Hesam Shahrokhi
Hesam is a Computer Scientist with a Ph.D. in Informatics from the University of Edinburgh. He completed his M.Sc. and B.Sc. degrees in Information Technology at Sharif University of Technology. Hesam specializes in the design of high-performance data processing systems, query engines, and compiler-based optimizations. He has been involved in both industrial and academic projects and gained deep expertise in the development of cloud, web, and system software solutions. Hesam's research has also been published in top-tier international venues and transformed into open-source tools on GitHub.
Industrial Experience
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Job Experience
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Senior Researcher in Databases, Huawei Research, Edinburgh, United Kingdom, Jun 2024 - Now
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Software Development Team Lead, Orchid Pharmed, Tehran, Iran, Dec 2019 - Feb 2021
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Founder, Product Manager, and Software Engineer, Sharif Pars, Tehran, Iran, Aug 2015 - Oct 2021
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Projects
- Planeto: A free cloud-based personal task-management service tailored for Persian users, featuring web and Android interfaces, with a 10K+ user base.
Academic Experience
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Publications
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PyTond: Efficient Python Data Science on the Shoulders of Databases,
Hesam Shahrokhi, Amirali Kaboli, Mahdi Ghorbani, Amir Shaikhha,
IEEE International Conference on Data Engineering (ICDE), 2024, Utrecht, Netherlands.
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Efficient Query Processing in Python Using Compilation,
Hesam Shahrokhi, Callum Groeger, Yizhou Yang, Amir Shaikhha,
ACM International Conference on Management of Data (SIGMOD), 2023, Seattle, US.
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An Efficient Vectorized Hash Table for Batch Computations,
Hesam Shahrokhi, Amir Shaikhha,
European Conference on Object-Oriented Programming (ECOOP), 2023, Seattle, US.
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Building a Compiled Query Engine in Python,
Hesam Shahrokhi, Amir Shaikhha,
ACM International Conference on Compiler Construction (CC), 2023, Montreal, Canada.
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Hinted Dictionaries: Efficient Functional Ordered Sets and Maps,
Amir Shaikhha, Mahdi Ghorbani, Hesam Shahrokhi
European Conference on Object-Oriented Programming (ECOOP), 2022 (Extended Abstract)/2023 (Full Paper), Seattle, US.
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Projects
- PyTond: A tool for automated translation of data science workloads (Pandas/NumPy) into optimized SQL with support for sparse and dense data layouts.
- VecHT: The first hardware-conscious vectorized hash table that offers efficient batch lookups by exploiting multi-threading, prefetching, and SIMD.
- SDQL.py: The first compiled query engine embedded in Python for highly efficient analytical query processing.
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Teaching
- Invited Lecturer, Web Programming, CE Department, Sharif University of Technology, 2015 and 2016
- Invited Lecturer, Operating Systems Design, CE Department, Sharif University of Technology, 2015
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Services
Honors and Awards
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Recognized as a Global Talent, The Royal Society of United Kingdom, 2024
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The University of Edinburgh Nominee for the Schmidt Science Fellowship, 2024
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Ph.D. Scholarship, University of Edinburgh, 2021
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Ranked 8 (out of 3,000) in Nationwide Ph.D. Admission Competitions, Iran, 2015
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Ranked 12 (out of 10,000) in Nationwide Postgraduate Admission Competitions, Iran, 2013