Streaming Readout Workshop SRO-XII

Speakers to be invited and topics (under development)

• Niko Neufeld (CERN) :  PCIe400
• Hao Xu (BNL), Hucheng Chen (BNL) : FELIX as Data Agregation module  
• Fernando Barbosa (JLab) : ASICs for SRO in ePIC
• Ken Oyama (NiAS) : AI chip 
• Esko Mikola (ALPHACORE) :  ALPHACORE ASICs for SRO
• Marco Locatelli (CAEN) : CAEN solutions for SRO ASICs
• Isar Mostafed (NALU) : NALU ASICs for SRO
• Manuel Rolo (IFNF) : SRO ASICs for HEP
• Christophe de la Taille (OMEGA) : OMEGA ASICs for SRO
• Chris Cuevas (JLab) : Fast Electronics for SRO
• Yoichi Igarashi (KEK) : nestDAQ framework and orchestration
• Kotaro Shirotori (RCNP) : nestDAQ tests at J-PARC and GR
• Shinsuke Ota (RCNP) : SPADI-Alliance and artemise framework for offline streaming data processing
• David Abbott (JLab) : sroCODA framework
• Vardan Gyurgyan (JLab) : Microservice framework for SRO
• David Lawrence (JLab) : SRO overview, test experiences at JLab, and prospects for GlueX and SoLID
• Martin Purschke (BNL) : rcdaq at sPHENIX
• Charles Hughes (Iowa): streaming experienence with sPHENIX TPC
• TBC : streaming experiences with sPHENIX VTX and INTT
• Nathan Brei (JLab) : JANA2 for streaming data processing
• Hanjie Liu (JLab) : SRO tools for test beam setups
• Jeff Landgraf (BNL) : ePIC SRO DAQ overview
• Markus Diefenthaler (JLab) : ePIC SRO computing
• William Gu : Timing and synchronization 
• Derek Anderson, Dmitry Kalinkin : Holistic reconsturction on streamed data
• Torre Wenaus (BNL) : Orchestration of Streaming data processing
• Jin Huang (BNL) : calibration overview for ePIC
• Cameron Dean (MIT) : Autonomous selection of physics events
• Tae Min Hong (Pittsburgh) : Near real-time Anomaly Detection
• Roberto Ammendola (IFNF) : AI for SRO
• Torri Jeske (JLab) : AI for Experimental Control
• Sergey Furletov (JLab) : Fast ML for FPGA
• Julián García Pardiñas (CERN) : Latest ML developments in LHCb
• Fabio Rossi (IFNF) : Real-time data reduction
• TBC : Noise reduction for dRICH in ePIC
• Yi Huang, Ray Ren (BNL) : Fast2D Convolutional Autoencoder for data compression of  TPC
• James Giroux (W&M) : Deep Learning for Cherenkov PID at EIC