Blog(2)

• TFPSNet Time-Frequency Domain Path Scanning Network for Speech Separation

  Deep learning techniques have accomplished a big step forward on speech separation task. The current leading methods are based on the time-domain audio separation network (TasNet) [1]. TasNet uses a learnable encoder and decoder to replace the fixed T-F domain transformation. It takes waveform inputs and directly reconstructs sources, and computes time-domain loss with utterance-level permutation invariant training (uPIT). Several approaches are proposed based on TasNet framework, such as the Conv-TasNet [2] , the dual-path recurrent neural network (DPRNN) [3], the dual-path Transformer network (DPTNet) [4], RNN-free transformer-based neural network (SepFormer) [5] , a self-attentive network with a novel sandglass-shape, namely Sandglasset [6].

• FedMargin - Federated Learning via Attentive Margin of Semantic Feature Representations

  Let’s play a simple game. Open the photo gallery on your phone and briefly scroll your images, do you see some patterns and recognize the objects you like on the images?

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Publications(355)

• Network GDT: GenAI Based Digital Twin for Automated Network Performance Evaluation

  AuthorSukhdeep Singh, Swaraj Kumar, Moonki Hong, Ashish Jain, Madhan Raj Kanagarahinam

  PublishedIEEE International Conference on Communications (ICC)

  Date2025-09-26

• Leveraging O-RAN SC AI/ML Framework & Non-RT RIC for AI-Driven Network Slice QoS Optimization

  AuthorAshish Jain, Sukhdeep Singh, Moonki Hong

  PublishedIEEE Globecom Workshop

  Date2025-08-12

• Reinforcement Learning Framework for Power Optimization in 5G RAN Systems with Blockchain-Enhanced Security

  AuthorSwaraj Kumar, Sukhdeep Singh, Moonki Hong, Taewan Kim

  PublishedIEEE Globecom Workshop

  Date2025-08-12

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News(43)

• Samsung Wins Best Paper Award at IEEE ICC 2025 for Breakthrough in GenAI-Based Digital Twin for Automated Network Evaluation

  Samsung Research (SR) is thrilled to announce that the research paper titled “Network GDT: GenAI based Digital Twin for Automated Network Performance Evaluation” has won the Best Paper Award at the Institute of Electrical and Electronics Engineers International Conference on Communications (IEEE ICC) 2025, one of the most prestigious flagship conferences in the field of telecommunications.

• Driving Technological Excellence: SRI-B Innovator Wins IEEE's Top Technologist Award

  Samsung Research & Development Institute, Bangalore (SRI-B), continues to set benchmarks in innovation and engineering as Dr. Madhan Raj, a distinguished technologist, has been named the ‘Technologist of the Year’ by the prestigious Institute of Electrical and Electronics Engineers (IEEE) India Council.

• Five Samsung Electronics Researchers Named IEEE Fellows  

  Samsung Electronics today announced that five of its researchers from around the world have been selected as 2025 Fellows of the Institute of Electrical and Electronics Engineers1 (IEEE), one of the world’s most prestigious engineering organizations.

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