Problems solved leveraging math. Career advice. Overviews of big data definitions.

1. APPLICATIONS OF MATH IN DATA
SCIENCE
COLLEEN M. FARRELLY, DATASEMBLY/STATICLYSM

2. MY CAREER PATH
• Sports patterns and translating paintings
to pots
• Focused on genetics/neuropsychology in
undergrad
• Quantitative MD/PhD student who started
going to geometry/topology workshops
• Switched to an MS in Biostatistics after
taking the GRE subject exam
• Graduate papers in structural equation
modeling and topology/machine learning
• 10+ years of consulting and working full-
time in industry data science
• Military, healthcare, biotech, education,
marketing, supply chain, consumer goods…

3. BIG DATA
• Volume, variety, veracity,
velocity
• Examples:
• Wide data that breaks
statistics
• Knitting together multiple
sources with different types
of data formats
• Non-independent data
• Text/image data

4. EXAMPLE PROBLEMS IN DATA SCIENCE

5. ANALYZING SURVEYS WITH FLAT DESIGNS
• Surveying identity
expression across
social contexts
• No hierarchical
structure to allow
factor-analysis-
based solutions
• Very small sample
sizes in different
population groups
without evidence of
population similarity

6. ANALYZING SURVEYS WITH FLAT DESIGNS
• Similar
construct to
gene expression
panels across
time
• Single-linkage
hierarchical
clustering
solution
• Problem of
statistical
comparison of
ILLCa_school_success_family
ILLCa_school_success_school
ILLCa_gender_dating
ILLCa_age_dating
ILLCa_age_freetime
ILLCa_sexual_or_dating
ILLCa_beauty_dating
ILLCa_sport_dating
ILLCa_sport_freetime
ILLCa_sport_religion
ILLCa_religion_freetime
ILLCa_religion_family
ILLCa_religion_school
ILLCa_religion_neighborhood
ILLCa_politics_dating
ILLCa_religion_group
ILLCa_sexual_or_religion
ILLCa_gender_religion
ILLCa_age_religion
ILLCa_politics_religion
ILLCa_politics_family
ILLCa_politics_neighborhood
ILLCa_politics_group
ILLCa_politics_school
ILLCa_politics_freetime
ILLCa_tribe_dating
ILLCa_tribe_group
ILLCa_tribe_freetime
ILLCa_tribe_family
ILLCa_tribe_school
ILLCa_tribe_neighborhood
ILLCa_tribe_religion
ILLCa_beauty_neighborhood
ILLCa_look_neighborhood
ILLCa_school_success_religion
ILLCa_look_religion
ILLCa_music_neighborhood
ILLCa_race_religion
ILLCa_status_religion
ILLCa_beauty_religion
ILLCa_religion_religion
ILLCa_religion_dating
ILLCa_race_school
ILLCa_race_freetime
ILLCa_sexual_or_school
ILLCa_beauty_family
ILLCa_beauty_freetime
ILLCa_beauty_school
ILLCa_beauty_group
ILLCa_look_freetime
ILLCa_look_family
ILLCa_look_school
ILLCa_status_dating
ILLCa_status_group
ILLCa_race_group
ILLCa_race_dating
ILLCa_sexual_or_group
ILLCa_sexual_or_freetime
ILLCa_gender_freetime
ILLCa_gender_family
ILLCa_gender_school
ILLCa_age_family
ILLCa_age_school
ILLCa_school_success_neighborhood
ILLCa_race_neighborhood
ILLCa_sexual_or_neighborhood
ILLCa_status_neighborhood
ILLCa_gender_neighborhood
ILLCa_age_neighborhood
ILLCa_sport_school
ILLCa_sport_family
ILLCa_sport_group
ILLCa_music_freetime
ILLCa_music_religion
ILLCa_music_dating
ILLCa_sport_neighborhood
ILLCa_school_success_dating
ILLCa_school_success_group
ILLCa_school_success_freetime
ILLCa_music_school
ILLCa_music_family
ILLCa_music_group
ILLCa_gender_group
ILLCa_age_group
ILLCa_look_group
ILLCa_look_dating
ILLCa_race_family
ILLCa_sexual_or_family
ILLCa_status_freetime
ILLCa_status_family
ILLCa_status_school
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0
0.2
0.4
0.6
0.8
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7. ANALYZING SURVEYS
WITH FLAT DESIGNS
• Paper linking 0th dimensional
persistent homology with
single-linkage hierarchical
clustering if the distance
metrics are the same
• Similar industry problems in
education (testing designs and
validation)
• Metrics for persistence diagrams
allow for sample comparisons.

8. PREDICTING EBOLA SPREAD ON TRAVEL
NETWORKS
• Democratic Republic of Congo
(DRC) outbreak in North
Kivu/Ituri Provinces
• Jungle areas dotted with
settlements
• Data included travel routes
connecting settlements and
cases over time in each
settlement
• Travel partially do to
populations fleeing rebel attacks

9. PREDICTING EBOLA SPREAD ON TRAVEL
NETWORKS
• Graph-based approach to
create a travel network with
case-time information
• Opened up Forman-Ricci flow
to highlight changes in travel
and disease outbreak patterns
on the DRC network
• Identified areas at most risk
to position supplies (Katwa)

10. TIPPING POPULATION HEALTH BEHAVIOR
• Unhealthy behaviors in the
Naval active duty and
reservist populations
• Impacts healthcare costs and
deployment fitness of the
force
• Large population with local
social ties (units,
neighborhoods…) and not
many ties over the rest of
the population
• Another good candidate for a

11. TIPPING POPULATION HEALTH BEHAVIOR
• Identify key vertices
(bridges) in the network for
intervention
targeting/demographics
• Estimate impacts via
stochastic differential
equations (SIS model)
• Parameters taken from the
extant literature on each
behavior’s “catching”
properties

12. NUCLEAR CORE LOADING PATTERN
PROBLEM
• Reactor core
• Rod mixtures
• Influences energy field/output
• Large optimization search space
(260
)
• Qubit approach of quantum
computing/hybrid quantum
algorithms

13. NUCLEAR CORE LOADING PATTERN
PROBLEM
• Translation of problem to
quantum computer (D-
Wave)
• Ising model
• Quadratic Unconstrained
Binary Optimization (QUBO)
mapping

14. NUCLEAR CORE LOADING PATTERN
PROBLEM
• Gains from
quantum annealing
over simulated
annealing
• Viable solutions
from hybrid
algorithms
• Good quantum
annealing
performance

15. STARTING A CAREER IN DATA SCIENCE

16. CAREER ADVICE
• Demonstrated experience:
• Publications (match publication history to position needs)
• Demonstrate applications to real-world problems (projects, papers,
internships…)
• Skillsets
• Specialize (genomics, NLP, image analytics, video analytics…)
• Programming (Spark/Python/NoSQL lately)
• Cloud experience (AWS/Azure… through a conference or online class)
• Consider a short programming-heavy bootcamp
• Indeed or start-up/Angel investing repositories have good
response rates

17. HOW TO CONTACT ME 
• cfarrelly@med.miami.edu
• LinkedIn (Colleen M. Farrelly)
• Quora (Colleen Farrelly)
• Book talks (once the first book is released  )