ACADEMIC TRACK


Heather T. Bednarz, MS, OTR/L
Occupational Therapist
HealthPRO Heritage

 

Heather T. Bednarz, MS, OTR/L is a licensed and registered Occupational Therapist focusing on the geriatric population of northeast Pennsylvania. She has a Bachelor’s degree in Health Sciences, with a double minor in Psychology and Philosophy, and a Master’s degree in Occupational Therapy. She is a co-inventor on two patents for an adjustable wheelchair and a pressure re-distribution system. Heather was inspired to invent these devices from her career of working with people with disabilities.

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Edward T. Bednarz III, Ph.D.
Associate Professor
Wilkes University

 

Dr. Edward T. Bednarz III is an Associate Professor of Mechanical Engineering at Wilkes University in Wilkes-Barre, PA, USA. He specializes in the field of solid mechanics. Prior to joining academia, Dr. Bednarz worked for 12 years as a Senior Mechanical Engineer for the U.S. Army. Research interests include strain gage based transducers. Dr. Bednarz has been awarded five patents. He has a passion for teaching and innovating alongside his students.

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Adjustable Wheelchair and Pressure Redistribution System

Heather Bednarz is a registered and licensed Occupational Therapist who has dedicated her career to helping patients. She recognized a need for a continuously adjustable wheelchair system that would replace many discrete sizes of wheelchair widths currently on the market. Along with husband, Edward Bednarz, who is an Associate Professor at Wilkes University, and Mechanical Engineering students, a product was developed and patented to accomplish this goal.

Similarly, Heather, Edward and another group of students invented a pressure redistribution system that can be used on wheelchairs and other devices. The goal of this product is to alleviate pressure ulcers by actively monitoring and repositioning patients who are prone to sitting in one position for extended periods of time. This product was also developed and patented.

The co-inventors, who are also business partners, are actively looking to sell both patents to companies. Their dream is to see these products mass produced to help people.


Michael Evans, Ph.D, MSEd, RN, ACNS, CMSRN, CNE
Assistant Chief Academic Officer and an Associate Teaching Professor of Nursing
Penn State University


Using Swivl as Teaching Tool in Nursing Education

Swivl is a remote-controlled robotic video observation device that produces high quality audio and video. Recordings were made of faculty performing focused assessments and interventions, which allowed students to watch the videos countless times in BOX as they worked to perfect their assessments and skills. In addition, it helped save the nursing department money as the typical nursing DVD costs anywhere from $100-$400/piece. Moreover, we were able to use Swivl technology to record student simulations and then use the videos as part of the debriefing exercise where students could learn from their mistakes in a safe environment while working to provide safe, patient care.

In this case, Swivl technology enhanced our ability to record students as it followed the students through the simulation lab as they worked through the scenario, which was a definite limitation of our previous recording system (webcam). A sample recording will be shown during the presentation. Student feedback has been very positive, including statements such as “I love how I can watch my teachers do the assessment the right way as many times as I need too.” and “Utilizing Swivl in the simulation setting has allowed me to be aware of my interactions with the patient and colleagues.” In conclusion, Swivl technology has enhanced our abilities to educate our students in a fun and interactive way while improving their clinical reasoning and judgment skills as we strive to prepare well educated graduate nurses who can provide safe, competent care.

Dr. Michael M. Evans, PhD, MSEd, RN, ACNS, CMSRN, CNE is the Assistant Chief Academic Officer and and Associate Teaching Professor of Nursing at Penn State University, College of Nursing, Scranton Campus, where he is responsible for teaching in the Baccalaureate, RN to BSN, and graduate programs. Dr. Evans is board certified in medical surgical nursing and nursing education.

Dr. Evans is published is the areas of nursing education and clinical practice. He also volunteers his time as a manuscript reviewer for MedSurg Matters. He is a member of many professional organizations including the Phi Kappa Phi Honor Society, Sigma Theta Tau International Honor Society of Nursing (Xi Gamma & Beta Sigma Chapters), National Association of Clinical Nurse Specialists, National League for Nursing and the Academy of Medical-Surgical Nurses, as well as the American Nurses Association, American Heart Association and the American Diabetes Association.

Dr. Evans received an Associate of Science in Nursing and his Bachelor of Science in Nursing from Penn State University and a Masters of Science in Nursing, with a specialization in adult health and a sub-specialization in nursing education from Misericordia University. In addition, he earned his Master of Science in Education with a focus in Professional Studies from Capella University and his PhD in Nursing from the College in Nursing at Penn State University.

He lives in Archbald with his wife, Stephanie, their son, Finn Michael, their dogs, Duncan Hines and Sweet Polly Purebred, and their two cats, Andrew Michael and Prairie Dawn.

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Martin Takac, Ph.D.
Associate Professor
Lehigh University


Reinforcement Learning in Engineering

In this talk, we briefly introduce Reinforcement Learning – a powerful machine learning tool used in many engineering fields. We will discuss two interesting applications of reinforcement learning (1) controlling stochastic supply chain (joint work with Prof. Snyder and supported by NSF grant in collaboration with Siemens Corporation,  and (2) training multiple smart agents to communicate and collaborate to achieve given goals.

We will conclude the talk by describing a novel Corrective Reinforcement Learning Framework which allows training reinforcement learning policies (e.g. hand-crafted expert strategy).

Prof Takac received his B.S. (2008) and M.S. (2010) degrees in Mathematics from Comenius University, Slovakia, and Ph.D. (2014) degree in Mathematics from The University of Edinburgh, United Kingdom. He received several awards during this period, including the Best Ph.D. Dissertation Award by the OR Society (2014), Leslie Fox Prize (2nd Prize; 2013) by the Institute for Mathematics and its Applications, and INFORMS Computing Society Best Student Paper Award (runner up; 2012). Since 2014, he is a Tenure Track Assistant Professor in the Department of Industrial and Systems Engineering at Lehigh University, USA. His current research interests include the design, analysis and application of algorithms for machine learning, optimization, high-performance computing, operations research and energy systems.

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Fred Aebli
Professor
Penn State Scranton

 

Fred Aebli is a 1991 alumni of Penn State University where he acquired a degree in Science with a Computer Science/Math Option. Upon graduation, he was commissioned a Second Lieutenant United States Marine Corps. While serving on active duty in various locations worldwide, he obtained his Master Degree in Computer Resource Management from Webster University at St Louis. 

After departing the active duty Marine Corps, Fred entered the civilian job market to work for Bell Atlantic in Baltimore’s Inner Harbor where he worked on database projects and early internet applications. He then joined Scientech Inc. as a consultant hired out by PPL where they developed a first of its kind, Decision Support System and Data Warehouse for the nuclear plant located in Berwick, PA. His team of developers were instrumental in using the then new Oracle Application Server technology. 

Upon completion of that assignment, Fred joined the faculty ranks at Penn State’s Scranton campus to help create the new Information Sciences and Technology (IST) degree where he teaches courses in database development, programming, website design, project management, and human computer interaction (HCI). This opportunity allowed Penn State University to begin educating the next generation IT professionals for the global market. Additionally, he coordinates the IST Internship Program where he connects local businesses with IST students as they attempt to fulfill their internship requirement. While at Penn State Scranton he has been part of the team supporting the creation and management of the Scranton LaunchBox business pre-incubator. Mr. Aebli separated from the Marine Corps Reserves in 2002 at the rank of Major. 

In order to maintain currency and proficiency in the IT sector, Mr. Aebli is the creator of GetMeCoding.com designed to inspire young people wanting to dream, collaborate, and problem while learning to write programming code. He is active in many local organizations fostering the connection of technology and business to include TecBridge and Tech Meetup. 

Fred and his wife, Jennifer, have 3 children and reside in Covington Township, PA.

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Frank Sorokach
Professor
Penn State Scranton

 

Frank M. Sorokach is leadership and management expert with both practical and academic experience.  He has been a lecturer at Penn State University since 2012, teaching at the Scranton campus on topics that include economics, project management, business strategy, risk management, and marketing.  He is also a course designer and lead faculty for the Penn State World Campus. In addition to teaching in a traditional academic setting, Frank has been facilitating leadership and managerial training to organizations for over two decades.    

Frank also has more than twenty years of applied management experience in varied disciplines. He has held managerial positions in sales, marketing, technology, and risk management.  He has also owned and operated several businesses and serves as a digital consultant for McGraw-Hill Education.  

Because his experience is broad in nature, Frank’s research interests include business process management, technology integration, risk, interpersonal relationships, and business disruption.  He is specifically focused on the application of new concepts, systems, and technologies to improve business processes and efficiency. This includes the integration of not only technology, but also new management theory in both the workplace and the education environment.  

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Smart Machines: Myth and Mysteries

Modern technologies are driving the business world into the future.  Disruption is now a constant state of existence and the pace of change is increasing.  And while there are many technologies driving the modernization and fueling the current industrial revolution, most people walk blissfully through the world without understanding the underlying technologies.   There are many myths and mysteries surrounding these technologies. 

In this session we will discuss some of the underpinnings of the topics that will be covered at the conference, including smart machines, collaborative robots, artificial intelligence, machine learning, additive manufacturing, and autonomous equipment.  This will include the technical and economic impacts of these technologies. We will show glimpses of the past of these technologies.  

Historians generally agree that there have been three previous industrial revolutions and that we are now experiencing the fourth industrial revolution.  We will explain the technologies that are the backbone of the modern industrial revolution and unravel the myths and mysteries surrounding them.


Benjamin Bishop, Ph.D., Professor
Professor of Computing Sciences
University of Scranton

 

Benjamin J. Bishop is a Professor of Computing Sciences at the University of Scranton in Scranton, PA USA. He received his B.S. in Computer Science and Ph.D. in Computer Science and Engineering from the Pennsylvania State University in 1996 and 2000, respectively. He is a senior member of ACM and co-founded the Scranton Girls Who Code group. He has volunteered as a Program Evaluator (PEV) for Computer Science within ABET/CAC since 2013. His primary areas of interest are in Computer Graphics and Architecture.

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Renée  M. Hakim, PT, PhD, NCS, Professor
PT, PhD, NCS, Professor
University of Scranton

 

Renée  M. Hakim,  PT, PhD, NCS is a Professor in the Department of Physical Therapy (PT) at the University of Scranton.  She has been teaching primarily in the areas of adult neurologic rehabilitation and motor control/motor learning since 1996.  Dr. Hakim received her entry-level PT degree from the University of Scranton, a MS degree in Neurologic PT from the University of Pittsburgh, and a PhD in Public Health from Temple University.  She received American Board of Physical Therapy Specialties (ABPTS) certification as a Neurologic Clinical Specialist in 1997 and re-certification in 2007. Her primary areas of research include balance testing/training, fall prevention and haptic robotic device training to improve upper extremity function.

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Haptic Devices to Improve Arm/Hand Function

Haptic devices collect input from the user while providing tactile feedback. These systems can be used to provide high repetition task-specific practice for patients with motor impairments. A system will be presented that focuses on functional task training (i.e., handwriting) for patients with arm/hand disorders. The system allows patients to improve dexterity by practice of writing using augmented feedback (haptic, visual, auditory) with or without the direct supervision of a physical therapist.


Del Lucent Ph.D.
Associate Professor of Physics
Wilkes University

 

New Kids on the Blockchain: Protein Folding and Machine Learning on the Coronai Network

Protein folding is among the most vital of processes needed to sustain life. Unfortunately, biochemical and biophysical experiments struggle to produce a comprehensive, mechanistic understanding of this process. Although detailed computer simulations help to ameliorate this problem, conducting these simulations requires substantial computational resources and yields very large datasets which must be distilled using various machine learning strategies. In order to meet these increasing computational demands, we are among the first adopters of Coronai: a general purpose, decentralized grid computing protocol. Coronai allows for flexible and efficient access to distributed computing by using a cryptocurrency to incentivize participation and a blockchain to ensure validity of scientific results. 

Dr. Del Lucent is an associate Professor of Physics (and Biology by courtesy) at Wilkes University.  Dr. Lucent is a Wilkes-Barre native, having attained his bachelor’s degrees at Wilkes University before moving to California for his graduate work.  He earned his Ph.D. in Biophysics from Stanford University in 2010 for his work on protein folding and molecular chaperones using the Folding@home distributed computing network.  Upon completing his graduate work, Lucent travelled to Melbourne, Australia for a postdoctoral fellowship at CSIRO, Australia’s national laboratory. While at CSIRO, Lucent conducted research in the fields of computational drug design, computational enzyme design, and structural genomics.  In 2012, Lucent returned to his Alma Mater as a professor of physics with the goal of integrating undergraduate students in interdisciplinary computational physics research. His research group continues to study the behavior of biological macromolecules through computational chemistry and physics as well as machine learning and topological data analysis.  He is currently collaborating with Onai, a Silicon Valley startup using blockchain and cryptocurrency technology to power scientific research.

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E. Thomas Pashuck, Ph.D. (Tommy)
Assistant Professor, Department of Bioengineering
Lehigh University


Developing Cell-Responsive Biomaterials for Regenerative Medicine

Regenerative medicine is a multidisciplinary approach that combines chemistry, engineering, biology, and medicine to design therapies to replace or repair damaged or diseased tissue. These are generally optimized for a single cell type, even though every tissue in the body is made up of many different cells working together towards a biological function. Therapies aimed at restoring these tissues will need to be able to support several different cell types simultaneously and foster the complex relationships that exist during regeneration and homeostasis. The current question is how materials can be designed to specifically target different cell types within a single scaffold. This will require extensive control over the specificity as well as spatial and temporal control over the activity of biological factors. This talk will focus on using cell-specific protease activity to induce local changes the matrix that can be used to guide regeneration.

E. Thomas Pashuck (Tommy) is a member of the Department of Bioengineering at Lehigh University. Prior to joining Lehigh he worked at the New Jersey Center for Biomaterials at Rutgers University and the Departments of Materials and Bioengineering and the Institute of Biomedical Engineering at Imperial College London in London, UK on a Marie Curie International Incoming Fellowship. He received a BS from the University of Florida and a PhD from Northwestern University, both in Materials Science and Engineering. For his doctoral work, under the guidance of Prof. Samuel Stupp, he focused on tuning the properties of self-assembling peptides through molecular design. His current research is focused on designing matrices that can target specific cell populations through the use of cell-responsive biomaterials to improve biomedical therapies.

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Michele M. McGowan, DBA, CPA, CIFHA
Associate Professor and Graduate Program Director, Healthcare Administration
King’s College

 

Smart Machines in Healthcare – Teaching the Management Side of Major Investments

Everyone wants the latest and greatest new toys, but are they worth the investment? These purchases require a large outlay of resources, have a long-term impact on earnings, generally lack liquidity, and influence the organization’s capacity for providing services. As a result, these decisions are among the most important ones made. So how do we make good capital investments decisions? This session will share how at King’s College we educate future healthcare leaders on appropriate capital budgeting techniques, methods of risk adjustment and scenario and sensitivity analysis, and the importance of qualitative considerations in the decision-making process. The goal is to help prevent you from making poor investment decisions that can have a disastrous effect on your organization.

In her role as associate professor and director of the graduate healthcare administration program at King’s College in Wilkes-Barre, Pennsylvania, Michele is not only teaching courses in financial management, accounting, strategic management, marketing, operations management, and economics, but also overseeing the administrative and curricular aspects of the program and the creation of strategic plans to develop and implement new program offerings.

Additionally, Michele participates actively in several college committees and community organizations and supplies leadership to several community boards and professional organizations, including the Northeast Pennsylvania Healthcare Foundation, the Association of University Programs in Health Administration, the Healthcare Financial Management Association, and the Scranton Area Foundation’s Women in Philanthropy.

She is a Northeastern Pennsylvania native; a graduate of Lakeland High School (1982), the University of Scranton (B.S. Chemistry-Business, 1986; B.S. Accounting, 1988), King’s College (M.S. Taxation, 1991); and Nova Southeastern University (DBA with a concentration in Accounting, 2014). Michele is also a licensed CPA in the Commonwealth of Pennsylvania and a Certified Internal Forensic Healthcare Auditor.

Prior to joining academia, Michele spent nearly 20 years in the hospitality and insurance industries, gaining experience in such areas as internal audit, tax preparation and compliance, claims processing, and business process improvement.

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Chris Speicher, Ph.D.
Director of Entrepreneurship, Marywood University
Chief Visionary Officer, DartDrones, LLC

 

Drones : The Sky is No Longer the Limit

The Drone industry took off with great momentum in 2014. Today it has plateaued and is in a hold pattern waiting for technology on the ground to catch up to the technology in the sky. How far are we away from the Jetsons era? How long until Starbucks delivers right here, right now? Where to and how long?

DartDrones is the international leader in drone education and training. With over 50 flight instructors worldwide, DartDrones, trains entities from US Governement agencies and police and fire organizations to leading utility and oil and gas producers to major video production companies.

Chris Speicher, Ph.D. is the Director of Entrepreneurship at Marywood University and a serial Entrepreneur. He earned his Doctorate from Temple University while studying the development of Entrepreneurs in Central and Eastern Europe in the 1990’s. Speicher has been involved in over 25 startups in his career.

Chris is currently the Chief Visionary Officer at DartDrones, the largest national drone flight school in the US, which was featured on Shark Tank in February of 2017.

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Joshua C. Agar, Ph.D.
Assistant Professor, Department of Materials Science and Engineering
Lehigh University

 

Deducing Inference from Hyperspectral Imaging of Materials via Machine Learning

Characterization of materials relies on measuring their stimuli-driven response after perturbation by an external energy source. These measurements generally involve either continuously changing the magnitude of the perturbation or the bandwidth/energy of the response which is measured resulting in data which has sequential or temporal dependence. Recent advances in high-speed sensors have allowed spectroscopic measurements to be conducted using a multitude of techniques (e.g., electron microscopy, atomic force microscopy, etc.) which also have high-spatial resolution. Coupling spectroscopic characterization with imaging allows researchers to directly probe structure-property relations at relevant length and time scales.

Despite a boon in these multidimensional spectroscopic imaging techniques the size and complexity of the data being collected coupled with the dearth of downstream analysis approaches have limited the ultimate scientific contributions of these powerful experimental techniques. Here, we show how deep-recurrent neural networks can be used to automate the extraction of features physically-important phenomena concealed within “big” multichannel hyperspectral data into focus for interpretation. Specifically, we will discuss the broad applicability of this approach to experimental techniques ranging from piezoresponse measurement of ferroelectrics, discovery of new conduction mechanisms at charged domain walls, and atomically-resolved electron energy loss spectroscopic of functional interfaces.

The methodology developed paves the way for spectroscopic techniques wherein the conventional scientific methods of designing targeted experiments aimed at a specific hypothesis are supplanted by approaches which collect all seemingly relevant data, which can then be automatically interpreted to identify a hypothesis for empirical testing.

Joshua C. Agar is an Assistant Professor in the Department of Materials Science and Engineering at Lehigh University. His research interests center around advanced complex oxide thin-film deposition, custom multidimensional and multifrequency electromechanical scanning probe spectroscopies, and machine and deep learning. Joshua earned a B.S. from the University of Illinois at Urbana-Champaign, an M.S. from the Georgia Institute of Technology and a Ph.D. from the University of Illinois at Urbana Champaign all in the field of Materials Science and Engineering. Following his Ph.D. Joshua was a postdoctoral fellow at the University of California-Berkeley.  His work has been published and highlighted in a range of high impact journals across scientific disciplines including: Nature Materials, Advanced Materials, ACS Nano, Physical Review Letters, etc. 

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Darlene Farris-Labar
Professor of Art + Design
East Stroudsburg University

“Heavy Metal”- The Disruption of 3D Printing

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Jill Murray, Ph.D.
EVP & Chief Innovation Officer
Lackawanna College

eSport. Smart Strategy.

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