Work with thought leaders and academic experts in Computational Theory and Mathematics

Companies can greatly benefit from working with experts in Computational Theory and Mathematics. These professionals possess advanced skills in data analysis, algorithm development, and problem-solving. By collaborating with them, companies can enhance their decision-making processes, optimize their operations, and develop innovative solutions. Computational Theory and Mathematics experts can also help companies improve their data security measures, identify patterns and trends in large datasets, and optimize complex systems. With their expertise, companies can gain a competitive edge in various industries, including finance, healthcare, technology, and logistics.

Researchers on NotedSource with backgrounds in Computational Theory and Mathematics include Ping Luo, Edoardo Airoldi, Hector Klie, Jeffrey Townsend, Dr. Justin Whalley, Ph.D, Dmitry Batenkov, Ph.D., Abbas Alameer, Oguzhan Kulekci, Denys Dutykh, Osaye Fadekemi, PhD, Anindya Ghose, and Suhang Wang.

Ping Luo

Toronto, Ontario, Canada
8 Years Experience
Assistant Professor at Algoma University
Education

University of Saskatchewan

Ph.D., Biomedical Engineering / September, 2019

Saskatoon, Saskatchewan, Canada

Beijing Institute of Technology

M.Eng., Biomedical Engineering / June, 2015

Beijing

Hunan University

B.Eng., Computer Science / June, 2010

Changsha
Experience

Princess Margaret Cancer Centre

Postdoctoral Researcher / November, 2019 — Present

I work in Dr. Trevor Pugh's lab and design cancer diagnosis and treatment strategies by analyze cell-free DNA and single cell sequencing data

Princess Margaret Cancer Centre

Bioinformatics Specialist / September, 2023 — Present

I work in Dr. Tak Mak's lab and study tumor immunology using single cell and TCR sequencing data.

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (22)
single-cell genomics
deep learning
complex network analysis
Genetics (clinical)
Genetics
And 17 more
About
8 years of science and engineering experience integrating multi-omics data to identify biomarkers for cancer studies. Seeking to apply data analytics expertise to develop new diagnosis and treatment strategies.

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Edoardo Airoldi

Professor of Statistics & Data Science Temple University & PI, Harvard University
Education

Università Bocconi

B.Sc., Institute for Quantitative Methods

Milano

Carnegie Mellon University

Ph.D., School of Computer Science

Pittsburgh, Pennsylvania, United States of America
Experience

Harvard University

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (44)
Statistics
Causal Inference
Network Science
Cell Biology
Molecular Biology
And 39 more
About
Edoardo Airoldi is a Professor in the Department of Machine Learning at Temple University. He is also the Director of the Center for Machine Learning and Health. He is a world-renowned expert in the fields of machine learning and artificial intelligence, with a focus on applications to health. Airoldi is a member of the prestigious Association for the Advancement of Artificial Intelligence (AAAI) and the International Machine Learning Society (IMLS). He has published over 200 papers in leading journals and conferences, and his work has been covered by various media outlets including The New York Times, The Wall Street Journal, The Economist, and Wired.

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Hector Klie

Houston, Texas, United States of America
21 Years Experience
CEO @ DeepCast.ai | AI-driven Industrial Solutions, Technical Innovation
Education

Ph.D., Computational Science and Engineering / May, 1997

Houston, Texas, United States of America

Master of Arts, Computational and Applied Mathematics / May, 1995

Houston

Simón Bolívar University

Master of Science, Computer Science / May, 1991

Caracas
Experience

DeepCast, LLC

CEO / May, 2017 — Present

ConocoPhillips Company

Staff Data Scientist / March, 2008 — April, 2016

Sanchez Oil and Gas

Director of Enterprise Data Solutions / March, 2016 — March, 2017

Design corporate data science platform, lead R&D in machine learning and AI to generate highly predictive models for field applications

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (24)
Artificial Intelligence
Machine Learning
Data Science
optimization
Computational Theory and Mathematics
And 19 more
About
**Results-driven AI leader with 20+ years of success spearheading model development and optimization initiatives in the energy industry and academia. Proven track record in leveraging computational data science, scientific machine learning, and AI to drive breakthrough physics-data solutions and deliver tangible business value. Adept at translating complex scientific concepts into robust AI models. Skilled in numerical simulation, scientific machine learning, and bilingual communication to optimize project outcomes.**

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Jeffrey Townsend

New Haven, CT, Connecticut, United States of America
29 Years Experience
Professor of Biostatistics and Ecology & Evolutionary Biology
Education

Harvard University

Ph.D., Organismic and Evolutionary Biology / May, 2002

Cambridge, Massachusetts, United States of America

Brown University

Sc.B., Biology / May, 1994

Providence, Rhode Island, United States of America
Experience

Yale University

Professor / July, 2018 — Present

Elihu Professor of Biostatistics / July, 2018 — Present

Elihu Associate Professor of Biostatistics / July, 2017 — June, 2018

Associate Professor / July, 2013 — June, 2018

Associate Professor / July, 2013 — June, 2017

Assistant Professor / July, 2006 — June, 2013

University of Connecticut

Assistant Professor / August, 2004 — May, 2006

St. Ann's School

Teacher / September, 1994 — June, 1997

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (53)
Evolutionary Genomics
Microbiology
Infectious Diseases
Genetics
Cell Biology
And 48 more
About
Jeffrey Townsend is a Professor of Organismic and Evolutionary Biology at Yale University. He received his Ph.D. from Harvard University in 2002 and his Sc.B. from Brown University in 1994. He has been a teacher at St. Ann's School and an Assistant Professor at the University of Connecticut. He is currently the Elihu Professor of Biostatistics at Yale University.

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Dr. Justin Whalley, Ph.D

North Chicago, Illinois, United States of America
9 Years Experience
Assistant Professor of Bioinformatics, with experience in finding the quintessential features in large, multi-layered 'omic datasets.
Education

Université d'Évry Val-d'Essonne

Ph.D., Bioinformatics / May, 2015

Évry

University of Bristol

M.Sci., Mathematics / June, 2008

Bristol
Experience

University of Oxford

Senior Bioinformatician / 2017 — 2022

Rosalind Franklin University of Medicine and Science Chicago Medical School

Assistant Professor of Bioinformatics / 2023 — Present

CNAG

Postdoctoral Researcher / 2014 — 2017

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (19)
Genomics
Bioinformatics
Immunity
Tensor decomposition
Cancer
And 14 more
About
Dr. Justin P. Whalley was educated in the UK (M.Sci. Mathematics, University of Bristol) and France (Ph.D. Bioinformatics, University of Évry). He moved to Spain to work as a postdoc at the National Center for Genomic Analysis (CNAG). During his time there, he ran the Quality Control working group for the Pan-Cancer Analysis of Whole Genomes project to assess the data coming in and reduce batch effects. This involved collaboration with researchers from the Broad Institute of MIT and Harvard, the German Cancer Research Center and the Wellcome Sanger Institute in the UK. He returned to the UK to work as a [Senior Bioinformatician at the University of Oxford](https://www.well.ox.ac.uk/people/jpw/). His time there coincided with the global pandemic and he was deeply involved in the COvid-19 Multi-omics Blood ATlas (COMBAT) consortium as the lead for the Integration (Tensor) working group. Dr. Whalley became a member of the [faculty of the Chicago Medical School at Rosalind Franklin University of Medicine and Science](https://www.rosalindfranklin.edu/academics/faculty/justin-p-whalley/) in January 2023.

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Dmitry Batenkov, Ph.D.

New York City, New York, United States of America
15 Years Experience
A highly experienced applied mathematician working in academia (faculty) and industry (consulting), with 15+ years of research and teaching expertise in inverse problems, signal processing, and data science.
Education

Weizmann Institute of Science

Ph.D., Applied Mathematics / January, 2014

Rehovot
Experience

Tel Aviv University

Assistant Professor / July, 2019 — Present

Producing high-impact research in inverse problems, super-resolution, numerical analysis, signal processing, physics-informed machine learning, computational harmonic analysis, optimization, atmospheric remote sensing • Advised 4 postdocs, 2 PhD, 4 M.Sc. students and 3 undergraduates • Developed and taught an advanced graduate class on Inverse Problems and Super-Resolution

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (31)
Applied Harmonic Analysis
Sparse Representations
Numerical Analysis
Approximation Theory
Inverse Problems
And 26 more
About
I am passionate about solving big problems with scientific and computational tools. A highly experienced applied mathematician working in academia (faculty) and industry (consulting), with 15+ years of research and teaching expertise in inverse problems, signal processing, and data science. A highly-skilled software engineer and analyst/architect with 6+ years of experience as a technical lead in professional software development.

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Abbas Alameer

9 Years Experience
Assistant Professor of Bioinformatics at Kuwait University
Education

University of Leicester

PhD in Bioinformatics and Molecular Modelling, Department of Molecular and Cell Biology / January, 2014

Leicester

University of Leeds

MRes in Bioinformatics and Computational Biology / December, 2006

Leeds
Experience

Kuwait University

Assistant Professor of Bioinformatics / February, 2014 — Present

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (11)
Bioinformatics
Computational Mathematics
Computational Theory and Mathematics
Computer Science Applications
Molecular Biology
And 6 more
About
Abbas Alameer is an Assistant Professor of Bioinformatics at Kuwait University. He received his PhD in Bioinformatics and Molecular Modelling from the University of Leicester in 2014 and his MRes in Bioinformatics and Computational Biology from the University of Leeds in 2006. He has over 10 years of experience in bioinformatics related research and teaching. His research focuses on the computational analysis and modelling of biological molecules, and the development of novel algorithms and Bioinformatics tools. He has published several articles in leading journals in the field and has presented his work at international conferences.

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Oguzhan Kulekci

25 Years Experience
Algorithm Engineer, Security/Privacy Researcher, Combinatorial Problem Solver
Education

Sabancı University

Ph.D., Computer Science / July, 2006

Istanbul
Experience

Indiana University

Visiting Professor / January, 2022 — Present

Istanbul Teknik Üniversitesi

Professor / November, 2015 — Present

national research institute of electronics and cryptology

Chief Researcher / January, 2007 — March, 2014

Design, analysis, and implementation of cryptographic security and privacy algorithms

Senior Researcher / June, 2004 — May, 2007

Design, analysis, and implementation of cryptographic security and privacy algorithms

Researcher / June, 1999 — June, 2004

Design, analysis, and implementation of cryptographic security and privacy algorithms

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (21)
algorithms
pattern matching
data compression
bioinformatics
security & privacy
And 16 more
About
My main expertise is in solving computational challenges with an innovative algorithm engineering approach. For more than two decades, I have been studying on such challenges originating from different fields mainly in cryptography and data security, natural language processing, information retrieval, computational biology, data compression and coding, massive data management, and most recently focusing on scalability and security aspects of ML/AI algorithms. I have been devising efficient innovative solutions and/or improving current state-of-art in terms of resource usage, e.g., time, memory, energy, communication costs. I would like to provide a summary of my previous achievements in engineering, research, and administration. Engineering Expertise: After spending around two years on programming point-of-sales devices and regular database programming, I have spent 10+ years in cryptography, where the main focus had been efficient implementation and cryptanalysis of the security&privacy algorithms and protocols both in hardware and software. During those years, despite gaining experience on how to develop programs that run fast and/or with small memory footprint, I had the chance to work with talented mathematicians and hardware engineers, that gave me the opportunity to widen my knowledge on different dimensions, including reverse engineering and FPGA/ASIC design. I also learned a lot on how to develop projects with a team of talent coming from different disciplines. I have observed, and today strongly believe, that theoretical knowledge is vital, but never enough to built efficient systems in practice. The platform that the solution will be executed on and the properties of the input data should always be considered for ground-breaking progress in practical performance. Theory without practice, or vice versa, is akin to trying to fly with one wing. In that sense, the development of the fastest pattern matching solutions and innovating patents that are licensed to companies have been exemplary outcomes of my perspective. Academic Expertise: Following my 15+ years in industry, I joined academia and have been serving as a professor of computer sci- ence. I succeeded to get several research grants and have been also serving in the committees of conferences. Actually, I started publishing in scientific venues when I was with the industry as well. I did my phd on natu- ral language processing, after which I got more engaged with combinatorial algorithms. I mostly published on data compression, combinatorial pattern matching and applications of them on computational biol- ogy/bioinformatics. Most recently, I have been studying scalablity and security aspects in ML/AI systems as well as in information retrieval. I have also experience in massive data management and analysis. I have been teaching courses on algorithms, security/privacy, and related topics. Administrative Expertise: After engineering cryptography for many years, I changed my focus to computational biology, particularly the genomics area. I have served as the deputy director of the National Institute of Genetics and Biotechnology of Turkey for two years, during which I was responsible for the establishment of the first high-throughput DNA sequencing facility of the country. That leadership equipped me with a unique experience of leading an interdisciplinary project with people from computing and life sciences disciplines. The establishment of the lab was supported with more than 2 million dollars grant by the government and was successfully completed in two years. Another leadership experience I had was being the program coordinator of the graduate programs in my university for more than four years. I was responsible by curriculum development and hiring new faculty. I have also served previously as principal investigator in research projects, lead research labs, and delivered project lead positions in industry projects.

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Denys Dutykh

16 Years Experience
Professional Applied Mathematician, Modeller, and Advisor
Education

École Normale Supérieure Paris-Saclay

PhD, Centre de Mathématiques et de Leurs Applications / December, 2007

Cachan
Experience

Centre National de la Recherche Scientifique

Research scientist / October, 2008 — August, 2022

Professional scientific research in the field of Applied Mathematics

Khalifa University of Science and Technology

Associate Professor / August, 2022 — Present

Professional research and educational activities in the field of Applied Mathematics

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (51)
Applied mathematics
fluid mechanics
scientific computing
numerical methods
Fluid Flow and Transfer Processes
And 46 more
About
Dr. Denys Dutykh initially comes from the broad field of Applied Mathematics. He did his Master's degree in numerical methods applied to the problems of Continuum Mechanics and a Ph.D. thesis at Ecole Normale Supérieure de Cachan (France) on the mathematical modeling of tsunami waves. After this, he was hired as a permanent research scientist at the Institute of Mathematics (INSMI) at the Centre National de la Recherche Scientifique (CNRS). His research activities have been conducted in the following years at the picturesque University Savoie Mont Blanc (USMB, France) in the field of mathematical methods applied to the modeling and simulation of nonlinear waves (mostly in Fluid Dynamics). The Habilitation thesis of Dr. Dutykh was defended there on the topic of the mathematical methods in the environment. Since then, his research interests have significantly broadened to include the Dimensionality Reduction methods in Machine Learning, modeling of PV panels, and even some more theoretical questions in the Number Theory.

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Osaye Fadekemi, PhD

4 Years Experience
Assistant Professor of Mathematics at Alabama State University with expertise in Graph Theory and Network Modeling
Education

University of Johannesburg

Doctor of Philosophy, Department of Pure and Applied Mathematics / July, 2019

Auckland Park

University of KwaZulu-Natal

Master of Science, School of Mathematics, Statistics and Computer Science / March, 2015

Durban

African Institute For Mathematical Sciences Ghana

Master of Science, Mathematical Sciences / June, 2013

Biriwa
Experience

Auburn University Auburn

Visiting Asisitant Professor / August, 2019 — May, 2021

Alabama State University

Assistant Professor / June, 2021 — Present

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (12)
Graph Theory
Network Modeling
Disease Modeling
Discrete Mathematics and Combinatorics
Theoretical Computer Science
And 7 more
About
Dr Fadekemi Janet Osaye is a mathematician whose primary research interest is in graph theory and network modeling. In particular, she is interested in distance measures in graphs and their applications to solving many real-world problems. Her interest in discrete mathematics was inspired by her research project carried out at AIMS Ghana. She has published several articles in reputable journals and has presented in several conferences across the globe. In 2019, she became the first black female to be awarded a PhD in Mathematics by the University of Johannesburg, South Africa, in its 116 years of its existence. Since June 2021, she has been an Assistant Professor of Mathematics at Alabama State University and was previously a Visiting Assistant Professor at Auburn University. She is the founder of GirlsMatics Foundation, a STEM non-governmental organisation for girls in Nigeria which was motivated by her involvement with AIMS Ghana’s outreach programs for high school students in Biriwa, Ghana. She is also the co-founder of FadNna Partners, an analytics and management firm based in Lagos, Nigeria.

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Anindya Ghose

6 Years Experience
Heinz Riehl Chair Professor of Business, NYU Stern
Education

Carnegie Mellon University

PhD, Information Systems / 2004

Pittsburgh, Pennsylvania, United States of America

Carnegie Mellon University

MS, Information Systems / 2002

Pittsburgh, Pennsylvania, United States of America

Indian Institute of Management Calcutta

MBA, Finance, Marketing, & Information Systems / 1998

Kolkata
Experience

NYU Stern School of Business

Heinz Riehl Chair Professor of Business / 2017 — Present

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (22)
Data Science
Mobile
Data Privacy
Digital Marketing
Digital Platforms
And 17 more
About
Dr. Anindya Ghose is the Heinz Riehl Chair Professor of Business at New York University Stern School of Business. His research interests are in the areas of IT-enabled platforms, services and products, including mobile apps, social media, digital marketplaces, and big data analytics. He has also done work on understanding consumer behavior in digital environments. He has published over 130 papers in academic journals and has been honored with several best paper awards. He has also served on the editorial boards of several journals, including Management Science, Information Systems Research, and MIS Quarterly. He is a Fellow of the Institute for Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM).

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Suhang Wang

5 Years Experience
Professor at Pennsylvania State University
Education

Arizona State University

PhD, Computer Science / July, 2018

Tempe, Arizona, United States of America

University of Michigan

MS, Electrical Engineering: Systems / December, 2013

Ann Arbor, Michigan, United States of America

Shanghai Jiao Tong University

BS, Electrical and Computer Engineering / July, 2012

Shanghai
Experience

Pennsylvania State University

Assistant Professor / August, 2018 — Present

Most Relevant Research Expertise
Computational Theory and Mathematics
Other Research Expertise (21)
Machine learning
Graph Mining
Theoretical Computer Science
Information Systems and Management
Computer Science Applications
And 16 more
About
Dr. Suhang Wang is an Assistant Professor of Computer Science and Engineering at Pennsylvania State University. He received his PhD in Computer Science from Arizona State University in 2018, and his Master's degree in Electrical Engineering: Systems from the University of Michigan in 2013. Before joining Penn State, Dr. Wang was a postdoctoral researcher at the University of California, Santa Barbara. His research interests include natural language processing, artificial intelligence, and machine learning. He was recognized for his work at the International Conference on Knowledge Discovery and Data Mining in 2017 and the Fifth ACM International Conference on Web Search and Data Mining in 2016.

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Example Computational Theory and Mathematics projects

How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on Computational Theory and Mathematics?

Optimizing Supply Chain Operations

A company in the logistics industry can collaborate with a Computational Theory and Mathematics expert to optimize their supply chain operations. By analyzing large datasets and applying advanced algorithms, the expert can identify bottlenecks, optimize routes, and minimize costs. This collaboration can lead to improved efficiency, reduced delivery times, and increased customer satisfaction.

Developing Fraud Detection Systems

In the finance industry, a company can benefit from working with a Computational Theory and Mathematics expert to develop fraud detection systems. The expert can analyze transaction data, identify patterns of fraudulent activities, and create algorithms to detect and prevent fraud. This collaboration can help the company protect its assets, reduce financial losses, and maintain the trust of its customers.

Predictive Analytics in Healthcare

A healthcare organization can collaborate with a Computational Theory and Mathematics expert to leverage predictive analytics. By analyzing patient data, the expert can develop models to predict disease outcomes, identify high-risk patients, and optimize treatment plans. This collaboration can lead to improved patient care, reduced healthcare costs, and better resource allocation.