Gokay

Building Automation Systems for Science

Software engineer and scientist. I build hardware-software automation, control systems, data pipelines, and AI systems that power modern scientific manufacturing.

About Me

I am a software and automation engineer with a PhD in science. My focus lies at the intersection of physical science, hardware control, and distributed software systems, building the core infrastructure that powers scientific manufacturing and automated laboratory R&D.

My work spans developing real-time instrument control software, designing high-throughput data pipelines, and integrating complex physical hardware into reliable, scalable production workflows — increasingly with AI and machine learning as the decision layer on top.

$1.5M+

Annual Savings from Automated Inspection

Saved via custom vision & AI defect detection systems

100+

Data Sources Integrated

Raw data streaming to S3 & Snowflake

35 TB

Data processed

High-volume manufacturing telemetry processed end-to-end

36+

Apps Shipped

Zero-setup executables auto-updated across hundreds of endpoints

250K

Images Inspected Annually

6 OpenCV systems replacing manual pass/fail review

25+

Hardware Interfaces Built

Across 12 instrument types via serial, Ethernet, VISA & GenICam

Technical Capabilities

Languages & Frameworks

PythonTypeScript/ReactSQLBash/LinuxVBA

AI & Computer Vision

PyTorchYOLOOpenCVMachine LearningApplied AIComputer VisionObject DetectionSegmentation

Data & Infrastructure

SnowflakeAWSTerraformDockerPostgreSQLGitHub Actions CI/CDSentryTableau

Hardware & Lab Systems

SCADAIgnitionMotion Control SystemsRobotic Liquid Handlers

Experience & Key Achievements

10X Genomics

Senior Automation EngineerCurrent Position

2024 — Present

Automation Engineer III

2022 — 2024

PythonComputer VisionMachine LearningPyTorchOpenCVApplied AIAWSSnowflakeISO-9001

Saved $1.1M annually and eliminated scrap (2.21% → 0%) by leading a team of 3 engineers to build and deploy an end-to-end PyTorch AI training and image-labeling framework (YOLO-based classification, detection, and segmentation) across multiple automated inspection workflows.
Partnered with manufacturing operators and engineers to build and deploy a manufacturing execution system (MES) for Atera optics subassemblies, featuring hardware-integrated GUIs that guide operators through assembly and QC for 5–6 instruments per week; replaced manual screenshot recordkeeping with automated data capture, ensuring per-unit traceability and preventing errors via step interlocks.
Built 6 classical image analysis and statistical inspection systems using OpenCV that process ~250K images per year across microscopy, laser profilometry, and other instruments, replacing manual analysis with ISO-9001-compliant, operator-free pass/fail dispositions.
Built Python hardware interfaces and a shared abstraction layer that automated device discovery and connection for ~25 devices across 12 instrument types via serial, Ethernet, VISA, and GenICam, laying the automation foundation for the MES and automated inspection workflows.
Collaborated with manufacturing managers across the US, Singapore, and Taiwan to architect data pipelines centralizing ~10–15 TB per year of manufacturing data from 100+ sources into AWS and Snowflake, replacing siloed files and manual spreadsheet-based investigation with real-time director-level dashboards and cross-site QC image review to drive production planning, AI-driven improvement opportunities, and troubleshooting.
Built a zero-setup executable build system with PyInstaller and GitHub Actions that packaged and auto-updated ~3 dozen internal Python applications (operator GUIs, automation scripts, and lab tools) across hundreds of endpoints including operator laptops, lab computers, shared devices, and manufacturing stations, with Sentry error telemetry and role-based access control (RBAC) across the company.
Built a broad portfolio of internal software — local Python GUIs, web apps, Tableau dashboards, and utility tools — used across manufacturing to support day-to-day operations.
Served as the Functional Lead for the AI LEAP Kinetic Core, setting company-wide artificial intelligence strategy and driving applied-AI initiatives across the organization.

Emerald Cloud Lab

Scientific Infrastructure Engineer II

2021 — 2022

Scientific Developer I

2020 — 2021

Automated WorkflowsNIST/GLPInstrument ControlRoot-Cause AnalysisLab AutomationRobotic Liquid Handling

Served as the sole overnight infrastructure engineer for a cloud lab of 120+ instruments including DNA/peptide synthesizers, HPLCs, robotic liquid handlers, mass spectrometers, NMRs, and plate readers, diagnosing systemic errors and implementing hardware, software, and procedural fixes.
Built a root-cause tracking system that logged each failure's cause, recurrence frequency, and time-to-permanent-fix, driving measurable improvements in the reliability, reproducibility, and efficiency of experiments, instruments, and the codebase.
Fielded user reports across software, hardware, and scientific domains — investigating root causes, delivering timely fixes, and advising scientists on the ECL software suite.
Contributed to the ECL cloud lab's experiment automation system, building chemical and biological assay workflows with automatic parameter optimization from user input and instrument constraints, real-time data analysis, and graphing that enabled scientists to run experiments remotely without manual instrument setup.
Engineered the instrument control and compliance layer with hardware/software interfaces, automated NIST/GLP qualification tests, and automatically triggered maintenance protocols such as part replacements and container parameterization, keeping the cloud lab operational and audit-ready.

Northwestern University

Graduate Research Assistant

2013 — 2020

High-Throughput ScreeningMachine LearningNanomedicineSNAsImmunologyVaccine DevelopmentIn Vivo Studies

Screened a 3,000-member spherical nucleic acid nanoparticle (SNA) library for immune activation — yielding design rules for SNA-based cancer vaccines — by building an end-to-end high-throughput synthesis and machine-learning pipeline and leading a team of 4 scientists.
Secured $11.7M in NIH funding for a cancer nanotechnology center with faculty and postdocs, then coordinated research and data collection across 7 partner labs and reported progress to the agency.
Led development of biocompatible SNA constructs that cross ocular barriers to treat retinal disorders, coordinating the legal contracts and IACUC approvals required to engage a contract research organization (CRO) for in vivo studies.
Directed a team of 5 scientists developing immunomodulatory SNAs as vaccines targeting melanoma, prostate cancer, and influenza.
Mentored 11 trainees: 5 PhD students, 1 MD student, 1 master's student, 3 undergraduates, and 1 research technician.

Education

Honors & Awards

Awarded to employees who embody the culture principle of "we strive for exponential impact"

Awarded to employees who embody the culture principle of "we are mission driven and stay relentlessly focused on that mission."

Awarded yearly to the best doctoral thesis in an academic year in Interdisciplinary Biological Sciences.

Awarded for exceptional contributions to the broad field of nanotechnology.

Awarded to outstanding graduate students dedicated to the exploration of fundamental nanoscale science and to advancing this knowledge into practical applications of benefit to society.

Awarded to graduate students who work across disciplinary boundaries of chemistry and biology to address the big problems in biomedical research.

Patents

Hairpin-like oligonucleotide-conjugated spherical nucleic acidGranted
Mirkin CA, Yamankurt G, Vasher MK
U.S. Patent No. 12,702,719
Rational vaccinology for prostate cancer using spherical nucleic acidsApplication
Mirkin CA, Chen P, Dominguez DS, Huang Z, Lee A, Qin L, Skakuj K, Teplensky MH, Wang S, Yamankurt G, Zhang B
U.S. Patent App. No. 17/766,801 (PCT App. No. PCT/US2020/055047, Pub. No. WO2021072124)
Addressing nanomedicine complexity through novel high-throughput screening and machine learningApplication
Mirkin CA, Mrksich M, Lee A, Bagheri N, Yamankurt G, Berns EJ, Xue A
U.S. Patent App. No. 17/046,511 (PCT App. No. PCT/US2019/027229, Pub. No. US 2022/0056220 A1)
Structure-function relationships in the development of immunotherapeutic agentsApplication
Mirkin CA, Wang S, Yamankurt G, Skakuj K, Lee A, Qin L, Zhang B
U.S. Patent App. No. 16/954,198 (PCT App. No. PCT/US2018/065765, Pub. No. US 2023/0381306 A1)
Therapeutic effects of cellular delivery of small molecules and macromolecules with liposomal spherical nucleic acids.Application
Mirkin CA, Yamankurt G, Wertheim JA, Cole L, Ferrer JR, Guan CM
U.S. Patent App. No. 16/334,312 (PCT App. No. PCT/US2017/052318, Pub. No. WO 2018/057529)

Selected Publications (4 of 11)

2022
Journal of the American Chemical Society
Hairpin-like siRNA-based spherical nucleic acids
Vasher MK, Yamankurt G, Mirkin CA
2020
Proceedings of the National Academy of Sciences
The effector mechanism of siRNA spherical nucleic acids
Yamankurt G, Posedas DM, Stawicki RJ, Carthew RW, Mirkin CA
2019
Nature Biomedical Engineering
Exploration of the nanomedicine-design space with high-throughput screening and machine learning
Yamankurt G*, Berns EJ*, Xue A, Lee A, Bagheri N, Mrksich M, Mirkin CA
2019
Proceedings of the National Academy of Sciences
Rational vaccinology with spherical nucleic acids
Wang S*, Qin L*, Yamankurt G, Skakuj K, Huang Z, Chen PC, Dominguez D, Lee A, Zhang B, Mirkin CA