Featured Researcher: Shahrad ShakerianPosted on March 12, 2021
Meet our new featured researcher, Shahrad Shakerian. Shahrad is doctoral student in architectural engineering who aims to predict failures in facility maintenance before they happen. His research focuses on reducing expenses of material and human resources by using predictive maintenance with the help of data science.
What is your academic background?
I’ve got a bachelor’s degree in civil engineering in 2017 and a master’s degree in construction engineering and management in 2019. Currently, I am a second-year Ph.D. student at Architectural Engineering Department at Penn State.
How did you get into this research field?
I was so interested in the application of new technologies in the construction industry. Working under supervision of Prof. Jebelli provided this opportunity to apply new emerging technologies such as wearable biosensors for different issues in the construction industry (e.g., workers’ safety). After working on the application of wearable biosensors for workers’ heat stress assessment, I started working on application of operational data collected from embedded sensors for failure prediction of building facilities.
What do you hope to accomplish with your research?
My research consists of four objectives and the goal of the research is designing a platform for facility maintenance management at Penn State. This platform continuously monitors and analyzes facilities’ operational data and aims to predict failures and send feedbacks to facility managers.
What are the big problems you hope this research solves?
Institutions like healthcare, military, and higher education have large and expansive building and infrastructure systems. Penn State for example, has multitude buildings in its portfolio worth over $7.5 billion in replacement value. All of these facilities are in various condition states requiring different levels of investment. This research aims to change the facility maintenance strategy from corrective maintenance to predictive maintenance, which can prevent frequent breakdowns in facilities and reduce expenses in terms of material and human resources.
What is the biggest surprise for you personally that has come out of your journey?
This journey familiarized me with the capabilities of data science and how new techniques in data analysis can solve vast variety of issues and reduce expenses for organizations, which was a great surprise for me. I used to think that only new technologies can solve long-lasting issues in different industries; however, new data analysis tools can offer new management strategies, which improve organizations’ performance with no additional costs.
What’s your favorite sound?
My favorite sound is the sound of piano specially when it is mixed with violin. This can make my day!
If you had unlimited money, what projects would you take on?
If I had unlimited money, after buying a mansion in Miami Beach, I would invest in projects related to artificial intelligence and electric cars as the future of smart cities.
What is your advice for would-be scientists?
My primary advice is to always improve your skills by self-education and self-learning through online courses and seminars, and not to only count on the courses you take at university.
What is in your song’s playlist?
My playlist mainly includes Drake songs and some deep house music.
What profession other than your own would you enjoy?
One of the professions that I really enjoy is real estate and I usually watch YouTube videos about that and follow successful people in this profession on social media such as Manny Khoshbin.
- Multi-institutional team to use AI to evaluate social, behavioral science claims
- NSF invests in cyberinfrastructure institute to harness cosmic data
- Center for Immersive Experiences set to debut, serving researchers and students
- Distant Suns, Distant Worlds
- CyberScience Seminar: Researcher to discuss how AI can help people avoid adverse drug interactions
- AI could offer warnings about serious side effects of drug-drug interactions
- Taking RTKI drugs during radiotherapy may not aid survival, worsens side effects
- Cost-effective cloud research computing options now available for researchers
- Costs of natural disasters are increasing at the high end
- Model helps choose wind farm locations, predicts output
- Virus may jump species through ‘rock-and-roll’ motion with receptors
- Researchers seek to revolutionize catalyst design with machine learning
- Resilient Resumes team places third in Nittany AI Challenge
- ‘AI in Action’: Machine learning may help scientists explore deep sleep
- Clickbait Secrets Exposed! Humans and AI team up to improve clickbait detection
- Focusing computational power for more accurate, efficient weather forecasts
- How many Earth-like planets are around sun-like stars?
- Professor receives NSF grant to model cell disorder in heart
- SMH! Brains trained on e-devices may struggle to understand scientific info
- Whole genome sequencing may help officials get a handle on disease outbreaks
- New tool could reduce security analysts’ workloads by automating data triage
- Careful analysis of volcano’s plumbing system may give tips on pending eruptions
- Reducing farm greenhouse gas emissions may plant the seed for a cooler planet
- Using artificial intelligence to detect discrimination
- Four ways scholars say we can cut the chances of nasty satellite data surprises
- Game theory shows why stigmatization may not make sense in modern society
- Older adults can serve communities as engines of everyday innovation
- Pig-Pen effect: Mixing skin oil and ozone can produce a personal pollution cloud
- Researchers find genes that could help create more resilient chickens
- Despite dire predictions, levels of social support remain steady in the U.S.
- For many, friends and family, not doctors, serve as a gateway to opioid misuse
- New algorithm may help people store more pictures, share videos faster
- Head named for Ken and Mary Alice Lindquist Department of Nuclear Engineering
- Scientific evidence boosts action for activists, decreases action for scientists
- People explore options, then selectively represent good options to make difficult decisions
- Map reveals that lynching extended far beyond the deep South
- Gravitational forces in protoplanetary disks push super-Earths close to stars
- Supercomputer cluster donation helps turn high school class into climate science research lab
- Believing machines can out-do people may fuel acceptance of self-driving cars
- People more likely to trust machines than humans with their private info
- IBM donates system to Penn State to advance AI research
- ICS Seed Grants to power projects that use AI, machine learning for common good
- Penn State Berks team advances to MVP Phase of Nittany AI Challenge
- Creepy computers or people partners? Working to make AI that enhances humanity
- Sky is clearing for using AI to probe weather variability
- ‘AI will see you now’: Panel to discuss the AI revolution in health and medicine
- Privacy law scholars must address potential for nasty satellite data surprises
- Researchers take aim at hackers trying to attack high-value AI models
- Girls, economically disadvantaged less likely to get parental urging to study computers
- Seed grants awarded to projects using Twitter data
- Researchers find features that shape mechanical force during protein synthesis
- A peek at living room decor suggests how decorations vary around the world
- Interactive websites may cause antismoking messages to backfire
- Changing how government assesses risk may ease fallout from extreme financial events
- Algorithm aims to alert consumers before they use illicit online pharmacies
- Deep learning may help doctors choose better lung cancer treatments
- Using cues and actions to help people get along with artificial intelligence
- Multi-university NSF grant to boost research computing expertise