\subtitle{Selected Projects}{\faSuitcase}

\begin{projects}
\project{Since 2026}		{Morphosphere}	{Distributed Data Architecture for Interactive 3D/4D Tomography Repositories}
    \action{\since{2025}}	{}		{Co-authored proposal; PI / work-package lead for data reduction and organization}
    \action{\since{2026}}	{}		{Project targets a data lifecycle spanning data-generation facilities, HPC centres \& users}
    \action{\since{2026}}	{}		{Exploring compression, caching, and abstractions to enable interactive data access}
    \action{\since{2026}}	{}		{Co-designing DAG tomography framework; evaluating NVIDIA Graphs/Holoscan}

% Canonical, Electronics, Physicts
 \project{Since 2018}		{KaaS}		{KATRIN-as-a-Service (KaaS) platform for distributed data acquisition systems}
    \action{\since{2018}}	{4}		{Initiated platform, secured funding, built team of 4, and led production rollout}
    \action{\since{2022}}	{}		{Coordinated integration across Canonical, KIT HPC, electronics \& experiment teams}
    \action{\since{2018}}	{4}		{KaaS integrates data from fast detectors and thousands of monitoring sensors}
    \action{\since{2022}}	{1}		{Led development of containerized AF\_XDP data-acquisition framework}
    \action{\ivl{2018}{2019}}	{}		{Cut costs by adapting legacy software for distributed ops and integrating HPC resources}

%    \action{\since{2020}}	{3}		{Modeled data access patterns and guided research on organization of time-series data}
%    \action{\since{2015}}	{1}		{Supervised development of online monitoring framework for the KaaS ecosystem}
%    \action{\ivl{2019}{2020}}	{3}		{Coordinated migration of the KATRIN services to the KaaS platform}
%    \action{\since{2020}}	{2}		{Lead research on cloud technologies for heterogeneous control systems}

 \project{\ivl{2017}{2022}}	{Toma}		{Uncovering \& Exploiting GPU Architectural Features}
    \action{\ivl{2017}{2018}}	{}		{Identified performance imbalances and hidden parallelism in NVIDIA and AMD GPUs}
    \action{\ivl{2017}{2018}}	{}		{Developed method exploiting intra-SM parallelism on NVIDIA (up to 30\% speed-up)}
    \action{\ivl{2017}{2018}}	{}		{Accelerated tomography 4–6× through architecture-aware resource balancing}
    \action{\ivl{2019}{2020}}	{}		{Published paper "\urlref{Reviewing GPU architectures to build efficient back projection...}{https://doi.org/10.1007/s11554-019-00883-w}"}

 \project{\ivl{2016}{2017}}	{CMS}		{GPU-based L1 Trigger for CERN CMS using GPUDirect (6~$\mu$s latency budget)} 
 \project{\ivl{2011}{2017}}	{UFO}		{Coordinated software work-package and led algorithm parallelization in a project "Ultrafast tomography with online monitoring and image-based control"}


% \project{\ivl{2011}{2016}}	{ADEI/ASTOR}	{Web-platforms for visualization of volumetric (tomographic) and time-series data}
% \action{\ivl{2011}{2014}}	{4}		{Developed Platform for exploration and analysis of time-series in terascale archives}
% \project{\ivl{2009}{2013}}	{GPU}		{Parallel algorithms and software optimization (GPGPU, SIMD): 10-100x speed-up}
% \project{\ivl{2003}{2006}}	{PHD}		{PhD in Computer Engineering on communication protocols for distributed DAQ}
% \project{\ivl{1999}{2008}}	{DAQ}		{Distributed Data Acquistion Systems for particle detector networks}

\end{projects}