CV

1. @gmachiraju
Gautam Machiraju
1190 Mission St. Apt 1811
San Francisco, CA 94103
614.599.6288 | gmachi@stanford.edu
Education
University of California, Berkeley August 2012 - May 2016
B.A. Applied Mathematics (Concentration: Mathematical Biology)
Minor: Bioengineering
Mathematics Physical Sciences Computer Science
Calculus I General Chemistry + Lab Scientific Programming
Calculus II Organic Chemistry + Lab Comp Sci Fundamentals
Multivariable Calculus Mechanics Physics + Lab Data Structures
Diff Eqs & Linear Algebra I E&M Physics + Lab Database Systems
Linear Algebra II
Discrete Mathematics Biological Sciences Business
Abstract Algebra Molecular & Cell Biology + Lab Health-tech Entrepreneurship
Numerical Analysis I Microfluidic Design Management of Tech Innovation
Numerical Analysis II Biophysical Chemistry
Real Analysis Bionanotechnology
Complex Analysis Synthetic Biology
Statistical Theory Computational Biology
Mathematical Biology
R&D Experience
Bioinformatics Research Assistant September 2016 - Present
Stanford University School of Medicine | Palo Alto, CA
• Supervisor: Dr. Parag Mallick [Mallick Lab, Department of Radiology, Canary Center at Stanford
for Cancer Early Detection]
• Utilization of integrative, multi-omics approaches to model the processes that govern proteome dy-
namics; subsequently use those models to discover cancer biomarkers and mechanisms
1. Mathematical models of biomarker shedding kinetics in early-stage, solid tumors via numerical
methods; generating parameter estimators using linear classification (e.g. LDA) of proteomic
features and tuning through time-series in vivo histopathology
– Collaborators: Stanford Radiology (Dr. Sharon Hori, Dr. Ramasamy Paulmurugan, Dr. Sanjiv
Sam Gambhir), University of Louisville (Dr. Hermann Frieboes)
– Publication: A lightweight, generalized biomarker shedding model for solid tumors in pursuit of
early detection metrics (in preparation → PLOS Computational Biology)
2. Big-data mining and NLP of in-text (PubMed) biomarker dark data to construct trained gen-
erative and discriminative learning models, as well as Markerville, a user-friendly web-hosted
database; mentored 5 interns to compete in Siemens Competition
– Collaborators: Stanford Info Lab (Alexander Ratner, Dr. Stephen Bach, Dr. Christopher R´e)
– Publication: Markerville: a web-hosted biomarker database constructed from big-data literature
extraction using Snorkel (in preparation → Bioinformatics)
3. Deep-learning of multi-omic (transcriptomic, metabolomic, wearable-tracked physiologic, etc.)
time-series patient data to determine systemic perturbations to circadian rhythm and baseline
health signatures
– Collaborators: Duke (Dr. Ricardo Henao), CMU (Dr. Ruslan Salakhutdinov, Dr. Aarti Singh),
Northeastern (Dan Guo, Dr. Olga Vitek), DARPA
• Languages: Python, R, MATLAB, C++, CUDA, JavaScript, Node.js, CSS/HTML, NoSQL (Mon-
goDB), SQL (PostgreSQL, MySQL)

2. Bioengineering (Software) Intern June 2016 - September 2016
Transcriptic | Menlo Park, CA
• Supervisors: Dr. Peter Lee, Yang Choo
• Cloud-based, biological laboratory automation; software engineering for the Bioengineering team and
members of the technical staff
• Contributed to development of interface infrastructure, back-end job-tree algorithms, bacterial plate
spread coverage optimization (multivariate constrained minimization), R3
Euclidean space coordinate
mapping for device drivers, and experimental analysis: assay design (KingFisher DNA purification),
autoprotocol software implementation, robot job builds and kickoffs, and QA/QC for assays, proto-
cols, and instrumentation
• Languages: Python, Scala
Undergraduate Researcher September 2015 - September 2016
Center for Computational Biology, UC Berkeley | Berkeley, CA
• Supervisor: Dr. Ian Holmes [Holmes Lab, Department of Bioengineering]
• Mathematical models of genetics, annotation of DNA sequence data, sequence alignment algorithms,
and bioinformatics software engineering
• Worked to determine PHRED quality score distributions for the Oxford Nanopore MinION Sequencer
by conducting a comparative algorithmic study of quaff, an in-house aligner specializing in MinION
sequence data using HMMs and ML, against other popular aligners run on MinION sequence data;
development of shell scripts and wrappers for performance study batch runs
• Languages: Python, UNIX/Bash
Undergraduate Researcher April 2013 - September 2015
Lawrence Berkeley National Laboratory | Berkeley, CA
• Supervisors: Dr. John Tainer (Scripps Institute), Dr. Robert Rambo (University of Oxford), Dr.
Gregory Hura [Tainer Lab, Advanced Light Source SIBYLS Beamline Group, Molecular Biophysics
and Integrated Bioimaging Division]
• Small-angle X-ray scattering (SAXS), when applied to enzymatic solutions, elicits conformational
changes in amino acid structure; utilization of this phenomena to study DNA repair mechanisms
• Sought to pinpoint biochemical, structural changes in SAXS data through statistical and mathe-
matical analysis such as compressed sensing, least squares techniques (e.g. L1 & L2 regularization),
dimensionality reduction methods (e.g. PCA, SVD), and other numerical methods; developed soft-
ware for protein structural similarity analysis and visualization via cubic spline interpolation and
heat-mapping
• Languages: MATLAB, C++, C
Bioinformatics Intern June 2015 - August 2015
Strand Life Sciences | Bangalore, Karnataka, India
• Supervisors: Dr. Ramesh Hariharan, Dr. Vamsi Veeramachaneni, Dr. Smita Agarwal
• Genetic profiling of patients across India, specializing in insight into rare, previously uncharacterized
diseases among homogeneous populations
• Research training focused on NGS data analysis and visualization, human genetics, alignment al-
gorithms, and data mining; studied mutations via chromosomal recombination and patient dataset
phenotypes, specifically those causing early-onset macular degeneration in Indian subpopulations
– Contributed to: Genomic Quirks: The Search for Spelling Errors
• Language: Java

3. Bioengineering Intern June 2014 - August 2014
Berkeley BioLabs | Berkeley, CA
• Supervisor: Dr. Ron Shigeta (Indie Bio)
• Accelerator enabling R&D by providing economical lab facilities and a collaborative biotech and DIY-
bio community; worked in conjunction with the Glowing Plant project, a team from the Sunnyvale-
based Biocurious hackerspace
• Worked on stable (non-transient, pre-CRISPR/Cas9 adoption) transfection via agrobacteria vec-
torization and molecular cloning techniques (restriction enzyme selection, PCR, digests, etc.) to
genetically modify Arabidopsis, Allium cepa, and Nicotiana tabacum phenotypes, aiming to express
bioluminescence synchronized with circadian rhythm
Relevant Skills
Programming Languages & Environments:
Python, Jupyter/IPython, R, MATLAB, UNIX/Bash, Java, C, C++, CUDA, Spark (PySpark), SQL
(SQLite, MySQL, PostgreSQL), NoSQL (MongoDB), Scala, JavaScript, Node.js, CSS/HTML
Computer Science, Data Science, & Software Engineering:
OOP, data structures, algorithm development, functional programming, GPU computing (paralleliza-
tion, threading), database systems, ML (K-means clustering), DL (TensorFlow), NLP, data mining/web-
scraping, big data application development (AWS EC2, Heroku), programming best practices & code
development cycle (Git, Arcanist, Phabricator, linters, pep8, tox testing, Jenkins builds, etc.)
Mathematical Analysis:
Statistical analysis (regression, hypothesis testing, bootstrap, etc.), optimization methods, numerical meth-
ods (approximation theory, fitting, interpolation, ODE & PDE solving, sensitivity analysis, iterative matrix
algebra, dynamical system solving, FFT, quadrature, gradient descent, etc.), linear algebraic analysis &
dimensionality reduction (regularization, compressed sensing, LDA, SVD, PCA, etc.)
Bioinformatics:
Biopython, Bioconductor, sequence alignment (BWA, LAST, marginAlign, etc.), sequence assembly (SPAdes,
Velvet, DNASTAR, etc.), BLAST, Clustal suite, Se-Al, PyMOL, SnapGene, MrBayes, analysis workflows
(WINGS & Galaxy)
Modeling & Design:
AutoCAD, COMSOL, Adobe Illustrator & InDesign, LATEX
Wet Laboratory:
Liquid handling (pipetting, serial dilution, titration, etc.), microscopy, dissection, ImageJ, DNA purifica-
tion (magnetic bead separation), molecular cloning (restriction enzymes, (q)PCR, digests, etc.), bacterial
plating, gel electrophoresis, microfluidic design, assay & protocol development, robotic lab automation
practices, sterile technique & regulatory compliance (BSL-{1,2})
Independent Coursework
Stanford Lagunita
• Statistics in Medicine
• Statistical Learning
• Algorithms: Design & Analysis
• Convex Optimization
Stanford Engineering Everywhere (SEE)
• Machine Learning (CS 229)
• Linear Dynamical Systems (EE 263)

4. Academic Workshops & Programs
Computational Genomics Summer Institute (CGSI) July 10 - 14, 2017
University of California, Los Angeles | Los Angeles, CA
• NIH-funded program to bring together mathematical and computational scientists, sequencing tech-
nology developers in industry and academia, and biologists who use research applications in order to
foster the development of infrastructures to meet emerging data analysis challenges
• Series of research talks, tutorials, and journal clubs to gain problem exposure in computational
genomics ranging from public health metagenomics and ancestral phylogenetics to ML techniques in
CRISPR site detection and combinatorial STR pattern matching algorithms
Mathematical Biosciences Institute (MBI) Summer Program June 2 - 13, 2014
The Ohio State University | Columbus, OH
• NSF-funded program to introduce students to mathematical biology and the interface between math-
ematics, computer science, and biology; exposed to a variety of research topics, spanning from infec-
tious pathogen dynamics to statistical phylogenetics
• Culminated in collaborative research project on linear and nonlinear dynamical systems modeling of
crustacean swimmerette motion (e.g. harmonic resonance, dampening, etc.) to explore optimized
water transport via biomimicry-inspired technology
Academic Conferences & Symposia
• Biomedical Computation at Stanford (BCATS) April 19, 2018
– Leadership: 2018 Organizing Committee Member (June 2017 - Present)
• Stanford Radiology Joint Research Retreat October 19 - 21, 2017
– Leadership: 2017 Organizing Committee Member (May 2017 - October 2017)
• DARPA Deep Purposeful Learning & Fundamentals of Complex Collectives
– Hackathon | Arlington, VA November 14 - 17, 2017
– Hackathon | Carnegie Melon University May 22 - 24, 2017
– Kickoff Meeting | Arlington, VA January 24 - 26, 2017
• Center for Computational Systems Biology (CCSB) Symposium May 5, 2017
– Poster: Mathematical model of tumor cell heterogeneity and biomarker shedding origins
• Canary Symposium May 3, 2017
– Poster: Mathematical model of tumor cell heterogeneity and biomarker shedding origins
• Biomedical Computation at Stanford (BCATS) April 10, 2017
– Poster: Mathematical model of cancer heterogeneity and biomarker shedding kinetics
Entrepreneurial Experience
Co-founder January 2015 - May 2017 (hiatus)
Aera Devices, Inc. | Berkeley, CA
• Co-founders: Sara Kianian (Apple), Jesse Zhang (UC Berkeley-UCSF Bioengineering PhD program)
• A pulmonary diagnostic company looking to develop a globally-affordable, disposable, off-the-grid,
and non-invasive microfluidic platform and diagnostic device that allows for the early detection of
COPD via sputum-based biomarkers and small molecules (in the form of exhaled breath condensate)
with a colorimetric output

5. Incubator Member
CITRIS Foundry | Berkeley, CA January 2017 - May 2017
• Instructors: Naeem Zafar (Sutardja Center), Ikhlaq Sidhu (Sutardja Center)
• Management of Technology Innovation (MTI) Program — a masterclass, boot-camp, and incubator
for UC Berkeley graduate and post-doctoral students across all disciplines to translate technical work
into value as new ventures or in industry settings; in collaboration with the College of Engineering,
Haas School of Business, Center for Information Technology in the Interest of Society (CITRIS), and
NSF I-Corps Program
• Focused on market research, needs analysis, investor pitching, product development & management,
QA, customer validation, identifying an MVP, business plans, financial projections, G2M entry time-
lines, unit economics, equity & liquidation
• Our startup, Aera Devices, was accepted as a top 5 (Track I) team with additional seed funding;
competed for VC prizes at a final pitch competition
Incubator Member
Free Ventures | Berkeley, CA Jan 2015 - May 2015
• Mentors: Dr. Paul Wolters (UCSF), Dr. Shyam Patel (UCB)
• Free University early-stage program — UC Berkeley’s student-run startup accelerator, providing
weekly sprint sessions with advisors, mentors, and incubator members, as well as resources to get
ideas off the ground
• Competed in the Pejman-Mar Ventures (now Pear Ventures) Berkeley Startup Challenge for $250K,
placing as semi-finalists
• Worked further on our startup company, Aera Devices; incorporated with WilmerHale (state of
Delaware) and received provisional patent support from UC Berkeley School of Law (Boalt)
Incubator Member
Catalyst@Berkeley | Berkeley, CA September 2014 - December 2014
• Mentors: Dr. Paul Wolters (UCSF), Dr. Shyam Patel (UCB)
• A student-run health-tech incubator that strives to develop viable biotechnological prototypes along-
side a business plan to bring them to the market
• Formed Aera Devices, a pulmonary diagnostic startup (see above); provided with seed funding for
early design engineering and proof of concept
Hackathons
AT&T Silicon Valley Hackathon, 2016
Our team built a functional iOS crowd-sourcing DJ app that (1) aggregated SMS texts from the crowd
(Twilio) onto a cloud DB platform (Heroku), (2) employed sentiment analysis on SMS texts (IBM Bluemix),
(3) visualized R-B LED gradient based on sentiment (Raspberry Pi), and (4) suggested adapted playlist
to the DJ
Cal Hacks, 2016
Our team designed an iOS app to supplement the popular Assassins tagging game; began building off of
the Google Maps API while learning basic Swift and iOS design