2023–2025
Stanford
MS in Epidemiology and Clinical Research
GPA 3.86
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Stanford University
MS in Epidemiology and Clinical Research · 2023–2025 · GPA 3.86
Hi, I'm
James Guo
过仲懿
3
years of experience leading projects end-to-end
I was made in Wuxi 🇨🇳 and adopted by California 🇺🇸.
Outside of work, I love body building, swimming, and MORE on my Instagram!
2020–2023
Cornell
BS in Statistics and Biology
GPA 3.57
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Cornell University
BS in Statistics and Biology · 2020–2023 · GPA 3.57 · Dean’s List
Core coursework
18 core coursesData Science✦Statistical Modeling✦Machine Learning✦Data Visualization✦Scientific Writing✦High Performance Computing✦Data Science✦Statistical Modeling✦Machine Learning✦Data Visualization✦Scientific Writing✦High Performance Computing✦
Experience
Technical
Corcept Therapeutics
Clinical Data Management Specialist09/2026 – Present
Biostatistics Intern06/2026 – 08/2026
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Corcept Therapeutics
Redwood City, CA · 06/2026 – Present
Clinical Data Management Specialist
09/2026 – Present- Returned as a full-time employee.
- To be updated...
Biostatistics Intern
06/2026 – 08/2026- Developed strategies to match 120+ external controls from RWD using propensity score, emulating index dates and analyzing outcome with Kaplan-Meier curves, log-rank tests, and Cox proportional hazards models.
- Built and validated patient profiles across ~20 panels in Medidata Clinical Data Studio, mapping data from annotated CRFs and creating derived variables to streamline clinical trial data review.
- Developed three-tier strategies to guide the venture capital arm’s setup, analyzing SEC filings for fund size and constructed portfolios ($50M/$100M/$150M) with real-world companies across stages and deal sizes.
Admin
Oceans Beyond LLC
General Manager05/2026 – Present
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Oceans Beyond LLC
05/2026 – Present
General Manager
05/2026 – Present- Started my own small business.
Technical
W74 Advisors
Data Scientist I03/2026 – 06/2026
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W74 Advisors
Remote · 03/2026 – 06/2026
Data Scientist I
03/2026 – 06/2026- Delivered analytical and statistical solutions for client building energy optimization, owning work end-to-end from problem framing to stakeholder reporting.
- Improved model performance by 25% over baseline by benchmarking XGBoost, LightGBM, Random Forest, Transformer, and DNN architectures with Optuna-based hyperparameter tuning; final model achieved a CVMSE of ~0.2, outperforming industry.
- Used Claude Code to accelerate prototyping and maximize productivity.
Service
Santa Clara County
Election Official04/2026 – 06/2026
Details →
Santa Clara County
Palo Alto, CA · 04/2026 – 06/2026
Election Official
04/2026 – 06/2026- Worked to support the 2026 California Primary Election voting.
- Guided 200+ voters through forms, check-in, and the voting process using in-depth knowledge of voting procedures and the Disney H.E.A.R.D. model, driven by a commitment to public service.
Technical
the Gladstone Institutes
Researcher07/2025 – 04/2026
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the Gladstone Institutes
San Francisco, CA · 07/2025 – 04/2026
Researcher
07/2025 – 04/2026- Pioneered the development of an R package (permuteDE) with a permutation testing-based pipeline to reduce false positives in differential gene expression analysis in Alzheimer's disease.
- Collected and integrated 10 massive-scale public scRNA-seq datasets from Synapse to demonstrate the package's usability.
- Applied AlphaGenome to study how the MAPT gene variants might alter splicing patterns.
- Removed doublets, performed dimensionality reduction and clustering of scATAC-seq data.
- Communicated complex statistical findings and effective data visualizations clearly to diverse audiences.
Operations
Stanford Online High School
Student Life Assistant02/2024 – 01/2025
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Stanford Online High School
Remote · 02/2024 – 01/2025
Student Life Assistant
02/2024 – 01/2025- Supported various event planning such as meeting agenda, student activities, arrival/departure bus schedules, etc.
- Designed engaging slides for weekly themed class meetings.
- Maintained student records in Google Sheets, using data entry and Excel functions with strong attention to details.
Technical
Stanford University & UCSF
Graduate Student Researcher10/2023 – 06/2025
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Stanford University & UCSF
Stanford, CA · 10/2023 – 06/2025
Graduate Student Researcher
10/2023 – 06/2025- Co-mentored by Dr. Rebecca Graff at UCSF and Dr. John Witte at Stanford University.
- Conducted (1) metabolomics analyses to investigate racial disparities and (2) deep learning–driven single-cell multi-omics studies of schizophrenia and bipolar disorder in parallel.
Technical
Match Group
iOS Development Intern07/2022 – 08/2022
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Match Group
Remote · 07/2022 – 08/2022
iOS Development Intern
07/2022 – 08/2022- Revised the “Enhanced Interests” feature in SwiftUI, allowing users to personalize their tags with text and emojis for richer self-expression.
- Improved code efficiency by migrating UIKit components to SwiftUI.
Teaching
Cornell University
Undergraduate Teaching Assistant01/2021 – 05/2023
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Cornell University
Ithaca, NY · 01/2021 – 05/2023
Undergraduate Teaching Assistant
01/2021 – 05/2023- Taught a variety of courses.
- Led discussions, graded homework and assignments, held office hours, and bridged communication between professors and students.
- Maintained course materials and student records in Canvas and Gradescope.
Operations
Cornell Dining
Student Food Assistant02/2022 – 05/2022
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Cornell Dining
Ithaca, NY · 02/2022 – 05/2022
Student Food Assistant
02/2022 – 05/2022- Replenished food in the Morrison dining hall.
- Made pizzas and chow meins to feed hungry students.
- Learned about dietary guidelines and protocols.
Projects
permuteDE
Novelpermutation-based method to combat false positives
permuteDE logo
permuteDE
the Gladstone Institutes · 07/2025 – 04/2026
Differential expression analyses are susceptible to false positives. permuteDE uses permutation testing to identify which comparisons have a higher number of significant differentially expressed features than would be expected by chance.
Novelpermutation-based method to combat false positives
Technical details
- Developed the permuteDE R package, overseeing maintenance, debugging, and feature development.
- Collected and integrated eight large-scale public snRNA-seq datasets from Synapse, performing rigorous data cleaning, metadata curation, and structuring data into Seurat objects and BPCells matrices.
- Applied the permuteDE pipeline across eight datasets to demonstrate its real-world utility.
Note: Currently we are finalizing the package and analyses; permuteDE will be released upon manuscript publication.
Bitcoin Portfolio Allocation
+40%max-Sharpe lift with BTC
Bitcoin Portfolio Allocation
2026 HKU Summer Camp · 05/2026
How much Bitcoin should a moderate-risk household hold alongside an ETF portfolio? This project answers this question end-to-end: data collection, descriptive analysis, mean–variance optimization under multiple risk constraints, and a forward-looking Black–Litterman adjustment.
+40%max-Sharpe lift with BTC
Technical details
- Universe: SPY, VEU, TLT, GLD, and BTC-USD; risk-free rate built dynamically from the 3-month T-Bill (^IRX); 2,917 aligned trading days (2014-09-17 to 2026-04-21). Target client: 5–10 year horizon, long-only, no leverage, ~15% annualized vol budget.
- Computed annualized return, volatility, Sharpe, skew, max drawdown, and the full correlation matrix; estimated CAPM beta of BTC vs SPY over full / pre-2017 / post-2017 sub-samples, showing BTC's structural shift from idiosyncratic (β ≈ 0.01) to risk-asset-like (β ≈ 0.97) while pairwise correlations with every other asset stay ≤ 0.22.
- Solved six long-only mean–variance scenarios across two universes (eleven portfolios total) in cvxpy (OSQP / SCS): max-Sharpe, vol caps at 10% and 15% p.a., a daily 95% Expected Shortfall cap at 5% and a loose 25% sanity check, and a max-return BTC ≤ 10% cap.
- Implemented Black–Litterman algorithm on the post-2017 sample so the prior covariance isn't dominated by the 2017 BTC bubble: reverse-optimized the equilibrium prior from an assumed market-cap-style weight vector and imposed three views (BTC outperforms VEU by 15% p.a.; SPY earns 10% p.a.; GLD outperforms TLT by 3% p.a.), then fed posterior expected returns into a max-Sharpe optimizer.
Results
- Including BTC lifted max-Sharpe from 0.81 to 1.13 (+40%); the Vol-Cap-15% portfolio with BTC simultaneously raised Sharpe to 1.12 and improved max drawdown from -29.0% to -26.2%, while a return-only objective with a 5% ES cap permitted a 50% BTC weight (drawdown -56%) — confirming ES alone is the wrong knob.
- Recommendation: allocate 5–10% to BTC, anchored on the Vol-Cap-15% with BTC portfolio (Sharpe 1.12, max DD -26%) and independently validated by Black–Litterman, which assigned BTC ~9.5% — almost exactly the 10% cap result. Rebalance quarterly; review annually.
Deep Learning + Single-Cell Multi-Omics
ChromBPNetcell type-specific models to pinpoint causal variants
ChromBPNet Model Architecture
Deep Learning + Single-Cell Multi-Omics
Stanford University · 04/2024 – 06/2025
I joined the PsychENCODE project at Prof. Anshul Kundaje's lab. I led this project analyzing scRNA-seq and scATAC-seq multiome data from three brain regions to investigate cell type-specific chromatin accessibility and gene expression patterns underlying schizophrenia and bipolar disorder to better understand their pathogeneses.
ChromBPNetcell type-specific models to pinpoint causal variants
Technical details
- Preprocessed high-dimensional multiome data through quality control, dimensionality reduction, clustering, doublet detection, marker identification, and cell type annotation.
- Performed differential gene expression & peak accessibility analyses (pseudobulk: Wald test; single-cell: Wilcoxon + MAST) across multiple cell types.
- Trained cell type-specific ChromBPNet models to identify causal genomic variants and their downstream effects on chromatin accessibility and gene regulation.
Figure sources: Emani et al., Science 2024 · Pampari et al., bioRxiv preprint 2025 · Ameen et al., Cell 2022
Black–White Metabolomic Disparities in Prostate Cancer
MS Thesisdefended before Stanford Epidemiology faculty
PCA Incidence Rates
Black–White Metabolomic Disparities in Prostate Cancer
UCSF · 10/2023 – 06/2025
Black men face higher prostate cancer incidence and mortality than White men. This project leverages LC-MS metabolomics on a cohort of 34 men (17 Black, 17 White) from the IRONMAN Registry to characterize metabolites associated with such disparities. I presented this project as my Master's thesis.
MS Thesisdefended before Stanford Epidemiology faculty
Technical details
- Applied t-test, PCA, PLS-DA, random forest, logistic & linear regression, chemical similarity enrichment analysis, pathway analysis, and WGCNA to LC-MS metabolomics data, characterizing metabolites associated with Black-White prostate cancer disparities.
- Interpreted complex statistical findings and communicated them through clear scientific writing and effective data visualizations; defended before Stanford Epidemiology faculty and students.
Global Disparities in Central Death Rates
D3interactive dashboards
Global Central Death Rates x Developmental Indicators
Global Disparities in Central Death Rates
Stanford University · 10/2024 – 12/2024
This project visualized the interplay between life expectancy (measured by central death rates) and economic development, healthcare access, energy production, and consumption patterns.
D3interactive dashboards
Technical details
- Developed interactive data visualization dashboards (global heatmaps, cross-country correlation analyses, and time-evolving bubble charts) using JavaScript D3.
Multi-omics Alzheimer's Grant Proposal
~30professors & students presented to
Multi-Omics Factor Analysis
Multi-omics Alzheimer's Grant Proposal
Stanford University · 03/2024 – 06/2024
In this project, I practiced NIH-style grant proposal writing by developing a theoretical proposal that integrates single-cell multiomics data to investigate the molecular mechanisms using factor analysis underlying Alzheimer's Disease.
~30professors & students presented to
Technical details
- Drafted the Specific Aims section of a conceptual NIH grant proposal and presented the multi-omics factor analysis plan to ~30 professors and students.
Figure sources: Argelaguet et al., 2018 · Growing Life
Subarachnoid Hemorrhage Risk Modeling
SASOnDemand
Boxplot of Body Mass Index
Subarachnoid Hemorrhage Risk Modeling
Stanford University · 10/2023 – 12/2023
This project evaluated associations between multiple exposures (age [categorical and continuous], sex, race, and smoking) and assessed alcohol as an effect modifier of the smoking–SAH relationship.
SASOnDemand
Technical details
- Cleaned and managed case-control datasets in SAS OnDemand: resolved duplicate records, standardized missing values, and created derived variables.
- Conducted descriptive analyses (chi-square tests and t-tests) and applied univariate and multivariable logistic regression to estimate crude and adjusted odds ratios for smoking.
- Performed stratified analysis using Mantel–Haenszel testing to adjust for alcohol use as a confounder.
- Generated summary tables and data visualizations for reporting.
BOOKED — an iOS App
HMBest UI, Hack Challenge
BOOKED
BOOKED — an iOS App
Cornell University · 04/2022 – 05/2022
This project developed an iOS app to ease the booking of a study space on campus in one of Cornell's many open libraries and study spaces.
HMBest UI, Hack Challenge
Technical details
- Programmatically developed a Cornell library study room booking system iOS app by integrating UIKit, AutoLayout, Navigation, UITable & UICollectionView, MVC, Delegation, and Animation.
- Implemented GET all libraries and available rooms, POST new reservation(s), UPDATE reservation history & DELETE reservation(s) that interact with backend API using Alamofire.
- Implemented UI with designers and collaborated with backend teammates for backend requests.
Results
- Nominated as Honorable Mention for Best UI for Hack Challenge Spring 2022.
Publications
Submitted · Cell 2026
APOE4 Drives Uniquely Dysfunctional Human Microglial States in Alzheimer’s Disease.
Submitted · Nature Neuroscience 2025
APOE4 and Aβ synergize to drive neuronal network dysfunction and lysosomal-ER proteostasis dysregulation in the preclinical stages of Alzheimer's disease.
Published · AACR Special Conference: Aging and Cancer 2022
Causal effect of type II diabetes on prostate cancer in the East Asian population: A two-sample Mendelian randomization study.
In Preparation · BMC Medicine
Metabolomic Disparities Between Black and Non-Hispanic White Men with Metastatic Hormone-Sensitive Prostate Cancer: A Pilot Study.
In Preparation · Cell
Multi-modal functional genomics analysis of bipolar disorder and schizophrenia.
In Preparation · Nature Neuroscience
Preventing false discoveries in Alzheimer's disease single-cell sequencing data using permutation testing.
‡ indicates co-first authorship.
Toolbox
Languages
R
SAS
PythonJava
JavaScript
Swift
HTML
CSS
LaTeXIDEs & Editors
Jupyter
RStudio
PyCharm
VS Code
Overleaf
XcodeSAS OnDemand
EclipseCLI & Cloud
UNIX
Terminal
SSH
AWS EC2
Conda
ClaudeHigh Performance Computing
Git
GitHubOffice
MS Word
MS Excel
MS PowerPoint
MS OutlookDesign
Illustrator
Photoshop
Procreate
After EffectsSAS
SAS Certified Specialist: Base Programming Using SAS 9.4
DeepLearning.AI
Neural Networks and Deep Learning
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Structuring Machine Learning Projects
Convolutional Neural Networks
Sequence Models