Assistant Professor
Computer Science, SUNY Binghamton
Email: aseethar@binghamton.edu
Office: Engineering Building, N-06
Phone: 607-777-4722

I am an assistant professor in the Computer Science Department at SUNY Binghamton. I obtained my PhD. from University of Massachusetts Amherst. My research encompasses the fields of computer networks, wireless networks, ubiquitous computing, cyber-physical systems and data science. I direct the Future InterNet Design Lab (FIND) at SUNY Binghamton.

Together with Prof. Arti Ramesh , I have started CSEdu4All.org , an educational initiative whose aim is to make computer science education accessible to people (i.e., students, professionals, computer science enthusiasts) around the world. We believe that everyone has the right to good education, and geographical and political boundaries should not be a barrier to obtaining knowledge and information. To ensure that students around the world have access to high quality educational content, all content available on CSEdu4All.org has been tested and reviewed by students.

I also have a YouTube channel that I update regularly with computer science teaching and research videos. Check it out here.

My research group has been conducting research to understand and quantify the impact of COVID-19. Check it out here.

Here is my analysis to help people understand COVID's spread and how to win this battle. My goal here is to keep it simple and educate as many people as possible. Check it out here.

I am looking for motivated M.S. and Ph.D. students to work on problems in the area of wireless networks, ubiquitous computing and data science. If you are interested, please send an email with your resume.

News

April 2021

Two short papers on understanding and modeling the impact of mobility on COVID-19 accepted to IFIP Networking 2021. Necati Ayan, the lead PhD student will present our findings in his poster presentation.

March 2021

Our project on predicting COVID-19 spread using cell-phone date has been covered by Bing News. Check it out here!

January 2021

Our project on characterizing mobility patterns during COVID-19 using cellular network data is in the news. Check out the article here!

January 2021

Our paper on QoE-aware assignment and acheduling of video streams in heterogeneous cellular networks has been accepted to IEEE Global Internet Symposium 2021 (held in conjunction with INFOCOM 2021). An earlier version of the paper appeared as a poster in IEEE CCNC 2021.

December 2020

SWIFT paper that predicts resolution time of non-emergency events in cities has been accepted to Elsevier Pervasive and Mobile Computing Journal.

December 2020

DeepER paper that predicts resolution times of emergency services has been covered by Bing News, Spectrum News, Government Computer News and Voice of America.

October 2020

Our paper on analyzing the societal impact during the early days of the COVID-19 pandemic has been accepted to SocialCom 2020.

October 2020

Our paper on wireless channel quality prediction using sparse Gaussian conditional random fields has been accepted to IEEE CCNC 2021.

September 2020

Our paper on predicting emergency resolution time using deep learning has been accepted to IEEE CPSCom 2020.

September 2020

Our research on desgining model-based and machine learning approaches for caching and routing has been accepted to EAI AdHocNets 2020.

... see all News