What is he best known for?
The fields of study he is best known for:
- The Internet
- Artificial intelligence
- Computer network
B. Aditya Prakash mainly investigates Graph, Theoretical computer science, Graph theory, Artificial intelligence and Spotting.
His Graph research focuses on subjects like Network topology, which are linked to Router.
B. Aditya Prakash interconnects Vulnerability, Complex network, Topology and Viral marketing in the investigation of issues within Theoretical computer science.
His Graph theory study deals with Network security intersecting with Robustness.
In his research, he performs multidisciplinary study on Artificial intelligence and Product.
His study in Spotting is interdisciplinary in nature, drawing from both Analytics and Data science.
His most cited work include:
- Rise and fall patterns of information diffusion: model and implications (245 citations)
- Spotting Culprits in Epidemics: How Many and Which Ones? (168 citations)
- Gelling, and melting, large graphs by edge manipulation (151 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Theoretical computer science, Artificial intelligence, Graph, Data mining and Machine learning.
His studies deal with areas such as Node, Graph theory, Representation and Viral marketing as well as Theoretical computer science.
His work in the fields of Artificial intelligence, such as Feature extraction, overlaps with other areas such as Product.
In the subject of general Graph, his work in Power graph analysis is often linked to Term, thereby combining diverse domains of study.
His biological study spans a wide range of topics, including Efficient algorithm, Critical infrastructure and Segmentation.
As a member of one scientific family, B. Aditya Prakash mostly works in the field of Machine learning, focusing on Social network and, on occasion, Social media.
He most often published in these fields:
- Theoretical computer science (25.26%)
- Artificial intelligence (21.05%)
- Graph (20.00%)
What were the highlights of his more recent work (between 2018-2021)?
- Pandemic (3.16%)
- Artificial intelligence (21.05%)
- Machine learning (13.68%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Pandemic, Artificial intelligence, Machine learning, Critical infrastructure and Outbreak.
He mostly deals with Deep learning in his studies of Artificial intelligence.
His Deep learning research is multidisciplinary, relying on both Artificial neural network, Leverage and Noisy data.
His studies in Critical infrastructure integrate themes in fields like Data mining and Greedy algorithm.
His work deals with themes such as Ground truth, Segmentation and Robustness, which intersect with Data mining.
His Sample research overlaps with Redundancy, Theoretical computer science, Local area network and Minimum description length.
Between 2018 and 2021, his most popular works were:
- EpiDeep: Exploiting Embeddings for Epidemic Forecasting (24 citations)
- DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting (11 citations)
- Designing Effective and Practical Interventions to Contain Epidemics (5 citations)
In his most recent research, the most cited papers focused on:
- The Internet
- Artificial intelligence
- Machine learning
Machine learning, Artificial intelligence, Deep learning, Artificial neural network and Scientific modelling are his primary areas of study.
His Machine learning study frequently draws connections to other fields, such as Noisy data.
His Artificial neural network study spans across into areas like Outbreak, Pandemic and Flexibility.
His Scientific modelling research incorporates Probabilistic logic, Econometrics, Staffing, Independent research and Geospatial analysis.
B. Aditya Prakash undertakes multidisciplinary investigations into Probabilistic logic and High variability in his work.
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