New Data X Faculty / 2016-2017 Academic Year

Data X faculty member, Eric Baumer

Eric Baumer, Assistant Professor, Department of Computer Science and Engineering
Secondary Department / Program: Journalism and Communication
Start Date: January 2, 2017

Eric P. S. Baumer earned his doctorate and master’s in information and computer sciences at the University of California, Irvine and his bachelors in computer science at the University of Central Florida. Before coming to Lehigh, Baumer served as a research associate at Cornell University and an assistant project scientist at the University of California, Irvine. He has presented his work at numerous conferences and published in ACM CHI Conference, New Media and Society, and the Journal of Information Technology and Politics.

WHY LEHIGH?

There were several things that attracted me to Lehigh--the moderate size, the world-class engineering college, the collegiality among faculty, the greater Lehigh Valley area I-but the main one was the balance of valuing both research and teaching. My work is largely in the area of human-computer interaction (HCI), which deals with the relationships among technology and people. My interests include how technology designers build, and how lay persons interpret, systems based on complex computational data analysis. While it may sound esoteric, these systems are both myriad and pervasive. Everything from your spam filter in your email, to Google's web search, to Facebook's news feed curation, to Netflix's or Amazon's recommendation systems fall into this class of systems. Data X provides a perfect environment to pursue such questions around both the implementation and the interpretation of such technologies.

HOW DOES DATA X MESH WITH YOUR VIEWS ON TEACHING AND RESEARCH?

While my work pushes the boundaries of what we can accomplish in HCI, it's also important to me, both professionally and personally, to share that experience with others. Teaching such courses CSE 252, titled Computers, the Internet, and Society, will allow me to share cutting edge research and perspectives on the social effects of technology with hundreds of students. In addition to teaching lectures and seminars, my work has involved collaboration with numerous students, including at the PhD, Masters, and Bachelors. I count these among some of my most rewarding experiences, and they were ultimately a deciding factor in my choice to pursue a career in academia. CSE's and Lehigh's strength come from valuing not only these activities individually -- research and teaching -- but also their synthesis.

Data X faculty member, Haiyan Jia

Haiyan Jia, Assistant Professor, Department of Journalism and Communication
Secondary Department / Program: Computer Science and Engineering
Start Date: August 15, 2016

Haiyan Jia earned her doctorate in mass communications at the Pennsylvania State University, and bachelor’s in atmospheric sciences at Peking University in China. Before joining Lehigh’s Data X Digital Media faculty, Jia served as a post-doctoral scholar at Penn State. Her research is primarily focused on the psychological and social effects of information and communication technology, ranging from social media to the Internet of Things. Jia has published her work in Communication Research, Human-Computer Interaction, and in numerous conference proceedings publications.

WHY LEHIGH?

Many reasons draw me to Lehigh, among which two stand out, including the specific position that will enable me to draw upon my research expertise, my passion for teaching, and my dedication to service, as well as the kindest and warmest people.

My position, at the conjunction of Journalism and Data X, fits my research interests perfectly and allows me to extend my interdisciplinary work. Lehigh is especially well known for its undergraduate education, and therefore has a culture of emphasizing teaching while valuing research. I also find it extremely exciting to be involved in the process of shaping what the Data X initiative evolves into, including the collaboration in cross-domain research, the development of new curriculum, and the development of new spaces for research and teaching.

More importantly, I fall in love with the people I met during my campus visit. The students at Lehigh are very driven and intelligent; I enjoy challenging them and being challenged in classroom. The faculty and staff members that I encountered are all very welcoming and friendly; in particular, the Department of Journalism and Communication made me feel immediately at home. They are supportive and caring for their colleagues, and strongly adhere to the work/life balance of its faculty.

WHAT MAKES YOU A GOOD FIT WITH LEHIGH’S DATA X INITIATIVE?

My research and teaching in data journalism is a perfect fit with Data X, as I am interested in finding effective ways of integrating data into news storytelling and for engaging and informing the readers. Journalism is one of the fields that increasingly utilize data for insight discovery. The Data X initiative identifies this emerging trend and puts Lehigh in a leadership role in developing research programs and new pedagogical approaches in the subfield of data journalism. One example of this effort that I am very excited about is the development of a state-of-art Digital Media Lab, which will serve as a collaborative space for research and teaching related to Data X.

Data X also offers extraordinary opportunities for interdisciplinary research that is aimed at pushing boundaries and enhancing innovation. The Colleges and Departments directly involved in the Data X initiative provide an organic network that support such collaboration; more broadly, the Data X initiative attracts faculty members in different disciplines and fields at Lehigh and bring awareness to the unlimited potentials of involving data in the most cutting-edge research. So far, I have been having the privilege of being involved in different research groups and developing research projects with scholars with different research backgrounds. This kind of collaboration is made possible by Data X to take place so quickly and so smoothly.

Data X faculty member, Sihong Xie

Sihong Xie, Assistant Professor, Department of Computer Science and Engineering
Secondary Department / Program: Marketing
Start Date: August 15, 2016

Sihong Xie (Computer Science and Engineering/Marketing) earned a doctorate in computer science at the University of Illinois at Chicago and a masters and bachelors in software engineering at Sun Yat-Sen University, China. Before joining Lehigh’s faculty Xie served as a research assistant at the University of Illinois at Chicago. Xie’s research emphasizes models and algorithms addressing challenges in big data, such as multiple data source aggregation, human-in-the-loop data mining and trustworthiness. He has published his work in ACM SIGKDD, WWW, IEEE ICDM, etc.

WHY LEHIGH?

I chose Lehigh to start my academic career is its prestige, well-rounded students and the rich interactions among faculty members from a broad range of disciplines.

WHAT ARE YOUR RESEARCH INTERESTS?

My research area is data mining, which is multi-disciplinary area with connection to business, psychology and health care. I analyze signals in many different formats emitting from these disciplines, and provide insights from the data to the experts. I am teaching text mining, a course that train computer to understand natural language that can be found in many areas outside computer science, such as criminology, business and healthcare. Data X has identified these dynamic interactions, and is recruiting many faculty members across departments to encourage more in-depth collaborations. I believe that my research and teaching will extremely fruitful under the initiative.

Data X faculty member, Rebecca Wang

Rebecca Jen-Hui Wang, Assistant Professor, Department of Marketing
Secondary Department / Program: Computer Science and Engineering
Start Date: August 15, 2016

Rebecca Jen-Hui Wang (Marketing) earned her doctorate in management at Northwestern University, her master’s in engineering management and bachelor’s in engineering sciences/electrical engineering from Dartmouth College. Before coming to Lehigh, Wang was a data engineer at Connance, Inc. in Waltham Massachusetts. Her research interests include mobile and digital marketing, customer relationship management, social media and technology and causal inference methods. She has published her work in the Journal of Retailing, Journal of Interactive Marketing, Computers in Human Behavior and The New Advertising: Branding, Content, and Consumer Relationships in the Data-Driven Social Media Era.

WHY LEHIGH?

When I visited Lehigh, I was impressed with the traditions and collegiality that the tight-knit community had to offer. I also enjoyed meeting with some of the students, who showed high levels of maturity and career-oriented focus during our conversations. Additionally, what set Lehigh apart from the other schools that had invited me to visit their campuses was the Data X Initiative. Before my doctoral studies, I worked in consulting and healthcare IT and applied engineering methods to business problems. As such, I greatly valued interdisciplinary approaches to problem solving, which Data X seemed to encourage and even help nurture. My department chair David Griffith and Data X CS faculty members Dan Lopresti and Brian Davison also shared their passion and visions, which felt like a great match with my research and teaching interests as well as professional development aspirations.

HOW DOES DATA X MESH WITH YOUR VIEWS ON TEACHING AND RESEARCH?

With respect to research, I look forward to collaborating with and learning from other faculty members across a variety of departments. I also hope that Data X becomes the institution an alum or a company comes to if they need help with data analytics or business problem-solving, as this type of collaboration can be a win-win opportunity for both the organization and our university. The up-and-coming facilities at Mountaintop should provide ample potential for doing research on Internet of Things, technology impact, innovation management, customer engagement, and digital marketing. With respect to teaching, because deriving insights from data has become such a critical component in today’s business environment, offering a curriculum that combines consumer theory and quantitative analysis should be beneficial to our students (e.g., the Business Analytics Certificate program created by Nevena Koukova from my department and Catherine Ridings from Management). One of Data X’s goals is to help students develop data-oriented mindset and skill set in preparation for their careers, and I am excited to be a part of that team and discussion.

Data X faculty member, Maiomaio-Zhang

Miaomiao Zhang, Assistant Professor, Computer Science and Engineering
Start Date: August 15, 2017

Miaomiao Zhang is currently a postdoctoral associate in Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. She completed her PhD in the Computer Science Department at University of Utah. Her research work focuses on developing novel models at the intersection of statistics, mathematics, and computer engineering in the field of medical and biological imaging. she received the Young Scientist Award at the 2014 Medical Image Computing and Computer-Assisted Intervention (MICCAI). She will be joining Lehigh's Department of Computer Science and Engineering in the Fall of 2017.

WHY LEHIGH?

Lehigh University engages a wide variety of excellent research and teaching activities. It is a place where I can conduct my own research with students and contribute to the computer engineering education.

WHAT MAKES YOU A GOOD FIT WITH THE DATA X INITIATIVE?

Since my research goal is to develop novel methods in interdisciplinary areas at the intersection of statistics, mathematics and computer engineering in the field of medical and biological imaging, the DataX initiative provides numerous potential opportunities to collaborate with researchers from other multiple related fields. Meanwhile, advising students studying and working across all disciplines is challenging but also more exciting!