10/2021: Our Work, "DREAMPlaceFPGA: an open-source analytical placer for large scale heterogeneous FPGAs using deep-learning toolkit," is accepted at IEEE ASPDAC 2022!
07/2021: Our Work, “ADAPT: An Adaptive Machine Learning Framework with Application to Lithography Hotspot Detection” is accepted at IEEE MLCAD 2021!
07/2021: My co-authored article "An Efficient Automatic Structure Design Method of Silicon on Insulator Lateral Power Device Considering RESURF Constraint" is accepted for publication in IEEE Transactions on Electron Devices.
01/2021: I joined Synopsys as a Senior R&D Engineer!
11/2020: I successfully defended by PhD dissertation "Machine Learning for VLSI Computer Aided Design"!
09/2020: Our Work, “Re-examining VLSI Manufacturing and Yield through the Lens of Deep Learning”, will be presented in a special session @ ICCAD 2020.
07/2020: My co-authored article “Automatic Selection of Structure Parameters of SOI LDMOS Using Bayesian Optimization” is accepted for publication in IEEE Electron Device Letters.
07/2020: I presented my PhD work @ DAC 2020 PhD Forum.
06/2020: My co-authored paper “TEMPO: Fast Mask Topography Effect Modeling with Deep Learning,” received Best Paper Award @ ACM International Symposium on Physical Design (ISPD), 2020
05/2020: Our article “GAN-SRAF: Sub-Resolution Assist Feature Generation using Generative Adversarial Networks” is accepted for publication in IEEE Transactions on Computer Aided Design (TCAD).
05/2020: My co-authored article “Critical Evaluation of Single Point Measurement-Based Quantitative Analyses in Forensic Breath Alcohol”, is accepted for publication in Forensic Science International: Reports.
02/2020: Our recent work “Wafer Map Defect Patterns Classification using Deep Selective Learning” is accepted @ DAC'20!
02/2020: My co-authored article “PowerNet: SOI Lateral Power Device Breakdown Prediction with Deep Neural Networks”, is published in IEEE Access.
01/2020: My co-authored work “Multicenter Validation of SPOT, an Artificial Intelligence based tool, to Optimize Selection of Elderly Stroke Patients for Mechanical Thrombectomy”, will be presented in the International Stroke Conference (ISC), 2020.
12/2019: Our article “Generative Learning in VLSI Design for Manufacturability: Current Status and Future Directions” is published in The Journal of Microelectronic Manufacturing (JOMM).
12/2019: I gave an invited talk @ Synopsys - Austin about our work “GAN-SRAF: Sub-Resolution Assist Feature Generation using Conditional Generative Adversarial Networks”.
11/2019: My co-authored paper “TEMPO: Fast Mask Topography Effect Modeling with Deep Learning ” was accepted @ ISPD 2020.
08/2019: Our recent work on “High-Definition Routing Congestion Prediction for Large-Scale FPGAs” is accepted @ ASPDAC'20!
06/2019: I presented our work “GAN-SRAF: Sub-Resolution Assist Feature Generation using Conditional Generative Adversarial Networks” @ DAC'19.
06/2019: I presented our work “Rethinking Sparsity in Performance Modeling for Analog and Mixed Circuits using Spike and Slab Models” @ DAC'19.
06/2019: My co-authored paper “LithoGAN: End-to-end Lithography Modeling with Generative Adversarial Networks” was selected as a Best Paper Award Candidate @ DAC'19!
03/2019: My co-authored paper “Litho-GPA: Gaussian Process Assurance for Lithography Hotspot Detection” was accepted @ DATE 2019.
03/2019: My co-authored journal article “Lithography Hotspot Detection using a Double Inception Module Architecture” was published in JM3.
02/2019: My co-authored journal article “Using Machine Learning to Optimize Selection of Elderly Patients for Endovascular Thrombectomy,” was published in Journal of NeuroInterventional Surgery (JNIS).
02/2019: My co-authored book chapter in Safe, Autonomous and Intelligent Vehicles (Springer, 2019) is published.