Jielin Qiu
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Jielin Qiu

Senior Research Scientist
Salesforce AI Research

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About

I am currently a Senior Research Scientist at Salesforce AI Research, working on multimodal LLM, Long-Context LLM, and LLM agent. Before that, I worked on building multimodal-LLM that can understand and generate audio at Boson AI.

I received my Ph.D. in Computer Science from Carnegie Mellon University. I was fortunate to be advised by Prof. Lei Li and Prof. Christos Faloutsos. Before that, I received my B.Eng. from Shanghai Jiao Tong University, advised by Prof. Bao-Liang Lu. During my Ph.D., I've worked at Google, Meta, Microsoft, Amazon Web Services, and Adobe.


News

  • [2026-09] Critical-State RL released for diagnosing trainable states in multi-turn tool use.
  • [2026-09] Salesforce Koa released as an enterprise language model for agentic tool use.
  • [2026-09] Random Attention released for efficient reasoning through KV cache eviction.
  • [2026-08] AI4AI at Test-Time released for strong-to-weak capability transfer via harnesses.
  • [2026-06] BehaviorBench released for modeling real-world user decisions from behavioral traces.
  • [2026-05] CMR-CLIP published in Nature Communications.
  • [2026-04] Whisper-AuT released for efficient audio-LLM training with a domain-adapted audio encoder.
  • [2026-04] RealUserSim released for grounded user simulation in agent benchmarking.
  • [2026-03] Enterprise Sales Copilot released for real-time AI support in live sales calls.
  • [2026-03] Building Enterprise Realtime Voice Agents from Scratch released as a technical tutorial with open-source code.
  • [2026-03] Vector Prompt Interfaces position paper released on enabling customization of large language models.
  • [2026-03] VoiceAgentRAG released for low-latency RAG in real-time voice agents using a dual-agent architecture.
  • [2026-01] Prompt Optimization Via Diffusion Language Models released with open-source code.
  • [2025-11] LoCoBench-Agent released for evaluating LLM agents in long-context software engineering.
  • [2025-11] MCPEval accepted by EMNLP 2025.
  • [2025-11] GeoGNN released for quantifying and mitigating semantic drift in text-attributed graphs.
  • [2025-10] xRouter: Cost-aware LLM orchestration system released.
  • [2025-10] Webscale-RL preprint released on scaling reinforcement learning data with an automated pipeline.
  • [2025-10] CoDA: Coding LM via Diffusion Adaptation released.
  • [2025-09] UserRL: User-centric agent training framework released.
  • [2025-07] Promptomatix: Automatic prompt optimization framework released.
  • [2025-04] We release Higgs-Audio, a powerful model for audio understanding and generation.
  • [2024-11] MMWatermark Robustness gets accepted by Journal of Data-centric Machine Learning Research (DMLR).
  • [2024-09] SnapNTell gets accepted by EMNLP 2024 Findings.
  • [2024-04] Defended my PhD thesis. Huge thanks to my amazing advisors Prof. Lei Li and Prof. Christos Faloutsos, and thesis committee Prof. Yonatan Bisk and Prof. William Wang.
  • [2024-04] MMSum dataset gets accepted by CVPR 2024 as Poster Highlight (Top 11.9%). Check our MMSum dataset!
  • [2024-03] Embodied Policy Learning with Language-based Scene Summarization gets accepted by NAACL 2024.
  • [2024-01] MMRobustness gets accepted as the very first paper at Journal of Data-centric Machine Learning Research (DMLR) 2024. Check our MMRobustness benchmark!
  • [2023-11] One paper about Cardiovascular record retrieval gets accepted by PMLR ML4H 2023.
  • [2023-10] Start a research internship at Google.
  • [2023-10] One paper about human languages and brain signals gets accepted by EMNLP Findings 2023.
  • [2023-06] One paper accepted as spotlight by ICML 2023 Workshop on Interactive Learning with Implicit Human Feedback.
  • [2023-06] Two papers accepted by ICML 2023 Workshop on Machine Learning for Multimodal Healthcare Data.
  • [2023-05] Start a research internship at Meta.
  • [2023-05] One paper about multimodal summarization by Optimal Transport gets accepted by ACL Findings 2023.
  • [2023-04] One paper about data augmentation on Geodesics gets accepted by ICML 2023.
  • [2023-04] Invited talk at Microsoft Research Cambridge.
  • [2023-02] One paper accepted by CVPR 2023.
  • [2023-02] One paper accepted by ICASSP 2023.
  • [2023-01] Start a research internship at Microsoft.
  • [2023-01] One paper accepted by EACL Findings 2023.
  • [2023-01] One paper accepted by AISTATS 2023.
  • [2022-10] One paper accepted by WACV 2023.
  • [2022-10] One paper accepted by NeurIPS 2022 Workshop on Distribution Shifts.
  • [2022-10] Top Reviewers in NeurIPS 2022.
  • [2022-06] One paper accepted by MLHC 2022.
  • [2022-05] Start a research internship at AWS AI.
  • [2022-05] One paper accepted by ICML 2022 workshop on Principles of Distribution Shift.
  • [2022-04] One paper accepted by ICLR 2022 Workshop on Socially Responsible Machine Learning.
  • [2021-09] Receive a gift funding from Adobe. Thanks, Adobe!
  • [2021-05] Start a research internship at Adobe research.

Publications

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Critical-State RL: Diagnosing Trainable States for Multi-Turn Tool Use overview
Critical-State RL: Diagnosing Trainable States for Multi-Turn Tool Use
Zixiang Chen, Wenting Zhao, Zhepeng Cen, Akshara Prabhakar, Jielin Qiu, Jianguo Zhang, Zhiwei Liu, Tulika Manoj Awalgaonkar, Liangwei Yang, Shelby Heinecke, Silvio Savarese, Huan Wang
arXiv preprint, 2026
[paper]

Salesforce Koa: An Enterprise Language Model for Agentic Tool Use overview
Salesforce Koa: An Enterprise Language Model for Agentic Tool Use
Zixiang Chen, Sufeng Niu, Yingchi Liu, Wenting Zhao, Akshara Prabhakar, Shubham Mehrotra, Bin Bi, Zhujun Lan, Katherine Tan, Mohammad Ramezanali, Tulika Manoj Awalgaonkar, Monojit Banerjee, Jielin Qiu, Shiva Kumar Pentyala, Zhepeng Cen, Anupam Tripathi, Ali Ziaei, Regunathan Radhakrishnan, Darvish Lee Shadravan, Shelby Heinecke, Sitaram Asur, Silvio Savarese, James Zhu, Phil Mui, Huan Wang
arXiv preprint, 2026
[paper]

Random Attention: Rethinking KV Cache Eviction for Efficient Reasoning overview
Random Attention: Rethinking KV Cache Eviction for Efficient Reasoning
Heng Wang, Jielin Qiu, Wenting Zhao, Cheng Qian, Liangwei Yang, Weizhi Zhang, Jiawei Han, Heng Ji, Silvio Savarese, Shelby Heinecke, Huan Wang
arXiv preprint, 2026
[paper] [code]

AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses overview
AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses
Cheng Qian, Wenting Zhao, Liangwei Yang, Heng Wang, Jielin Qiu, Heng Ji, Silvio Savarese, Huan Wang, Shelby Heinecke
arXiv preprint, 2026
[paper]

BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces overview
BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces
Liangwei Yang, Jielin Qiu, Zixiang Chen, Ming Zhu, Juntao Tan, Zhiwei Liu, Wenting Zhao, Zhujun Lan, Akshara Prabhakar, Silvio Savarese, Huan Wang, Shelby Heinecke
arXiv preprint, 2026
[paper]

Contrastive Language Image Pretraining for a Cardiac Magnetic Resonance Image Embedding with Zero-Shot Capabilities overview
Contrastive Language Image Pretraining for a Cardiac Magnetic Resonance Image Embedding with Zero-Shot Capabilities
Makiya Nakashima, Jielin Qiu, Peide Huang, Jihye Lee, Po-Hao Chen, Richard Grimm, Christopher Nguyen, Byung-Hak Kim, Ding Zhao, Deborah Kwon, David Chen
Nature Communications 17, 4416 (2026)
[paper] [code] [model]

Whisper-AuT linear probe accuracy comparison from Table 2
Whisper-AuT: Domain-Adapted Audio Encoder for Efficient Audio-LLM Training
Jielin Qiu, Ming Zhu, Wenting Zhao, Zhiwei Liu, Liangwei Yang, Zixiang Chen, Roshan Ram, Akshara Prabhakar, Juntao Tan, Rithesh Murthy, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang
arXiv preprint, 2026
[paper]

RealUserSim: Bridging the Reality Gap in Agent Benchmarking via Grounded User Simulation overview
RealUserSim: Bridging the Reality Gap in Agent Benchmarking via Grounded User Simulation
Ming Zhu, Juntao Tan, Rithesh Murthy, Jielin Qiu, Liangwei Yang, Wenting Zhao, Silvio Savarese, Shelby Heinecke, Huan Wang
arXiv preprint, 2026
[paper]

Enterprise Sales Copilot system architecture from Figure 1
Enterprise Sales Copilot: Enabling Real-Time AI Support with Automatic Information Retrieval in Live Sales Calls
Jielin Qiu, Liangwei Yang, Ming Zhu, Wenting Zhao, Zhiwei Liu, Juntao Tan, Zixiang Chen, Roshan Ram, Akshara Prabhakar, Rithesh Murthy, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang
arXiv preprint, 2026
[paper]

Enterprise realtime voice agents time-to-first-audio comparison from Table 5
Building Enterprise Realtime Voice Agents from Scratch: A Technical Tutorial
Jielin Qiu, Zixiang Chen, Liangwei Yang, Ming Zhu, Zhiwei Liu, Juntao Tan, Wenting Zhao, Rithesh Murthy, Roshan Ram, Akshara Prabhakar, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang
arXiv preprint, 2026
[paper] [code]

Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models overview
Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models
Liangwei Yang, Shiyu Wang, Haolin Chen, Rithesh Murthy, Ming Zhu, Jielin Qiu, Zixiang Chen, Juntao Tan, Jianguo Zhang, Zhiwei Liu, Wenting Zhao, Silvio Savarese, Caiming Xiong, Huan Wang, Shelby Heinecke
arXiv preprint, 2026
[paper]

VoiceAgentRAG: Solving the RAG Latency Bottleneck in Real-Time Voice Agents Using Dual-Agent Architectures overview
VoiceAgentRAG: Solving the RAG Latency Bottleneck in Real-Time Voice Agents Using Dual-Agent Architectures
Jielin Qiu, Jianguo Zhang, Zixiang Chen, Liangwei Yang, Ming Zhu, Juntao Tan, Haolin Chen, Wenting Zhao, Rithesh Murthy, Roshan Ram, Akshara Prabhakar, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang
arXiv preprint, 2026
[paper] [code]

Prompt Optimization Via Diffusion Language Models overview
Prompt Optimization Via Diffusion Language Models
Shiyu Wang, Haolin Chen, Liangwei Yang, Jielin Qiu, Rithesh Murthy, Ming Zhu, Zixiang Chen, Silvio Savarese, Caiming Xiong, Shelby Heinecke, Huan Wang
arXiv preprint, 2026
[paper] [code]

EGI-BENCH six-metric model profiles from Figure 3
EGI-BENCH: An Enterprise General Intelligence Benchmark Suite
Zhiwei Liu, Zhujun Lan, Jielin Qiu, Zixiang Chen, Liangwei Yang, Juntao Tan, Ming Zhu, Akshara Prabhakar, Wenting Zhao, Shelby Heinecke, Silvio Savarese, Huan Wang
Preprint, 2026
[paper]

LightMem extraction, consolidation, and retrieval overview from Figure 1
A Lightweight, Domain-Adaptive Memory System for LLM Agents
Juntao Tan, Liangwei Yang, Wenting Zhao, Jielin Qiu, Ming Zhu, Rithesh Murthy, Silvio Savarese, Huan Wang, Shelby Heinecke, Caiming Xiong
ICLR 2026 Workshop on Memory for LLM-Based Agentic Systems
[paper]

LoCoBench-Agent: An Interactive Benchmark for LLM Agents in Long-Context Software Engineering
Jielin Qiu, Zuxin Liu, Zhiwei Liu, Rithesh Murthy, Jianguo Zhang, Haolin Chen, Shiyu Wang, Ming Zhu, Liangwei Yang, Juntao Tan, Roshan Ram, Akshara Prabhakar, Tulika Awalgaonkar, Zixiang Chen, Zhepeng Cen, Cheng Qian, Shelby Heinecke, Weiran Yao, Silvio Savarese, Caiming Xiong, Huan Wang
2025
[paper] [code]

GeoGNN: Quantifying and Mitigating Semantic Drift in Text-Attributed Graphs overview
GeoGNN: Quantifying and Mitigating Semantic Drift in Text-Attributed Graphs
Liangwei Yang, Jing Ma, Jianguo Zhang, Zhiwei Liu, Jielin Qiu, Shirley Kokane, Shiyu Wang, Haolin Chen, Rithesh Murthy, Ming Zhu, Huan Wang, Weiran Yao, Caiming Xiong, Shelby Heinecke
arXiv preprint, 2025
[paper]

MCPEval: Automatic MCP-based Deep Evaluation for AI Agent Models
Zhiwei Liu, Jielin Qiu, Shiyu Wang, Jianguo Zhang, Zuxin Liu, Roshan Ram, Haolin Chen, Weiran Yao, Shelby Heinecke, Silvio Savarese, Huan Wang, Caiming Xiong
EMNLP 2025 (System Demonstrations)
[paper] [code]

xRouter: Training Cost-Aware LLMs Orchestration System via Reinforcement Learning
Cheng Qian, Zuxin Liu, Shirley Kokane, Akshara Prabhakar, Jielin Qiu, Haolin Chen, Zhiwei Liu, Heng Ji, Weiran Yao, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang
2025
[paper] [code] [model]

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels overview
Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels
Zhepeng Cen, Haolin Chen, Shiyu Wang, Zuxin Liu, Zhiwei Liu, Jielin Qiu, Ding Zhao, Silvio Savarese, Caiming Xiong, Huan Wang, Weiran Yao
arXiv preprint, 2025
[paper]

CoDA: Coding LM via Diffusion Adaptation
Haolin Chen, Shiyu Wang, Can Qin, Bo Pang, Zuxin Liu, Jielin Qiu, Jianguo Zhang, Yingbo Zhou, Zeyuan Chen, Ran Xu, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang, Weiran Yao
2025
[paper] [code] [model]

UserRL: Training Interactive User-Centric Agent via Reinforcement Learning
Cheng Qian, Zuxin Liu, Akshara Prabhakar, Jielin Qiu, Zhiwei Liu, Haolin Chen, Shirley Kokane, Heng Ji, Weiran Yao, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang
2025
[paper] [code] [data]

LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software Engineering
Jielin Qiu, Zuxin Liu, Zhiwei Liu, Rithesh Murthy, Jianguo Zhang, Haolin Chen, Shiyu Wang, Ming Zhu, Liangwei Yang, Juntao Tan, Zhepeng Cen, Cheng Qian, Shelby Heinecke, Weiran Yao, Silvio Savarese, Caiming Xiong, Huan Wang
2025
[paper] [code]

Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models
Rithesh Murthy, Ming Zhu, Liangwei Yang, Jielin Qiu, Juntao Tan, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang
2025
[paper] [code]

Higgs-Audio: A Multimodal Foundation Model for Audio Understanding and Generation
Jielin Qiu, et al.
2025

[code] [model] [blog]

MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning
Yiqing Liang, Jielin Qiu, Wenhao Ding, Zuxin Liu, James Tompkin, Mengdi Xu, Mengzhou Xia, Zhengzhong Tu, Laixi Shi, Jiacheng Zhu
2024
[paper] [website] [code] [data]

Evaluating Durability: Benchmark Insights into Image and Text Watermarking
Jielin Qiu*, William Han*, Xuandong Zhao, Shangbang Long,
Christos Faloutsos, Lei Li
Journal of Data-centric Machine Learning Research (DMLR) 2024
[paper] [code]

SnapNTell: Enhancing Entity-Centric Visual Question Answering with Retrieval Augmented Multimodal LLM
Jielin Qiu, Andrea Madotto, Zhaojiang Lin, Paul Crook, Ethan Xu,
Luna Dong, Christos Faloutsos, Lei Li, Babak Damavandi, Seungwhan Moon
EMNLP 2024 Findings
[paper]

Embodied Executable Policy Learning with Language-based Scene Summarization
Jielin Qiu*, Mengdi Xu*, William Han*, Seungwhan Moon, Ding Zhao
NAACL 2024
ICML 2023 Workshop on Interactive Learning with Implicit Human Feedback (spotlight)
[paper] [code]

MMSum: A Dataset for Multimodal Summarization and Thumbnail Generation of Videos
Jielin Qiu, Jiacheng Zhu, William Han, Aditesh Kumar, Karthik Mittal, Claire Jin, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Ding Zhao, Bo Li, Lijuan Wang
CVPR 2024 (Poster Highlight 11.9%)
[paper] [website] [dataset] [code]

Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao,
Bo Li, Mu Li
Journal of Data-centric Machine Learning Research (DMLR) 2024
[paper] [website] [code]

Entity6K: A Large Open-Domain Evaluation Dataset for Real-World Entity Recognition
Jielin Qiu, William Han, Winfred Wang, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Christos Faloutsos, Lei Li, Lijuan Wang
2024
[paper]

Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment
Jielin Qiu, Jiacheng Zhu, Mengdi Xu, Franck Dernoncourt, Trung Bui, Zhaowen Wang, Bo Li, Ding Zhao, Hailin Jin
ACL 2023 Findings
[paper] [press]

Can Brain Signals Reveal Inner Alignment with Human Languages?
William Han*, Jielin Qiu*, Jiacheng Zhu, Mengdi Xu, Douglas Weber,
Bo Li, Ding Zhao
EMNLP 2023 Findings
[paper] [code]

Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report
Jielin Qiu*, Jiacheng Zhu*, Shiqi Liu, William Han, Jingqi Zhang, Chaojing Duan, Michael Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao
PMLR Proceedings of Machine Learning for Health 2023
[paper] [code]

Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging
Jielin Qiu*, Peide Huang*, Makiya Nakashima, Jaehyun Lee, Jiacheng Zhu, Wilson Tang, Pohao Chen, Christopher Nguyen, Byung-Hak Kim, Debbie Kwon, Douglas Weber, Ding Zhao, David Chen
ICML 2023 Workshop on Machine Learning for Multimodal Healthcare Data
[paper]

Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models?
Jielin Qiu*, William Han*, Jiacheng Zhu, Mengdi Xu, Michael Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao
EACL 2023 Findings
[paper] [code]

Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation
Jielin Qiu*, Jiacheng Zhu*, Mengdi Xu, Peide Huang, Michael Rosenberg, Douglas Weber, Emerson Liu, Ding Zhao
ICASSP 2023
[paper]

LiveSeg: Unsupervised Multimodal Temporal Segmentation of Long Livestream Videos
Jielin Qiu, Franck Dernoncourt, Trung Bui, Zhaowen Wang, Ding Zhao, Hailin Jin
WACV 2023
[paper] [press]

Interpolation for Robust Learning: Data Augmentation on Geodesics
Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, XuanLong Nguyen,
Bo Li, Ding Zhao
ICML 2023
[paper]

Align and Attend: Multimodal Summarization with Dual Contrastive Losses
Bo He, Jun Wang, Jielin Qiu, Abhinav Shrivastava, Trung Bui, Zhaowen Wang
CVPR 2023
[paper] [code]

Benchmarking Robustness under Distribution Shift of Multimodal Image-Text Models
Jielin Qiu, Yi Zhu, Xingjian Shi, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li
NeurIPS 2022 Workshop on Distribution Shifts
[paper] [press] [code]

GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction
Jiacheng Zhu*, Jielin Qiu*, Zhuolin Yang, Douglas Weber, Michael Rosenberg, Emerson Liu, Bo Li, Ding Zhao
MLHC 2022
[paper]

Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables
Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao
AISTATS 2023
[paper] [code]

Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction
Jiacheng Zhu*, Jielin Qiu*, Zhuolin Yang, Michael Rosenberg, Emerson Liu, Bo Li, Ding Zhao
ICLR 2022 Workshop on Socially Responsible Machine Learning (SRML)
[paper]

Comparing Recognition Performance and Robustness of Multimodal Deep Learning Models for Multimodal Emotion Recognition
Wei Liu, Jielin Qiu, Wei-Long Zheng, Bao-Liang Lu
IEEE Transactions on Cognitive and Developmental Systems 2021
[paper] [code]

Visual Sequence Learning in Hierarchical Prediction Networks and Primate Visual Cortex
Jielin Qiu, Ge Huang, Tai Sing Lee
NeurIPS 2019
[paper]

Investigating Sex Differences in Classification of Five Emotions from EEG and Eye Movement Signals
Lan-Qing Bao, Jielin Qiu, Hao Tang, Wei-Long Zheng, Bao-Liang Lu
EMBC 2019
[paper] [code]

Multi-view Emotion Recognition Using Deep Canonical Correlation Analysis
Jielin Qiu, Wei Liu, Bao-Liang Lu
ICONIP 2018
[paper] [code]

Services

  • Area Chair: ACL Rolling Review (ARR)
  • Conference Reviewer: ICML, NeurIPS, ICLR, CVPR, ECCV, ICCV, WACV, ACL Rolling Review (ARR), ACL, EMNLP, EACL, AAAI, ACM MM, KDD, AISTATS, ICASSP, CHIL, MICCAI, MLHC
  • Journal Reviewer: Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Transactions on Machine Learning Research (TMLR), Journal of Data-centric Machine Learning Research (DMLR), IEEE Transactions on Neural Networks and Learning Systems.
  • Committee: NeurIPS 2022 virtual deep-dive session chair, CMU RISS Committee.

    		•

    Teaching

  • Teaching Assistant of CMU 16-824 Visual Learning and Recognition, Instructor: Prof. Jun-Yan Zhu, Fall 2021
  • Teaching Assistant of CMU 11-777 MultiModal Machine Learning, Instructor: Prof. Yonatan Bisk, Spring 2021

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