working experience

data science

experience

tech

portfolio

mobility, numeric
e-commerce, advertising

Dr Giovanni Marelli

Numerics - simulations




Research assistant 06-12

Signal theory

C++, qt graphic libraries

Studies and programming

LaTeX, fortran, c++

solid state

Monte Carlo simulations, openGL, c++

viral fusion

fusion pathway and activation probability for viral fusion

Molecular dynamics

Force decomposition, parallel high performance software, openMP, MPI

inclusion objects

event collection
Monte Carlo, Configurational Bias, Widom insertion. C++, openGL, CGAL

numeric calculation

event collection
Finite differences, 4th order 2d differential equation with boundary conditions

Lectures

event collection
Statistical mechanics, biophysics exercises

Enterprise planning


Data consultant 13-14

Offgrid electrification

php-mysql forms, R scripts

Databases - forms

php-mysql, spss, gtk

ERP CRM inventory

openErp, odoo, postres

webapp - portals

openLayers, facebook connector

apps

Android studio, cordova

electric violins

arduino, teensy, openFrameworks

creative coding - arduino

openCV, openGL, openFrameworks, processing, arduino

d3 data visualization

data visualization and dashboards with d3.js

conversion uplift



A/B tests, conversion uplift

Frankfurt

Data scientist 14-15

personalization

maxymiser, tealium

a/b testing

monitoring a/b tests

text mining

NLP, stemming, classification

customer feedback

Sentiment, promoter score, personas

tracking

webtrends, tealeaf, tealium, maxymiser

targeted advertising





look alike, conversion uplift

Milano

Sr Data Scientist 16-17

audience affinity

R, clustering, labelling

geodata

weblogs, geographical classification

time series

arma, exp decay, periodic decomposition

forecast

event collection
Forecast on signal components

socio demo

verticality, crm data

data pricing

costs and performances

data visualization

data exploration with d3.js

taxonomy

content classification

time series dashboard

highcharts, html, css

audience offer

presenting a large number of targets

tracking

dmp, dsp, ssp, ad server, census

page labelling

content analysis, loop-ai, admantix

Mobility - transportation




movement patterns, commercial capture rate

Berlin

ML Expert 17-19

event collection

event collection
We collect an handover between cells per device (D1-Netz)

Events to movements

event collection
We groups events into activities and trips

Activity probability

event collection
triangulation, signal cleaning

Daily patterns

event collection
train on census data

Tourist patterns

event collection
BI tools, tibco, tableau

age, gender, device types

event collection
tibco

movements across the country

event collection
kepler.gl

origin destination matrices

event collection
important for local transportation companies

routing/infrastructure

event collection
we work on an efficient routing and infrastructure

local network

event collection
Special modules consider city centers

subway module

event collection
Distinguish the mean of transportation labelling cells (training data)

subway passangers

event collection
Collecting information about commuters

Intensity of activities

event collection
Activity intensity: breaks of motorway drivers

collect important features

event collection
we select the most relevant features

training set

event collection
geographical information to train system

classification

event collection
We train our models to predict important features

compare external sources

event collection
Public information from different sources

capture rate

event collection
Calculate the coverage of a commercial activity

whitespot analysis

event collection
Customer potential on regions not covered within a isochrone

time dependent data

event collection
Weather/time dependent data

geo static information

event collection
Predict absolute values

learning process

event collection
Scoring, cross validation, classification

evaluate data and time series

event collection
Series clustering, distribution, class stability

Shared mobility




demand prediction, fleet optimization

Berlin

AI lead 19-20

demand - offer areas

event collection
Activation, revenues, app opening, errors

location intelligence

event collection
Spot the relevant geo data for predictions

motion patterns

event collection
Start, end, route, deviations, graphs

fleet dispatch

event collection
optimization engine for fleet dispatch

graph routing

event collection
from street network

ai - reinforcement learning

event collection
reinforcement learning to tune the simulation

infrastructure design

event collection
microservice based, parallel, asynchronous

frontend

event collection
interaction frontend, ui interaction with the solution

documentation libraries

event collection
documentation libraries

Resources

dauvi

github

linkedin

antani

intertino

geomadi