Resume-aware faculty matching

Find professors who actually fit you

Upload your resume. Four AI agents analyze your background, rank the faculty who fit, inspect their recent research, and help you draft outreach — grounded in their actual work, not templates.

Free to startNo credit cardCancel anytime
Top matches Balanced preset
Dr. Sarah Chen
Stanford · Interpretability · NLP
91
Dr. Marcus Holloway
MIT · Robotics · RL
84
Dr. Aisha Okonkwo
CMU · Fairness · HCI
82
Nova · Professor Researcher · re-ranking top 20…
Stanley Qi

Stanley Qi

· Associate Professor of Bioengineering and, by courtesy, of Biomedical Data ScienceVerified

Stanford University · Bioengineering

Active 2006–2024

h-index14
Citations723
Papers314 last 5y
Funding
See your match with Stanley Qi — sign in to PhdFit.Sign in

About

Stanley Qi is an Associate Professor of Bioengineering and, by courtesy, of Biomedical Data Science at Stanford University. He is a pioneer in the field of genome engineering and the architect of foundational technologies that transitioned CRISPR from a 'cutting' tool into a universal platform for Programmable Biology. As the inventor of CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa), Qi established the first methods for the precise, reversible, and targeted regulation of the human genome without altering the DNA sequence. His lab integrates scalable genomic perturbation with live-cell and super-resolution imaging and computation-guided design to redefine cellular control boundaries. Under his leadership, the group has expanded the genome engineering toolbox, evolving CRISPR into a multidimensional platform for controlling dynamic and spatial cell states, including technologies for epigenetic editing, multiplexed transcriptome regulation, programmable 3D genome organization, and spatial RNA control. His work includes pioneering real-time visualization of chromatin dynamics and RNA in living cells, providing insights into fundamental control principles of life. The lab's technology has moved into clinical testing, with a compact epigenetic editor currently in first-in-human trials for FSHD muscular dystrophy, exemplifying the lab's mission to translate engineering into next-generation therapeutics. Beyond single-cell control, his lab is developing frameworks for synthetic cell–cell communication, focusing on immune-neuronal interactions, aiming to uncover general rules linking molecular programs to systems-level physiology through the integration of computational design and experimental biology. Qi is a Chan Zuckerberg Biohub Investigator and an Institute Scholar at the Sarafan ChEM-H, committed to shaping the future of human genome engineering.

Research topics

  • Computer Science
  • Machine Learning
  • Natural Language Processing
  • Artificial Intelligence
  • Biology
  • Pharmacology
  • Internal medicine
  • Immunology
  • Cancer research
  • Chemistry
  • Intensive care medicine
  • Medicine
  • Biochemistry
  • Cell biology

Selected publications

  • Reinforced Multi-teacher Knowledge Distillation for Unsupervised Sentence Representation

    Lecture notes in computer science · 2024-01-01 · 1 citations

    book-chapterSenior author
  • eMoCo: Sentence Representation Learning With Enhanced Momentum Contrast

    2022 · 1 citations

    1st authorCorresponding
    • Computer Science
    • Computer Science
    • Artificial Intelligence

    Sentence representation learning can transform sentences into fixed format vectors, and provides foundation for downstream tasks such as information retrieval, semantic similarity analysis, etc. With the popularity of contrastive learning, sentence representation learning has also been further developed. At the same time, contrastive learning method based on momentum has achieved great success in computer vision. It solves the coupling between negative samples and batch size. But its expected performance is not observed in natural language processing tasks because the combination of data augmentation strategies is weak, and it only utilizes the samples in the momentum queue as negatives while ignoring those generated in current batch. In this paper, we propose eMoCo: enhanced Momentum Contrast to solve the above issues. We formulate a set of data augmentation strategies for text, and present a novel Dual-Negative loss to make full use of all negative samples. Extensive experiments on STS (Semantic Text Similarity) datasets show that our method outperforms the current state-of-the-art models, indicating its advantages in sentence representation learning.

  • CSD 1787653: Experimental Crystal Structure Determination

    The Cambridge Structural Database · 2020-09-14

    datasetOpen access

    An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

  • Targeting ROCK1/2 blocks cell division and induces mitotic catastrophe in hepatocellular carcinoma

    Biochemical Pharmacology · 2020 · 23 citations

    • Cancer research
    • Cell biology
    • Biology
  • Evidence-based Pharmaceutical Practice Responding for Novel Coronavirus Pneumonia Epidemic

    Zhongguo yaofang · 2020

    • Medicine
    • Pharmacology
    • Intensive care medicine

    OBJECTIVE:To p rovide reference for related pharmacy work for developing evidence-based pharmacy information support to respond for novel coronavirus pneumonia (COVID-19) epidemic. METHODS :The PubMed,CNKI and Wanfang database were consulted to obtain treatment progress of COVID-19,prohibited for use with lopinavir/ritonavir and adverse drug reactionas until February 12,2020;so were package insert and UpToDate at the same time. Those information were summarized and evaluated. RESULTS & CONCLUSIONS :Totally 14 literatures introduced chemical drugs for COVID- 19,involving 7 categories, 20 kinds of chemical drugs as antiviral drugs (interferon α/interferon α-2 β , lopinavir/litonavir, etc.), immunomodulatory agents (such as glucocorticoid ,gamma globulin ),antimalarial drugs (such as chloroquine phosphate ). The existing evidence of drug treatment mainly comes from in vitro cell test or currently progressing RCT ,with low-level evidence and recommendation intensity (Oxford evidence level is level 5,recommendation intensity is level D ). For lopinavir/ritonavir that recommended in the diagnosis and treatment recommendations for COVID- 19 published by the National Health Commission ,it is a CYP3A inhibitor ,which resulted in increased plasma concentrations of some medications such as antiarrhythmic drugs ,antitumor targeted drugs and antibacterial drugs ,and should not be used in combination with drugs such as afzosin ,ivabradine,amiodarone, etc. Its common adverse reactions mainly involved igestive system (diarrhea,taste disorders ,vomiting,etc.),respiratory system (upper respiratory tract infection ),endocrine and metabolic system (hypercholesterolemia,etc.),skin and its appendents (skin rash),which should be monitored clinically.

  • PET Imaging of HER2-Positive Tumors with Cu-64-Labeled Affibody Molecules

    Molecular Imaging and Biology · 2019-01-07 · 29 citations

    article1st authorCorresponding
  • Robust Corrole-Based Metal–Organic Frameworks with Rare 9-Connected Zr/Hf-Oxo Clusters

    Journal of the American Chemical Society · 2019-08-21 · 116 citations

    article

    The corrole unit from the porphyrinoid family represents one of the most important ligands in the field of coordination chemistry, which creates a unique environment allowing for the observation of unusual electronic states of bound metal cations and has shown great promise in various applications. Nevertheless, studies that directly and systematically introduce these motifs in porous crystalline materials for targeting further functionalizations are still lacking. Herein, we report for the first time the construction of two robust corrole-based metal–organic frameworks (MOFs), M6(μ3-O)4(μ3-OH)4(OH)3(H2O)3(H3TCPC)3 (M = Zr for Corrole-MOF-1 and M = Hf for Corrole-MOF-2, H3TCPC = 5,10,15-tris(p-carboxylphenyl)corrole), which are assembled by a custom-designed C2ν-symmetric corrolic tricarboxylate ligand and the unprecedented D3d-symmetric 9-connected Zr6/Hf6 clusters. The resultant frameworks feature a rare (3,9)-connected gfy net and exhibit high chemical stability in aqueous solutions within a wide range of pH values. Furthermore, we successfully prepared the cationic Corrole-MOF-1(Fe) from the iron corrole ligand, which can serve as an efficient heterogeneous catalyst for [4 + 2] hetero-Diels–Alder reactions between unactivated aldehydes and a simple diene, outperforming both the homogeneous counterpart and the porphyrinic MOF counterpart.

  • Research on industrial planning of sustainable development new town—a case study of Hengshui Lakefront New Town

    2017-03-16

    book-chapter1st authorCorresponding
  • Effect of cerium ion modifications on the photoelectrochemical properties of TiO2-based dye-sensitized solar cells

    Optical Materials · 2017-11-06 · 16 citations

    article
  • New benzoselenadiazole-based D–A–π–A type triarylamine sensitizers for highly efficient dye-sensitized solar cells

    Dyes and Pigments · 2017-02-14 · 36 citations

    article

Frequent coauthors

  • Zhen Cheng

    Chinese Academy of Sciences

    17 shared
  • Yaqing Feng

    Tianjin University

    12 shared
  • Hongguang Liu

    Heilongjiang University of Technology

    11 shared
  • Zheng Miao

    First Hospital of Jilin University

    8 shared
  • Han Jiang

    Nanjing Tech University

    7 shared
  • Paul D. Benny

    Oak Ridge National Laboratory

    5 shared
  • Yingding Xu

    Radiology Associates

    5 shared
  • Benjamin B. Kasten

    5 shared

Education

  • Ph.D., Bioengineering

    Stanford University

    2011
  • B.S., Bioengineering

    University of California, Berkeley

    2006
  • Resume-aware match score
  • Save to shortlist
  • AI-drafted outreach

See your match with Stanley Qi

PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.

  • Free to start
  • No credit card
  • 30-second signup