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Survival analysis: Forecasting lifespans of patients and products
How long will you live? Should you spring for that AppleCare+ warranty for your iPhone? When will your buddy pay you back for that lunch? For centuries, soothsayers have striven to understand the lifespan of things – be they patient longevity, product lifecycles, or even time to loan default. Nowadays, scientists have turned away from reading tea leaves and toward survival analysis – a complex data science method for predicting not only whether an event will happen (the death of a patient, the failure of a product or machine, default on a payment, and so on) but when this event is likely to occur. But it’s problematic. Until now, the tools of survival analysis have only been applicable in certain settings. This is due to the inherent heterogeneity of what is being analyzed: differences in patient lifestyles, demographics, product usage patterns, and so on. New research by Goizueta Business School’s Donald Lee, associate professor of information systems and operations management and of biostatistics and bioinformatics, has yielded a new tool that greatly extends survival analysis to broader use cases. “Historically, scientists have used classic survival analysis tools to predict the lifespan of different things in different fields, from products to patients,” Lee said. “Since the 1950s, the Kaplan-Meier estimator has been the benchmark for analyzing lifetime data, particularly in clinical trials. The next breakthrough came in the 1970s when the Cox proportional hazards model was introduced, which allows researchers to incorporate variables that can affect the predictability of things like patient mortality.” The problem with the existing survival analysis tools, Lee said, is that they make certain assumptions that can skew the predictions if the assumptions are not met. “There are very few existing tools that can incorporate variables without imposing assumptions on how they affect survival, let alone when there are a lot of variables that can also change over time. For example, two iPhones will have different lifespans depending on the temperature at which they are stored, amongst many other factors. But it’s unlikely that storing your phone at 30 degrees will halve its lifespan compared to storing it at 60 degrees. This sort of linear relationship is commonly assumed by existing tools.” Lee’s team developed a new survival methodology based on something called gradient boosting: a machine learning technique that combines decision trees to yield predictions. The method, Lee said, is totally assumption-free (or nonparametric in technical parlance) and can deal with a large number of variables that can change continuously over time, making it significantly more general than existing methods. Nothing like it has been seen until now, he noted. “Calculating the survival rate of anything is super complex because of the variables. Say you want to create an app for a smart watch that monitors the wearer’s vitals and use this information to create a real-time warning indicator for stroke. Doing this accurately is difficult for two reasons,” Lee explained. “First, a large number of variables may be relevant to stroke risk, and the variables can interact in ways that break the assumptions central to existing survival analysis methods. And second, variables like blood pressure vary over time, and it is the recent measurements that are most informative. This introduces an additional time dimension that further complicates things.” The software implementation of Lee’s method, BoXHED, overcomes both issues and allows scientists to develop real-time predictive models for conditions like stroke. The trained model can then be ported to a watch app to tell its wearer if and when they’re likely to have a stroke, a process known as inferencing in machine learning lingo. The implications, Lee said, are huge. “BoXHED now opens the door for modern applications of survival analysis. In previous research, I have looked at the design of early warning mortality indicators for patients with advanced cancer and also for patients in the ICU. These use other methods to make predictions at fixed points in time, but now they can be transformed into real-time warning indicators using BoXHED.” He cited the case of end-stage cancer patients who are often better served by hospice care than by aggressive therapy. “Accurate predictions of survival are absolutely critical for care planning. In previous analyses, we have seen that using existing predictive models to inform end-of-life care planning can potentially avert $1.9 million in medical costs and 1,600 days of unnecessary inpatient care per 1,000 patient visits in the United States. BoXHED is likely to lead to even better results.” Lee’s research paper is forthcoming in the Annals of Statistics. He has also created an open-source software implementation of BoXHED, which can radically improve the accuracy of survival analysis across a breadth of applications. The paper describing BoXHED was published in the International Conference on Machine Learning, and the latest version of the BoXHED software can be found online. If you are a journalist or looking to speak with Donald Lee – simply click on his icon now to arrange an interview or appointment today.
A Free App Can Help School and College Administrators Contain COVID-19
With COVID-19 infection rates rising across the country as students return to school for the spring semester, how will schools and colleges control the spread? COVID Back-to-School can help. It’s a free online tool that predicts the outcome of taking specific measures to curtail the spread of the virus. The algorithm powering the app was developed by Rensselaer Polytechnic Institute computer science professor Malik Magdon-Ismail and builds upon the success of COVID War Room, an algorithm that can predict the spread of COVID-19 in smaller cities and counties across the United States and select international locations. Administrators at Rensselaer consulted COVID Back-to-School when devising a COVID-19 management plan that successfully kept the infection rate on campus well below 0.5% during the fall 2020 semester, even with most students attending in-person classes. Magdon-Ismail, an expert in machine learning, designed the algorithm to allow administrators at schools of all levels, as well as ordinary citizens, to quantitatively analyze various strategies for containing the virus. Users can enter details about their institution — like the zip codes students come from, the size of the school, how often students are tested, the number of expected interactions during a class or meal — and COVID Back-to-School will project outcomes like the proportion of students likely to arrive infected, the proportion of students likely to be infected over time, and the number of likely new infections every 14 days. “This is a publicly available tool that we’re hoping schools can use to quantitatively analyze re-opening strategies,” Magdon-Ismail said. “Schools can use it, at least, to evaluate how their current strategy will play out assuming an infection on campus. Better still, COVID Back-to-School allows schools to try out various strategies before actually implementing them, to see what works and what doesn’t.” Magdon-Ismail is available to discuss how the algorithm works and the utility it may provide to colleges and universities across the country in the spring semester.
Optimizing the delivery speed promise can boost sales
After the coronavirus pandemic forced most of the country into lockdown, online shopping soared. According to CCInsights.org, by the end of April 2020 there was a 146% year-over-year increase in U.S. and Canadian online retail orders. Amazon was so overwhelmed by the combination of increased demand, logistical nightmares, and warehouse worker safety issues that the company announced significant delays in its Amazon Prime shipping speeds. When the company announced it would prioritize the shipping of essential items, the online retailer’s third-party sellers were left to manage their own shipping — something Amazon usually did for them. Shoppers who placed orders for non-essential products at the end of March sometimes received estimated delivery dates of more than a month away. While consumers often received their orders sooner than the 30-day estimate, for Prime shoppers used to getting their items delivered for free the next day, the change in delivery speed was a shock. Amazon shoppers turned to alternative outlets that promised much quicker delivery speeds. Companies with strong e-commerce positions and supply chains, such as Walmart, took advantage of Amazon’s situation. “People are very sensitive to delivery and how fast they can get products,” said Ruomeng Cui, assistant professor in information systems & operations management. “Maybe, just maybe, Amazon would be able to deliver faster than one month, but they chose to promise customers one month — that was their choice.” Unfortunately for Amazon, by setting conservative delivery speed promises, they exacerbated an already bad situation. According to Cui’s paper “Sooner or Later? Promising Delivery Speed in Online Retail” (Ruomeng Cui, Tianshu Sun, Zhikun Lu and Joseph M. Golden), optimizing delivery speed promise can have a substantial effect on a company’s sales. How substantial? Without changing the actual delivery speed itself — only the delivery speed promise — Cui’s research showed that when the retailer promised customers one day faster shipping, sales increased, profits increased, and customers spent more on each order. “It’s a very critical decision for retailers to try to determine how to manage delivery and how to manage the information aspect of delivery,” added Cui. The study is attached and found two key findings: The value of communicating delivery times From a customer satisfaction standpoint, the conservative disclosure lowered customer satisfaction while the aggressive disclosure didn’t affect the company’s satisfaction score, although it did increase product returns when shipping speed was overly aggressive and products were delivered late. “These results indicate that in our research context, promising customers a faster delivery speed can boost sales and profitability but at the cost of a higher product return rate,” the researchers wrote. They go on to caution retailers that promising a conservative shipping speed can be costly. “It’s a careful balance that companies need to think about — how to manage customers’ expectations properly,” explained Cui. Crafting the delivery promise Given online retailers’ adoption of machine learning, Cui believes companies could tweak their algorithms to explore what products and which types of customers are more tolerant to over-promising as it relates to the delivery speed promise. “Companies can then use the analysis to customize and differentiate the types of products that adopt different types of information strategies,” Cui said. “Just change your algorithm, learn and incorporate some of the data-driven decisions and methods.” Going forward, Cui hopes to customize algorithms for companies in an effort to help them dynamically optimize how to promise the correct delivery speed to customers. While many companies, like Collage.com, don’t own their own delivery function and can’t change the actual delivery speed by changing infrastructure, these companies can “manage the information,” said Cui. “It’s easy, and I think it should be the retailer’s responsibility and job to optimize.” “I want to advocate for all retailers to think strategically in their information aspect,” said Cui. “Don’t let such an easily fixed lever just sit there at almost zero cost.” If you are a journalist looking to cover this study or speak with Professor Ciu about subjects like online shopping and operations management, simply click on her icon now to arrange an interview today.
Virtual Reality-Based Surgical Simulations Could Make Patients Safer
Suvranu De, the director of the Center for Modeling, Simulation, and Imaging in Medicine at Rensselaer, has dedicated more than a decade of research to making surgery safer by developing virtual reality-based surgical training simulations that closely mimic the optics and haptics a surgeon may encounter in the operating room. A new $2.3 million grant from the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health will further his research in this space, by supporting the development of a collaborative virtual reality-based surgical simulation environment that allows medical professionals to practice technical, cognitive, and interpersonal skills as a team. “People will be wearing head-mounted displays, and they will be immersed in a virtual operating room working on a virtual patient as a team,” De said. “We want to have an expert team in the operating room focused on the treatment of a patient, and not just a team of experts.” Conceptually, this approach is similar to crew resource management practiced by aviation pilots, which has led to a significant reduction in aircraft accidents. The Virtual Operating Room Team Experience (VORTeX) simulation system will provide realistic distractions, interruptions, and other stressors that medical professionals may encounter in an operating room. Traditionally, this type of simulation training has required mannequins, instructors, and a dedicated space, as well as significant coordination and resources. In contrast, the VORTeX system will be both distributed and asynchronous – allowing participants to join the simulation from different locations, and instructors to review the simulation and provide feedback at their convenience. Machine learning algorithms will be used to crunch the data and provide feedback to participants, who will be able to return to the virtual environment to review their performance. De is available to discuss how this type of virtual training is developed and implemented.
As the global pandemic touches almost all parts of the United States – it is essential that the public receives only accurate and definitive information from credible and expert sources as news, media and information reaches million of people across the country. An invisible enemy is killing thousands and forcing people worldwide to cower behind closed doors. Unfounded conspiracy theories and miracle “cures” abound on social media. Politicians and pundits send mixed messages about how to protect yourself. Who you gonna call? - Bedford Gazette, April 14 As the coronavirus rampages, the public increasingly is turning to experts in academia and government -- the educated, experienced “elites” that many Americans had tuned out. The Coronavirus 2019 (COVID-19) situation is certainly new to all of us. As guidance from the CDC changes and instructional methods transition, there are experts at Georgia Southern who can help to answer questions such as: How should we best address this pandemic as a nation? How should we best address this pandemic individually? What does it mean to “flatten the curve?" What is the economic impact of COVID-19? How do you best manage employees virtually? Why are grocery stores having trouble keeping inventory on their shelves? Should we prepare for a lapse in groceries and goods? What contributes to the fear and panic in disasters and pandemics? What do educators, parents and students need to know to prepare for online learning in the K-12 and college settings? If you are a reporter covering COVID-19, let the team of experts from Georgia Southern help with your coverage. Public Health: Atin Adhikari, Ph.D. Associate Professor of Environmental Health Sciences, Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health Dr. Adhikari brings over 15 years of extensive research experience on aerosols, airborne microorganisms, other air pollutants, and related respiratory disorders. His current research areas include environmental air quality, exposure assessment, occupational health and safety, environmental microbiology, and respiratory health. Before joining JPHCOPH, Dr. Adhikari was also involved (Co-I) with two DoD-DTRA and U.S. Office of Naval Research funded projects on inactivation of hazardous microorganisms. Chun Hai (Isaac) Fung, Ph.D. Associate Professor, Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health Dr. Isaac Chun-Hai Fung is a digital health expert and an infectious disease epidemiologist. He analyses social media data for public health surveillance and health communication and uses digital technologies for public health interventions. He investigates the transmission of communicable diseases with a focus on respiratory infections and environmentally transmitted infections. He applied a variety of methods, from classical statistical methods to machine learning and mathematical modeling, to address public health problems and to provide solutions to policy-makers. He is especially interested in assisting public health agencies in their responses to public health emergencies. He is currently a guest researcher with the Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention (CDC). Examples of his recent projects include: Surveillance of unplanned school closures through social media platforms, Analysis of social media posts pertinent to public health emergencies, such as Ebola, MERS and Zika. Jessica Schwind, Ph.D. Assistant Professor, Department of Biostatistics, Epidemiology, and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health Dr. Jessica Smith Schwind is an epidemiologist and program evaluator. She joined the Department of Biostatistics, Epidemiology and Environmental Health Sciences at JPHCOPH in August 2017. Her current research interests include disease surveillance, capacity building and risk communication for the prevention and/or early recognition of outbreaks with a focus on: best practices for operationalizing the ‘One Health’ approach, understanding and improving capacity building efforts and priorities for increasing health surveillance, and improving early warning systems for disease detection and response by bridging the gap between global digital databases and local health information. Schwind also conducts SoTL research on innovative online/onsite teaching and evaluation with a focus on immersive and service-learning practices. Pandemics, panic and the public: Amy Ballagh, Ed.D. Associate Vice President of Enrollment Management Featured in the Washington Post : Jessica Schwind, Ph.D. Assistant Professor, Department of Biostatistics, Epidemiology, and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health Dr. Jessica Smith Schwind is an epidemiologist and program evaluator. She joined the Department of Biostatistics, Epidemiology and Environmental Health Sciences at JPHCOPH in August 2017. Her current research interests include disease surveillance, capacity building and risk communication for the prevention and/or early recognition of outbreaks with a focus on: best practices for operationalizing the ‘One Health’ approach, understanding and improving capacity building efforts and priorities for increasing health surveillance, and improving early warning systems for disease detection and response by bridging the gap between global digital databases and local health information. Schwind also conducts SoTL research on innovative online/onsite teaching and evaluation with a focus on immersive and service-learning practices. Jodi Caldwell, Ph.D. Executive Director of the Georgia Southern University Counseling Center On a national level, Dr. Caldwell is currently serving her second elected term to the Directorate Board of the Commission for Counseling and Psychological Services of the American College Personnel Association and is a certified Red Cross Disaster Mental Health Responder. COVID-19 and logistics, the economy and the workforce: Alan Mackelprang, Ph.D. Associate Professor, Department of Logistics & Supply Chain Management Currently the director of the Ph.D. in Logistics and Supply Chain Management program, his research interests include examining interdependencies among supply chain partners, JIT/Lean production, manufacturing flexibility as well as supply chain integration. Scott Ellis, Ph.D. Associate Professor, Department of Logistics & Supply Chain Management Scott Ellis’ research interests center on the study of purchasing and supply management processes and functions. He has published in Journal of Operations Management and Journal of Supply Chain Management, among others. Richard McGrath, Ph.D. Professor, Parker College of Business Richard McGrath researches immigration, consumer survey methodology, and applied microeconomics. He is a long time expert on the economy in Savannah and the Coastal Empire. Michael Toma, Ph.D. Fuller E. Callaway Professor of Economics Michael Toma is a professor and lead analyst for the Center for Business Analytics and Economic Research, a student- and faculty-staffed applied research group focused on the Savannah-area economy that works with many local partners on special initiatives, customized applied business research and impact studies. Based on Toma's analytics, the Center publishes the quarterly Coastal Empire Economic Monitor, a closely watched economic report. Toma's community ties are also strong in the area. He serves on the Board of Directors for United Way of the Coastal Empire and on the organization's Executive Committee as chair of the Community Investments Committee. David Sikora, Ph.D. Assistant professor of management David Sikora’s research interests include strategic human resource management and the business impact of employee management practices. He has published his research in such journals as the Journal of Applied Psychology, Leadership Quarterly, Human Resources Management Review, International Journal of Selection and Assessment, and International Journal of Human Resources Development and Management. Prior to his academic career, David had extensive corporate experience in human resources and marketing including serving as human resources vice president at Cigna Corporation and director of human resources product management at Gevity HR, Incorporated. Steven Charlier, Ph.D. Associate Professor, Department of Management Charlier’s research interests are focused on the modern work environment, and include virtual teams, e-learning, leadership in a virtual world, and management education. His work has been published in several leading international academic journals, including The Leadership Quarterly, Human Resource Management, Journal of Organizational Behavior, Academy of Management Learning & Education, and Human Resource Management Review. Online teaching and learning: Charles Hodges, Ph.D. Professor, Department of Leadership, Technology and Human Development Hodges is a tenured professor of instructional technology at Georgia Southern with over 20 years of online teaching experience. As an active researcher in online teaching and learning, Hodges presents regularly at the national and international levels. He currently serves as the editor-in-chief of the journal and he is a long-time member of the Association for Educational Communications and Technologies, a professional organization for Educational Technology scholars and practitioners. Featured in the Inside Higher Ed article (published 3/11/20): Jeffrey Tysinger, Ph.D. and Dawn Tysinger, Ph.D. Professors, Department of Leadership, Technology and Human Development The Tysingers are one of very few individuals who are actively researching in the area of crisis preparedness in K-12 online learning Professors, Department of Leadership, Technology and Human Development The Tysingers are one of very few individuals who are actively researching in the area of crisis preparedness in K-12 online learning: o https://digitalcommons.georgiasouthern.edu/nyar/vol2/iss1/4/ o https://dl.acm.org/doi/10.5555/2811036.2811057 o https://eric.ed.gov/?q=Tysinger&id=EJ1147626 o https://eric.ed.gov/?q=Tysinger&id=ED595756 Dawn Tysinger, NCSP, serves as professor and program director for the nationally-recognized, National Association of School Psychologists-Approved Education Specialist program in school psychology at Georgia Southern University. Tysinger has contributed to her field through active participation in NASP, publications in school psychology journals, and presentations at the local, state, regional, national, and international levels. She currently serves on the NASP program review board for school psychology programs and as a member of the editorial boards of Journal of School Psychology, Psychology in the Schools, Trainers’ Forum: Journal of the Trainers of School Psychologists, National Youth-At-Risk Journal and Journal of Online Learning Research. Jeff Tysinger, NCSP, is a professor of school psychology at Georgia Southern University. He has been the president of the Kansas Association of School Psychologists (KASP), editor of the KASP Newsletter, KASP Futures committee member, KASP NCSP committee member, member of National Association of School Psychologists (NASP) since 1997, Nationally Certified School Psychologist since 1997, NASP Program Reviewer, NCSP Portfolio Reviewer, member of NCATE Board of Examiners, member of Georgia Association of School For parents at home with (k-12) children now distance learning: Chelda Smith Associate Professor, Department of Elementary and Special Education Smith’s master's thesis focused on parents as the first teachers of children and can speak to how parents can be empowered in that role. Her research agenda continues to focus on home and community assets, of which parents/caregivers are the primary influence and factor for positive outcomes. Lastly, as a parent of both a middle schooler and a toddler, Smith is navigating the process of being a primary educator in the home in real-time. Each expert is available to speak with media – simply contact Melanie Simon at 912.313.3245 to arrange an interview today.
Will schools reopen before semester ends? Georgia Southern pandemic expert can give perspective
While education has moved into homes across the country because of the COVID-19 pandemic, people are wondering if the shutdowns will actually help stop the spread of the disease. Isaac Chun-Hai Fung, Ph.D., a digital health expert and infectious disease epidemiologist at Georgia Southern University, said school closures can delay the peak of the outbreak, reduce the amount of cases and decelerate the spread of the virus. Fung was a part of a study in 2015 that modeled a potential flu pandemic. The study showed that delaying the spread of a virus can give health care professionals more time to come up with vaccines and other treatments, as well as giving the system time to brace itself for the onslaught of patients. “The key message of my paper is not necessarily how quickly we shut down schools,” Fung told Rolling Stone. “It is the duration of school closure that matters. Whenever we relax social distancing measures, we will see a bounce-back of the cases, unless we are able to completely block all transmission chains and have driven the case number to zero — i.e., extinction of the virus, as in the case of SARS in 2003.” While some think opening schools and other public places would benefit the economy, Fung said doing so could leave the country vulnerable. “To save the U.S. economy, we must control this disease first,” Hung said to Rolling Stone. “That is what China is going to achieve — even if they have already suffered a great deal economically due to COVID-19. That is why (Narendra) Modi asks the whole of India to stay home for three weeks. That is also what Boris Johnson asks the British people to do now. The Americans should take heed.” Fung analyses social media data for public health surveillance and health communication and uses digital technologies for public health interventions. He investigates the transmission of communicable diseases with a focus on respiratory infections and environmentally transmitted infections. He applied a variety of methods, from classical statistical methods to machine learning and mathematical modeling, to address public health problems and to provide solutions to policymakers. He is especially interested in assisting public health agencies in their responses to public health emergencies. Fung is available to speak with media regarding this topic — simply reach out to Georgia Southern Director of Communications Jennifer Wise at jwise@georgiasouthern.edu to arrange an interview.
Introducing AiMOS, The Most Powerful Supercomputer at a Private University
The most powerful supercomputer to debut on the November 2019 Top500 ranking of supercomputers, also the most powerful supercomputer in New York State, was recently unveiled at the Rensselaer Polytechnic Institute Center for Computational Innovations (CCI). Part of a collaboration between IBM, Empire State Development (ESD), and NY CREATES, the eight petaflop IBM POWER9-equipped AI supercomputer is configured to help enable users to explore new AI applications and accelerate economic development from New York’s smallest startups to its largest enterprises. AiMOS is: The most powerful supercomputer housed at a private university. The 24th most powerful supercomputer in the world. The third-most energy efficient supercomputer in the world. Named AiMOS (short for Artificial Intelligence Multiprocessing Optimized System) in honor of Rensselaer co-founder Amos Eaton, the machine will serve as a test bed for the New York State-IBM Research AI Hardware Center, which opened on the SUNY Polytechnic Institute (SUNY Poly) campus in Albany earlier this year. The AI Hardware Center aims to advance the development of computing chips and systems that are designed and optimized for AI workloads to push the boundaries of AI performance. AiMOS will provide the modeling, simulation, and computation necessary to support the development of this hardware. “The established expertise in computation and data analytics at Rensselaer, when combined with AiMOS, will enable many of our research projects to make significant strides that simply were not possible on our previous platform,” said Christopher Carothers, director of the CCI and professor of computer science at Rensselaer. “Our message to the campus and beyond is that, if you are doing work on large-scale data analytics, machine learning, AI, and scientific computing, then it should be running at the CCI.” Built using the same IBM Power Systems technology as the world’s smartest supercomputers, the US Dept. of Energy’s Summit and Sierra supercomputers, AiMOS uses a heterogeneous system architecture that includes IBM POWER9 CPUs and NVIDIA GPUs. This enables AiMOS with a capacity of eight quadrillion calculations per second. You can watch Rensselaer President Shirley Ann Jackson talk about AiMOS here: Chris Carothers is the director of the Center for Computational Innovations (CCI) at Rensselaer. He is available to speak with media about AiMOS and what it can enable – simply click on his icon to arrange an interview.
With 2018 in full swing there’s no sign that the issue of fake news is going away. In fact, it continues to plague major social platforms such as Facebook as well as the traditional media players. This erosion of trust begs the question – how can we ensure the right experts on important topics are at the center of the conversation? If your organization has experts, there is a silver lining. There has never been a more important time for experts – the real ones – not the “fake it till you make it” collection of posers and promoters that have read a blog on personal branding. We’re talking about the people who have put in their 10,000 hours of researching, building and publishing. Presenting your top people in a more visible, engaging and approachable way presents huge opportunities for you to build trust and deepen relationships with a variety of audiences, including customers and partners – not just the media. However, to really capitalize, you have to look closely at how audiences interact with your expert content. Based on our work with thousands of experts and their organizations, we’ve prepared a list of key trends and predictions you need to watch if you’re a communications and digital media professional. Trend 1: Organizations are measuring their “Internal Bench Strength”. The power behind any organization is its people, but many organizations fall short in taking stock of their roster of experts who are capable of building voice and reputation with key audiences. Communicators are increasingly turning to internal pulse surveys and annual assessments that better identify competencies, professional interests and attitudes across the organization. Smart organizations are using surveys to create an efficient roster of internal experts and match them to the news cycle. Identifying a “core group” of go-to experts who will best benefit from programs such as media training and carefully mapping key topics to experts will ensure the organization is aligned to support communications objectives – both for proactive story development and responding quickly to breaking news opportunities. Trend 2: Organizations are starting to function more like newsrooms. As newsrooms in the print and broadcast world continue to be streamlined and downsized, organizations can play a key role in helping journalists by making relevant content and credible sources more accessible. Incorporating better search features that allow journalists to quickly find experts using simple keyword searches is an important starting point. Showcasing experts in the context of key news events in a content hub with interesting story angles are increasing in popularity Trend 3: Next generation newsroom platforms will change how media find expert sources. Journalists have a challenging role today amidst a backdrop of fake news and increasing cynicism about the credibility and sources of information. They still have the same day deadlines, but with an increased responsibility to get the story right, so reliable sources are critical to their success. So it’s not surprising that journalists, television bookers and producers are gravitating to solutions that make it easier for them to discover, evaluate and connect with expert sources. We recently integrated our ExpertFile global directory into the Associated Press newsroom software which is used by thousands of print, broadcast and digital newsrooms around the world. The AP, as the world’s leading news organization, recognizes the pressures that publishers and broadcasters are under. They are committed to technology advances that help news organizations. Few journalists have the time to rummage around in poorly designed corporate websites and university faculty directories looking for the best expert. And if you think it’s just junior reporters using these online tools think again. We’re seeing seasoned journalists from top media outlets including The New York Times, CNN, Time Magazine, NBC, The Washington Post, the BBC, NPR Radio and the CBC making regular use of the ExpertFile platform. The bottom line: If you aren’t thinking about broader distribution of your expert content beyond your website you are missing out. Trend 4: New search technologies are helping organizations cut through the content clutter. Searching for the right person based on attributes such as key topics, publications, or geography inside an organization remains a challenge – even for those organizations that have invested heavily in content management solutions and intranet platforms. The organic and onsite search user experience has become a top issue for marketing and IT teams. Audiences who have been spoiled by “Google-like simplicity” expect to find relevant information, or they’re gone within seconds. That’s why many organizations are investing in new search technologies powered by machine learning to provide faster discovery and connections with their subject-matter experts. Last year we built Elasticsearch features right into our platform to save our clients the time and money of doing this for themselves. Search remains one of the biggest opportunities to quickly drive more market attention and audience engagement, as well as to improve internal collaboration between experts. Trend 5: Video will continue to outperform all other forms of content. There’s nothing quite like video to drive the value of owned content. But remember that video is becoming essential to boosting earned media. We’re continually impressed by the new research that continues to emerge on the power of video content. Last fall, LinkedIn reported audience engagement numbers for its new video feed feature that showed 20 times more engagement for video vs. all other forms of content on its platform. As more audiences demand video content, so does the demand in television newsrooms for broadcast-ready experts. That’s why we also partnered with Dejero to help broadcasters who use their platform to search for experts suitable for interviews. If you are looking to get more television coverage, then you have to invest some of your budget on video to showcase your experts. We predict that the most successful organizations will adopt a video-centric approach to storytelling, creating snackable multimedia content that connects with a range of audiences. Many marketers are overthinking video as something requiring a massive production with a big annual shoot”. That doesn’t work for audiences such as journalists who are feeding a real-time news cycle. Our simple advice – look carefully at your video strategy and identify opportunities to use video across your digital properties in areas such as your homepage, media room and even landing pages. We’re interested to hear how your organization is capitalizing on these trends to better promote your experts to key audiences. For more information on how ExpertFile can help your organization incorporate the latest software and services innovations into your thought leadership and expert marketing strategies please drop us a line at dtaenzer@expertfile.com.
The Many Faces of Expertise: Theres more than one way to define an expert!
As the lead researcher at ExpertFile I spend a lot of my time thinking about the nature of expertise. I often get asked about the criteria that we use to identify experts, and it’s actually a very difficult concept to pin down. One of my favourite services that we provide to our clients is sitting down with them and helping them articulate what exactly “expertise” means to them. Sometimes this is an easy question, sometimes it is very, very difficult. The fact remains that there is no definition of expertise that perfectly encapsulates every organization’s requirements. How do you begin to select your experts to showcase? Well, there are many different ways of exhibiting expertise. A lot of our clients are higher education institutions who are seeking to promote their academics. The evidence demonstrating their unique experience in their respective fields are easily encapsulated in their academic credentials, awards, grants, publications and professional affiliations. Academics are often at the cutting edge of their fields, and are very experienced telling meaningful stories about them. If a reporter is writing a story about the mountains of Pluto, then an astronomer who has dedicated their lives to the study of extra-Neptunian objects is a perfect choice. By contrast, expertise in the corporate realm is more based on personal experience than academic credentials. This significantly differentiates corporate expert marketing programs from higher education. Although education and credentials remain important, it is generally more graded with a personal experience with the topic at hand. For example, a senior engineer at Google (with extensive media experience) would obviously be a tier A source for explaining the science behind contemporary web search engines, despite potentially having no university education in computer science! (Note: Some fields in computer science, such as machine learning, have a much more academic basis). Both the astronomer and computer scientist are clearly experts, but the means that we used to evaluate their expertise are very different. I’m sure that you can see that both academics and practitioners have meaningful comments to add to news reporters. At ExpertFile, we think that the most important skill an expert can have is the ability to distill their domain-specific knowledge into a compelling, relevant and meaningful story. This ability to tell stories transcends experience, or credentials. A Harvard professor may be a nobel prize winner, but unless he can effectively communicate his research to the media and the public, he will not be perceived as an expert. In contrast, a professor at a local community college may have less august credentials, but if they can tell a good story, then they will engage with the public and media much more effectively. In fact, in some cases “lowly” adjuncts bring vibrant life-experiences and direct understanding of the real world applications of academic theory, and may therefore eclipse the atrophied viewpoints of some tenured faculty isolated for decades in the academy. So at ExpertFile, we feel that a balanced representation of both academics and practitioners at every level is crucial for creating a balanced marketplace of experts that is a valuable resource for all our users. Although our platform contains thousands of academics, some from top flight institutions, we also list thousands of incredibly credible, engaging experts with real world, contemporary experience that can often eclipse that of tenured faculty. We are very proud of our network, and curate an active and vibrant community with a diversity of different voices and perspectives on topics of breaking news interest. We don’t open our network to anyone, the ability to distill meaningful and engaging content for others is crucial, so those who are only shilling a product or self-promoting are not welcome. Some people think that only academics belong on an expert network, but at ExpertFile we believe that would exclude many people with extensive expertise. Similarly, it would be the height of elitism for us to restrict our database to tenured academics from top-tier universities. This would do our users a great disservice by removing those voices with a perspectives gained from practical experience.
D. Tyler McQuade, Ph.D., professor in the Department of Chemical and Life Science Engineering at Virginia Commonwealth University College of Engineering, is principal investigator of a multi-university project seeking to use artificial intelligence to help scientists come up with the perfect molecule for everything from a better shampoo to coatings on advanced microchips. The project is one of the first in the U.S. to be selected for $994,433 in funding as part of a new pilot project of the National Science Foundation (NSF) called the Convergence Accelerator (C-Accel). McQuade and his collaborators will pitch their prototype in March 2020 in a bid for additional funding of up to $5 million over five years. Adam Luxon, a Ph.D. student in the Department of Chemical and Life Science Engineering who has been involved from the beginning, explained it this way: “We want to essentially make the Alexa of chemistry.” Just as Amazon, Google and Netflix use data algorithms to suggest customized predictions, the team plans to build a platform and open knowledge network that can combine and help users make sense of molecular sciences data pulled from a wide range of sources including academia, industry and government. The idea is right in line with the goal of the NSF program: to speed up the transition of convergence research into practice in nationally critical areas such as “Harnessing the Data Revolution.” The team itself reflects expertise across several specialties. Working with McQuade are James K. Ferri, Ph.D., professor in the Department of Chemical and Life Science Engineering; Carol A. Parish, Ph.D., professor of chemistry and the Floyd D. and Elisabeth S. Gottwald Chair in the Department of Chemistry at the University of Richmond; and Adrian E. Roitberg, Ph.D., professor in the Department of Chemistry at University of Florida. Two companies are also involved with the project: Two Six Labs, based in Arlington, Virginia, and Fathom Information Design, based in Boston, Massachusetts. Currently, there is no shared network or central portal where molecular scientists and engineers can harness artificial intelligence and data science tools to build models to support their needs. What’s more, while scientists have been able to depict what elements make up a molecule, how the atoms are arranged in space and what the properties of that molecule are (such as its melting point), there is no standard way to represent — or predict — molecular performance. The team aims to fill these gaps by advancing the concept of a “molecular imprint.” The collaborators will create a new system that represents molecules by combining line-drawing, geometry and quantum chemical calculations into a single, machine-learnable format. They will develop a central platform for collecting data, creating these molecular imprints and developing algorithms for mining the data, and will develop machine learning tools to create performance prediction models. Parish said, “The ability to compute molecular properties using computational techniques, and to dovetail that data with experimental measurements, will generate databases that will produce the most comprehensive results in the molecular sciences. “There are many laboratories around the world working in this space; however, there are few organizational structures available that encourage open sharing of these data for the benefit of the community and the common good. We seek to collaborate with others to provide this structure; an open knowledge network or repository where scientists can deposit their molecular-level experimental and computational data in exchange for user-friendly tools to help manage and query the data.” The initial response to their idea has been strong from potential partners. Ferri and the others have already collected more than a dozen letters from major corporations such as Dow and Merck expressing interest in participating. Also on board are Idaho National Laboratory and Argonne National Laboratory, as well as national chemical engineering and chemistry organizations. McQuade said that chemical engineers in major industries including consumer products and oil and gas producers expend a lot of effort running experiments to determine the molecule they want to use, such as finding the best shampoo additive that doesn’t make babies cry. “The ability to design the properties you want is still more art than science.” The team also plans to develop a toolkit for processing and visualizing the data. Roitberg, whose research focuses include advanced visualization, said this could take the form of a virtual reality realm in which a user could find materials that are soluble in water but not oil, for instance, and then be able to browse for similar materials nearby. “We envision a very interactive platform where the user can explore relations between data and desired material properties,” he said.
