Robert Bardunias, MBA
Adjunct Assistant Professor | Milwaukee School of Engineering
Milwaukee, WI, UNITED STATES
Robert Bardunias is an operational, technological and financial leader with an over 20-year track record of successfully driving growth.
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Education, Licensure and Certification (4)
Certification: Artificial Intelligence and Architecture, North Carolina State University 2023
Certification: Data Scientist, North Carolina State University 2023
MBA: Zarb School of Business, Hofstra University 2008
Summa Cum Laude, Beta Gamma Sigma
B.A.: McGowan School of Business, King’s College 1998
Biography
Robert Bardunias is an operational, technological and financial leader with an over 20-year track record of successfully driving growth. His areas of expertise are strategic partnerships, operations management, corporate development, M&A, adoption of new technologies, and operational integrations. Robert is also interested in innovative initiatives to expand the scope and enhance profitability of global business operations.
Areas of Expertise (5)
Operational Integrations
Operations Management
Market Analysis
Strategic Partnerships
Corporate Development
Accomplishments (1)
Beta Gamma Sigma - MBA Honor's Fraternity (professional)
2006 Hofstra University
Affiliations (2)
- Boy Scouts of America : Executive Board Member - Three Harbors Council
- Wisconsin Veterans Chamber of Commerce : Advisor
Media Appearances (3)
Restaurants Take Heed: Uber Eats May Soon Own Your Relationship with Customers
FSR Magazine online
2020-05-13
With fresh news that Uber Technologies, Inc. is in advanced talks to acquire Grubhub Inc., restaurant owners who outsource delivery should be warned: The risk of a third-party platform effectively owning the relationship with your customers just increased. Dramatically.
MBPT Spotlight: Please Shut Up About Millennials Cord Cutting
Broadcasting & Cable online
2015-04-24
We sure do love our buzzwords; they have their time and place, and can be effective when used properly. But when it comes to digital video and the usage of "cord cutting," I just want to bloody scream! Not a frustrated, just-missed-the-last-train scream; I'm referring to a blood-curdling psycho scream. Yes, we love our buzzwords, but when we use them without considering the economic inference to industry, we’re left looking quite dumb.
Ad Fraud and Advertisers: Time to Pick Your Poison
Huffington Post online
2014-11-19
Programmatic technology is the ultimate key to enabling the fight against ad fraud, click fraud, and most importantly, consumption fraud. Without embracing Programmatic's role in delivering content, the digital advertising industry will be setting itself up for failure.
Patents (4)
Delivery management system with integrated driver management and scheduling
US20220092520A1
2022-03-24
A method including receiving a digital schedule, the digital schedule including one or more shifts, each of the one or more shifts including at least one opening, execute a machine learning model using the digital schedule to generate demand characteristics associated with the digital schedule, the demand characteristics including (i) a number of drivers and (ii) driver characteristics associated with the number of drivers, parsing a database including a plurality of digital representations of drivers to identify a selection of drivers having the driver characteristics, automatically assigning the selection of drivers to the one or more shifts of the digital schedule according to the demand characteristics, monitoring completion of at least one shift of the one or more shifts to measure a key delivery parameter associated with each delivery, and updating the machine learning model.
Delivery management system with integrated driver declaration
US20220092521A1
2022-03-24
One or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to receive a digital task assignment including a user identifier and an indication of one or more required declarations associated with the task assignment, wherein the digital task assignment is locked by a digital flag, generate and transmit a digital declaration based on the indication to a user device associated with the user identifier, wherein the digital declaration includes one or more conditions, receive a modified digital declaration from the user device, perform semantic extraction on the digital declaration to validate a user response to the one or more conditions, and in response to validating the user response to the one or more conditions, update the digital task assignment by modifying the digital flag to unlock the digital task assignment.
Delivery management system with integrated worker management and scheduling
US20220092519A1
2022-03-24
A method including receiving a digital schedule associated with an entity, the digital schedule including one or more shifts, each of the one or more shifts including at least one opening having an assigned individual with a specific role, retrieving context information associated with a location of the entity, executing a machine learning model using the context information to generate a predicted demand associated with the entity during a time period corresponding to the one or more shifts, updating the digital schedule based on the predicted demand, monitoring completion of the at least one shift to measure an actual demand associated with the entity, and updating the machine learning model based on the actual demand.
Delivery system including fleets and driver-specific capabilities
US20220092516A1
2022-03-24
One or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to receive one or more delivery parameters describing characteristics associated with a task type, wherein the one or more delivery parameters include at least one key parameter, receive task information for a specific task of the task type, wherein the task information includes a location, execute a machine learning model specific to the at least one key parameter using the task information to generate a delivery assignment for the specific task, the delivery assignment including an identifier identifying an individual, monitor completion of the specific task by the individual, wherein monitoring completion of the specific task includes monitoring the at least one key parameter, and update the machine learning model based on monitoring the at least one key parameter.
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