I am a master's student in the Electrical and Computer Engineering department at The University of British Columbia (UBC), working with Prof. Matei Ripeanu. During my grad studies at UBC, I did an 8-month internship at TELUS Communications Inc. and MobileLIVE as a Network Engineer. Before starting my graduate studies in Canada, I worked for a year as a research intern at IST Austria, where I was hosted by Prof. Dan Alistarh. Prior to that, I did an internship at EPFL under the guidance of Dr. Mirjana Stojilovic and Prof. Paolo Ienne. I did my undergraduate studies at Amirkabir University of Technology (Tehran Polytechnic).

My current research lies in High-performance computing and its application to genome analysis. In particular, I study different approaches to accelerate DNA sequence alignment by employing available and emerging technologies like Processing-in-Memory (PIM). Some other areas of my interest are federated learning, performance analysis, edge computing, reconfigurable computing, and domain-specific languages.

Recent News

• August 2024: Our PiM paper was nominated for Best Paper Award (top 6 papers) at Euro-Par 2024.
• April 2024: Our paper “(re)Assessing PiM Effectiveness for Sequence Alignment” was accepted at Euro-Par 2024.
• May 2023: I started my internship at TELUS.
• November 2022: Our CGX paper was chosen as Best Paper Award Runner-up at Middleware 2022.
• Jan 2022: I became a member of NetSysLab.
• Jan 2022: I started my masters studies at UBC in Vancouver.
• August 2020: I moved to Klosterneuburg to work at IST Austria.
• February 2020: I started a new internship at EPFL.
• Oct 2019: I got my undergrad degree.
• June 2019: I started my internship at EPFL.
• March 2019: I won Summer@EPFL fellowship.

Publications

Hamidreza Ramezanikebrya and Matei Ripeanu, (re)Assessing PiM Effectiveness for Sequence Alignment. In 30th International European Conference on Parallel and Distributed Computing (Euro-Par 2024), August 26-30, 2024, Best Paper Award Nominee.

Ilia Markov, Hamidreza Ramezanikebrya, and Dan Alistarh, CGX: Adaptive System Support for Communication-Efficient Deep Learning. In 23rd International Middleware Conference (Middleware 2022), November 7-11, 2022, Best Paper Award Runner-up.