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Manodeep ***** AI/ML Researcher

$1200 / day


Manodeep Sinha is specialised in developing cutting-edge software solutions that unlock insights from massive datasets. With a background as a Senior Research Software Scientist at Swinburne University, he led the development of Corrfunc, a renowned open-source tool leveraging SIMD intrinsics to enhance the performance of astronomical computations significantly. His expertise spans Python programming, C algorithms, and HPC, with notable achievements including the creation of novel algorithms for cosmological simulations and pioneering advancements in AI-driven data processing. Manodeep has a PhD in Astronomy & Astrophysics from The Pennsylvania State University and a B.Tech in Electrical Engineering from the Indian Institute of Technology, Kharagpur. He is recognised for his leadership in research software engineering and has received prestigious awards for his contributions to astronomy software development.


ARM NEON)AVXAVX2AVX512FC AlgorithmsCode OptimizationDevOpsDistributed SystemsHPCMPIOpenCLOpenMPPythonSIMD Intrinsics (SSE4Software DevelopmentUI/UX
AI Research ScientistAI Software DeveloperDeep Learning EngineerMachine Learning Engineer


Dec 2008 PhD in Astronomy & Astrophysics at The Pennsylvania State University
Jun 2000 B. Tech. in Electrical Engineering at Indian Institute of Technology


Aug 2010 - July 2015 Research Assistant Professor at Vanderbilt University

– Developed a groundbreaking algorithm to identify and characterize halo-halo flybys in cosmological simulations, pioneering the understanding of galactic interactions.
– Enhanced computational efficiency through parallel computing techniques including MPI and OpenMP, ensuring scalability and performance optimization.
– Integrated the algorithm seamlessly into existing simulation frameworks, facilitating its application across diverse cosmological models.
– Contributed to advancing knowledge in galaxy formation dynamics by enabling detailed analysis of halo interactions.

Aug 2015 - Dec 2016 Postdoctoral Researcher at Swinburne University of Technology

– Developed bespoke Python utilities to convert research datasets into a compatible format for ingestion by an established web-based tool, streamlining data integration processes.
– Implemented data preprocessing techniques to ensure accuracy and compatibility with the web platform’s requirements, facilitating seamless data transfer and analysis.
– Enhanced the efficiency of data transformation workflows through automation and optimization, reducing manual effort and increasing productivity.
– Collaborated with interdisciplinary teams to tailor data processing pipelines to specific research needs, fostering effective communication and project alignment.
– Supported ongoing research initiatives by providing reliable tools for data preparation, contributing to improved accessibility and usability of research findings.

Jan 2017 - March 2024 Senior Research Software Scientist at Swinburne University of Technoolgy

– Developed, implemented, and launched multiple iterations of the widely-used open-source tool, Corrfunc, employing software and hardware co-design strategies and SIMD intrinsics
(SSE4, AVX, AVX2, AVX512F, ARM NEON) to enhance the performance of common astronomy computations by more than 50Ă—.
– Modernized legacy C code to accommodate diverse data formats as inputs, improved MPI parallelization, integrated Python interfaces, implemented continuous integration practices,
and enhanced documentation for increased usability and maintainability.
– Designed a versatile and portable data format along with associated Python tools to facilitate the public distribution of hundreds of terabytes of simulation data from a large-
scale international collaboration.
– Collaborated closely with interdisciplinary teams to ensure the compatibility and scalability of Corrfunc across various computational environments and datasets, fostering
enhanced collaboration and research outcomes.
– Spearheaded efforts to optimize computational workflows, reducing processing times and resource utilization, thereby advancing capabilities in large-scale astronomical data

March 2024 - Present Founder & CEO at Sorsery Consulting

– Secured approximately USD 35,000 in funding to develop and deliver research software solutions.
– Identified and resolved a memory-race condition in multi-threaded execution within a prominent astronomy library, enhancing its stability and performance.
– Developed and deployed a distributed software pipeline for a client, enabling the processing of diverse data formats within existing legacy systems.
– Collaborated with stakeholders to ensure the seamless integration and operation of the distributed pipeline, optimizing data processing efficiency and scalability.
– Provided technical expertise and support to stakeholders, facilitating smooth project execution and achieving project milestones effectively.