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Naw Safrin Sattar

Institution/Organization: University of New Orleans.

Department: Computer Science.

Academic Status: Graduate Student.

What conference theme areas are you interested in:

Computational science and machine learning;
High performance software: packages and design;
Algorithms at extreme scales;
High-order methods, novel discretizations, and scalable solvers;
Data science, analytics, and visualization;
Scientific simulation and uncertainty.


Since my undergraduate studies, I have been enthusiastic to work with Big Data. I have been aware that to work with Big Data, I need to learn and use some technologies and High-Performance Computing is one such arena which is closely related to Big Data. After learning the aspects of HPC, I aspire for becoming a prominent researcher and educator focusing HPC. My research interest includes intersection of data mining, HPC and network science. Therefore, after completing my B.Sc., I was actively looking for an opportunity to pursue my PhD Degree in the USA. I am very fortunate to get myself admitted to University of New Orleans and be the part of Big Data and Scalable Computing Research Group which aligns with my research interest completely. Currently, I work on mining and analysis of big social and information networks by designing parallel algorithms and HPC techniques. I’ve been working on HPC since 2015 to present, with an experience of around 4 years. I started my research work with my undergraduate thesis that is based on Approximation technique of HPC. This work is published in proceedings of IEEE ICECE 2016. I have also completed the Concurrent Programming Course during my PhD course-work and obtained above 90% marks where I have done several projects using Fork-Join Framework, Java NIO, Multi-threading, etc. In my PhD research, I am currently working on designing parallel scalable algorithms for detecting communities in large-scale networks using OpenMP and MPI. This work has been accepted in the 16th IEEE DASC 2018, Athens, Greece. I am also familiar with MPI performance tools: Gyan and Varlist. I use Louisiana Optical Network Infrastructure (LONI), the largest available resource for HPC in Louisiana State. At times, I work on the server owned by UNO as well when LONI becomes unavailable due to disaster. I also use graphx from Apache Spark. I foresee myself as a full-fledged research professional in an organization, or a faculty member in the field of HPC.

Non-Work Related Activities/Interests:

I have volunteered several big events starting from my undergraduate school, Bangladesh University of Engineering and Technology (BUET) and continuing in my Graduate School, University of New Orleans (UNO) too. Currently, I am appointed as Webmaster at Bangladesh Student Association (BSA) at UNO. I actively volunteered in the following events:

1) CSE Festival at BUET, 2011-2015: Managing crowd and directing people participating in open rally program (More than 500 people), Running Coding Contest to smoothly & taking care of needs of the participants, Making arrangements for organizing Poster Session & Robotics Contest, Catering Food and distributing Food 2) 4th International Conference on Networking, Systems and Security (NSysS) at BUET, 2017: Imparting duty on Registration booth and handing over participants their conference belongings, directing participants for Snacks & Lunch, making technical arrangements during Paper Presentation Session 3) International Mother Language Day Celebration at UNO, 2017: decorating the venue, making sitting arrangement, welcoming guests at registration Booth (Around 300 people) 4) Get to Know UNO, 2017: Setting up Stall, greeting guests, arranging photo booth for guests 5) International Night at UNO, 2018: Setting up Stall, greeting guests, Serving Food, Cleaning Up after Event (More than 1000 people) 6) Crawfish Mambo at New Orleans, 2018: Setting Up Stall, helping Guests by serving Food, Cleaning up after event (More than 1000 people) 7) Career Fair at UNO, 2018: Welcoming guests at registration Booth and providing them with goods (Around 400 people)