Sciences, co-chaired the reclassification study with the conviction that: “Community engagement extends our vision and practice of an inclusive culture out into the world beyond our campus through relationships and partnerships focused on mutual collaborations that matter and make a difference…locally, regionally, and globally.”

This community engagement classification re-affirms UMBC as a place where people and relationships are centered. At a time when the impact of higher education is in question, UMBC’s commitment to inclusive excellence as seen through this reclassification offers a powerful counter narrative about the roles of universities in a critically important moment. 

“It speaks to how learning and knowledge can be transformational, not just transactional,” says Taylor, noting his belief that higher ed can be oriented toward positive social change, supporting holistic and lifelong learning with civic purposes, as well as professional pathways and economic mobility. 

President Valerie Sheares Ashby echoes these sentiments, noting during the self-study that, “At UMBC, we do not just talk about equity and social justice, we make it happen in real, tangible ways that improve people’s everyday lives.”

Dr. Chein-I Chang, professor of computer science and electrical engineering at UMBC, will publish his fifth book on hyperspectral imaging in early 2026.

The book is the first of its kind in deriving a unified statistical treatment of hyperspectral target and anomaly detection from signal and image processing perspectives. It goes from the early detection-theory chapters through the matrix-decomposition methods, effective anomaly space-based anomaly detection, and concludes applications of statistical detection theory to hyperspectral image classification at the end. The entire book centers main concepts of hypothesis testing, signal-to-noise ratio, target detectability, background suppression to provide coherent chapters which can be closely related to one another. It is quite different from many other existing hyperspectral or statistical signal-processing texts in the sense that it offers readers who care about a rigorous, detection-theoretic treatment and want to see a coherent research line developed in the book with great details. Moreover, it is unusually strong in building a unified statistical framework for hyperspectral target and anomaly detection and hyperspectral image classification and further develops a broad spectrum of various methods inside the framework.

The book is organized by five parts made up of 21 chapters and 5 appendices starting from hypothesis testing-based detection theory and matrix decompositions followed by a progression from hyperspectral target detection, hyperspectral anomaly detection and hyperspectral image classification. 

 Chein-I Chang received the Ph.D. degree in electrical engineering from the University of Maryland, College Park, USA. Dr. Chang is currently a professor with the University of Maryland, Baltimore County (UMBC). He has been a Chang Jiang Scholar Chair Professor awarded by Ministry of Education, China since 2016 and also a Yushan Scholar Chair Professor awarded by Ministry of Education, Taiwan at National Cheng Kung University from 2022-2028, a Life-time Chair Professor of National Yang Ming Chiao Tung University, Hsinchu, Taiwan since 2025. Dr. Chang has been also the director of Center for Hyperspectral Imaging in Remote Sensing (CHIRS) at Dalian Maritime University, Dalian, China since 2016.

Dr. Chang authored four books, Hyperspectral Imaging: Techniques for Spectral Detection and Classification published by Kluwer Academic Publishers, 2003, Hyperspectral Data Processing: Algorithm Design and Analysis, John Wiley & Sons, 2013, Real Time Progressive Hyperspectral Image Processing: Endmember Finding and Anomaly Detection published by Springer, 2016, Recursive Hyperspectral Sample and Band Processing: Algorithm Architecture and Implementation, published by Springer, 2017. In addition, Dr. Chang also edited three books, Recent Advances in Hyperspectral Signal and Image Processing published by Trivandrum, Kerala, India, 2006, Hyperspectral Data Exploitation: Theory and Applications, published by John Wiley & Sons, 2007, Advances in Hyperspectral Image Processing Techniques, published by Wiley, 2023. Besides, he also co-edited with A. Plaza a book on High Performance Computing in Remote Sensing, published by CRC Press, 2007 and two special issue books from MDPI.

Dr. Chang is a Life Fellow, (Institute of Electrical and Electronics Engineers), a Fellow of SPIE (Society for Photo-optical Instrumentation Engineers) and a Fellow of AAIA (Asia-Pacific Artificial Intelligence Association). He is currently serving as associate editor of Remote Sensing and IEEE Transaction on Geoscience and Remote Sensing.