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Hi there ๐Ÿ‘‹

  • ๐Ÿ I'm Xuefen (้›ชๆžซ in Chinese), a Ph.D. student @Institute of Computing Technology of Chinese Academy of Sciences, received my bachelor degree@BUPT in the summer of 2021.
  • ๐ŸŒฑ My research interest mainly includes distributed ML system, data quality, cyber security, AutoDrive and various deep learning applications. I'm passionate about uncovering valuable & unsettled research topics, so perhaps we can collaborate to do some interesting things๐Ÿ˜†.
  • ๐Ÿ“ซ You can reach me via my email: [email protected], visit my personal website, or view my Google scholar.
  • โœจ I'm the big fan of Iris.
  • ๐ŸŒผ I love films & anime & sightseeing & music & night & sleeping a lot. I'm also an Apex & Overwatch amateur player : )
  • ๐Ÿ˜œ Thank you for your coming~

๐Ÿ’ฌ Recent News~

  • ๐ŸŽ‰ Three works got accepted @IEEE TPDS, INFOCOM and TMC, congrats to Jerry!
  • โ›ช I help to initialize the website of our lab, welcome to visit ICT-MobileComputingTeam!
  • ๐Ÿ˜„ I'll be a volunteer @ACM Turing Meetup because my supervisor serves as a PC, perhaps we can meet in Wuhan this summer!
  • ๐ŸŽ‰ Our FedNoRo which focuses on noisy&long-tailed data got accepted @IJCAI'23 main track, congrats to NanNan!
  • ๐Ÿ“š I'm invited to serve as a reviewer for ICML & AISTATS & CVPR & WWW & ICLR & NeurIPS & AAAI workshop & KDD workshop & ECAI & ICME & ACM TKDD & IEEE TKDE & IEEE TIV and help to review DCN.
  • ๐ŸŽ‰ Two co-authored works FedTrip&FedBIAD got accepted @IEEE/IPDPS'23, congrats to Xujing&Jingjing!
  • ๐Ÿ—ฝ My first work FedLSR got accepted @ACM/CIKM'22 full paper track with SIGWeb/NSF student award, and I'm currently working on its extension and trying to provide a deeper understanding towards this direction.
  • ๐Ÿ“– Currently dive into the sea of knowledge and explore together with friends.
  • ๐Ÿš— Join AMD and focus on Auto-Drive (especially in multi-sensor SLAM & 3D Perception & behavior prediction & LLM4Drive) as a "Co-op".

โ„Please feel free to contact me via WeChat, and it's a huge pleasure for me to discuss&chat with you.

drawing

Xuefen's Projects

algorithm-practice-in-industry icon algorithm-practice-in-industry

ๆœ็ดขใ€ๆŽจ่ใ€ๅนฟๅ‘Šใ€็”จๅขž็ญ‰ๅทฅไธš็•Œๅฎž่ทตๆ–‡็ซ ๆ”ถ้›†๏ผˆๆฅๆบ๏ผš็ŸฅไนŽใ€Datafuntalkใ€ๆŠ€ๆœฏๅ…ฌไผ—ๅท๏ผ‰

astraea icon astraea

Unofficial codes of TPDS'21 paper: Self-Balancing Federated Learning With Global Imbalanced Data in Mobile Systems

awesome-deep-phenomena icon awesome-deep-phenomena

A curated list of papers of interesting empirical study and insight on deep learning. Continually updating...

awesome-fl icon awesome-fl

Federated learning on graph and tabular data related papers, frameworks, and datasets.

awesome-llm4ad icon awesome-llm4ad

A curated list of awesome LLM for Autonomous Driving resources (continually updated)

bevfusion icon bevfusion

[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

chinese-chatbot-pytorch-implementation icon chinese-chatbot-pytorch-implementation

:four_leaf_clover: Another Chinese chatbot implemented in PyTorch, which is the sub-module of intelligent work order processing robot. ๐Ÿ‘ฉโ€๐Ÿ”ง

conad icon conad

Contrastive Attributed Network Anomaly Detection with Data Augmentation (PAKDD'22)

cpu624 icon cpu624

A TEC-8 Simulated Pipeline Processor Contributed by Dormitory#624

detzero icon detzero

[ICCV 2023] DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds

dilu icon dilu

DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

distributed-ac icon distributed-ac

A distributed airconditioning system contributed by 314-B group

ds-slam icon ds-slam

A complete robust semantic SLAM system which reduces the influence of dynamic objects

fedgcn icon fedgcn

Official Code for FedGCN [NeurIPS 2023]

fedlsr icon fedlsr

Official codes for CIKM '22 full paper: Towards Federated Learning against Noisy Labels via Local Self-Regularization

fednoro icon fednoro

Official codes of IJCAI'23 main track paper FedNoRo: Towards Noise-Robust Federated Learning By Addressing Class Imbalance and Label Noise Heterogeneity

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