Aristotelis Sigiouan Leventidis
Education
- BS in Physics, University of Michigan, Ann Arbor
- BS in Computer Science, University of Michigan, Ann Arbor
About Me
- Hometown: Thessaloniki, Greece
- Field of Study: Computer Science
- PhD Advisors: Mirek Riedewald & Cody Dunne
Biography
Aristotelis Sigiouan Leventidis is a PhD student at Northeastern studying Data Science and Data Visualization, advised by Professors Mirek Riedwald and Cody Dunne. He has a BS in Physics and Computer Science from the University of Michigan, Ann Arbor. He is interested in using novel techniques to mine large data sets and develop anomaly detection methods, as well as developing data visualization methods to make said data more understandable; he is also excited by the interdisciplinary work that comes with mining real-world data.
What are the specifics of your graduate education (thus far)?
I am an incoming 1st year PhD student that will be under the supervision of Professor Mirek Riedewald in the Data Lab and Professor Cody Dunne in the Data Visualization group.
What are your research interests?
My research interests lie in the intersection of developing novel methods to mine large datasets and constructing appropriate visualization methods to help understand them. During my undergraduate research experience, I realized that making sense of large, highly dimensional datasets can be very challenging without proper visualization, which led me to also want to explore visualization techniques for large datasets.
What’s one problem you’d like to solve with your research/work?
I would like to develop efficient anomaly detection methods for a variety of datasets such as social networks and brain scans. With these methods I want to construct an application that can aid field experts to quickly pinpoint unusual data in their large datasets.
What aspect of what you do is most interesting?
One interesting aspect of doing research in data mining is the large variety of researchers I could collaborate with. When analyzing brain scan data we collaborate with medical researchers, when analyzing social network data we collaborate with social scientists and network scientists. Collaborating with researchers from different fields broadens my knowledge of other fields and exposes me to new ways of conducting research.
What are your research or career goals, going forward?
Currently I am focused on learning more about my field and producing high quality research. In the future I would like to continue doing research either in academia or in industry.
Where did you grow up or spend your most defining years?
I grew up in Greece. I went to the University of Michigan for my undergraduate studies.
Education
- BS in Physics, University of Michigan, Ann Arbor
- BS in Computer Science, University of Michigan, Ann Arbor
About Me
- Hometown: Thessaloniki, Greece
- Field of Study: Computer Science
- PhD Advisors: Mirek Riedewald & Cody Dunne
Biography
Aristotelis Sigiouan Leventidis is a PhD student at Northeastern studying Data Science and Data Visualization, advised by Professors Mirek Riedwald and Cody Dunne. He has a BS in Physics and Computer Science from the University of Michigan, Ann Arbor. He is interested in using novel techniques to mine large data sets and develop anomaly detection methods, as well as developing data visualization methods to make said data more understandable; he is also excited by the interdisciplinary work that comes with mining real-world data.
What are the specifics of your graduate education (thus far)?
I am an incoming 1st year PhD student that will be under the supervision of Professor Mirek Riedewald in the Data Lab and Professor Cody Dunne in the Data Visualization group.
What are your research interests?
My research interests lie in the intersection of developing novel methods to mine large datasets and constructing appropriate visualization methods to help understand them. During my undergraduate research experience, I realized that making sense of large, highly dimensional datasets can be very challenging without proper visualization, which led me to also want to explore visualization techniques for large datasets.
What’s one problem you’d like to solve with your research/work?
I would like to develop efficient anomaly detection methods for a variety of datasets such as social networks and brain scans. With these methods I want to construct an application that can aid field experts to quickly pinpoint unusual data in their large datasets.
What aspect of what you do is most interesting?
One interesting aspect of doing research in data mining is the large variety of researchers I could collaborate with. When analyzing brain scan data we collaborate with medical researchers, when analyzing social network data we collaborate with social scientists and network scientists. Collaborating with researchers from different fields broadens my knowledge of other fields and exposes me to new ways of conducting research.
What are your research or career goals, going forward?
Currently I am focused on learning more about my field and producing high quality research. In the future I would like to continue doing research either in academia or in industry.
Where did you grow up or spend your most defining years?
I grew up in Greece. I went to the University of Michigan for my undergraduate studies.