Assefaw Hadish Gebremedhin
School of Electrical Engineering and Computer Science
Washington State University
Email: assefaw AT eecs DOT wsu DOT edu
Office: EME B43
355 Spokane St
EME B43, School of EECS
Washington State University
Pullman, WA 99164
Assefaw Gebremedhin is currently an assistant professor in the
School of Electrical Engineering and Computer Science at Washington State University, where he leads the Scalable Algorithms for Data Science (SCADS)
Prior to joining WSU in Fall 2014, he was a
research assistant professor at Purdue University
Department of Computer Science.
There, he served as a founding member and a co-investigator in the Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute, a multi-institution project funded by the Department of Energy under the SciDAC-2 program.
His current research activities and interests include: combinatorial scientific computing, network science, high-performance computing, and data mining and machine learning with a focus on applications involving (i) analysis of patterns of short-sequence repeats in DNA data and (ii) development of robust methods for integration and analysis of data collected via sensor-equipped wearable systems and mobile devices.
In 2016, Assefaw received the National Science Foundation CAREER Award for work on fast and scalable combinatorial algorithms for data analytics.
Assefaw earned his PhD and MSc in Computer Science from the University of Bergen, Norway, and his BSc in
Electrical Engineering from Addis Ababa University, Ethiopia.
Curriculum Vitae (pdf, last updated July 2017)
In Spring 2018, I will be teaching the course CptS 591 Elements of Network Science. A version of the course was offered in Spring 2017 under the course number CptS 580. Visit the course website of the Spring 2017 offering to get an idea about the course, pre-requisites and audience.
In Fall 2017, I am teaching the course CptS 483-04 Introduction to Data Science.
the syllabus of the course and here is the course website.
The course is designed to be suitable for both undergraduate and graduate students.
The previous two offerings of the course (Fall 2015 and Fall 2016) attracted about 30 students each time, with about 50%--50% split between
undergrad and graduate enrollment. If you are a graduate student and would like to enroll for the course this Fall, send an email to
Jessica Cross at the address firstname.lastname@example.org (with a copy to me) so she may grant you the required permission.
If you are interested in the course but are not sure about your background, feel free to email me about it.
CSC16 (The Seventh SIAM Workshop on Combinatorial Scientific Computing) with Erik Boman.
The proceedings of workshop has appeared on SIAM Publication platform.
And a short article about the workshop has appeared in
- Browse through the News page in the menu on the left for more news and updates.
Here are a few things I am currently working on (browse through the
Research page in the menu on the left
for details in each):
- Developing models, algorithms and software for management and analysis of short-sequence DNA repeat data
- Developing effective paradigms for parallelizing graph and other combinatorial algorithms on modern computing platforms
- Developing efficient machine learning and signal processing algorithms for wearable systems, with an eye on health analytics applications
- Developing network data analytics methods for graph query performance prediction
- Developing fast and scalable algorithms for discovering dense subgraphs in large, sparse networks
- Developing efficient Automatic Differentiation algorithms for Hessian computation
NSF CAREER Award Info:
Here is a link to NSF's Announcement and here is a link to the project's website.
Note to Prospective Students:
I am actively looking for motivated graduate students with strong background and interest in working
in the research areas I pursue. If you would like to join my group, please send me an email
containing a brief statement of interest, and CV and relevant test scores in an attachement.