Work with thought leaders and academic experts in discrete mathematics combinatorics

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.

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.

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.

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.

Wesley R. Hartmann is a Professor at the Graduate School of Business at Stanford University. He received his PhD in Economics from the University of California, Los Angeles in 2003, and his MA in Economics from the University of California, Los Angeles in 2001. He also holds a BA in Economics and Political Science from the University of California, Irvine.

Robert Granat, Ph.D. is a highly accomplished machine learning and remote sensing expert with extensive experience in research and development. He received his Ph.D. in Electrical Engineering in 2004 and his M.S. in Electrical Engineering in 1998. He has held various leadership positions in both academia and the private sector, including CTO and Head of Science at CarbonSpace Ltd, a company focused on developing novel methods for carbon measurement using satellite observations. Dr. Granat's expertise lies in the fields of machine learning, Earth science, and remote sensing technologies. He has a strong background in developing algorithms and software systems for remote sensing measurement technologies and data analysis. His work has been instrumental in advancing the understanding of climate change and its impacts on the environment. Prior to his work at CarbonSpace Ltd, Dr. Granat held several research positions at the Research Foundation of City University of New York and Jet Propulsion Laboratory (JPL). At JPL, he served as the Science Team Algorithms Lead for the OCO-2 mission, a satellite mission dedicated to measuring carbon dioxide levels in Earth's atmosphere. He also served as the Group Supervisor for the Machine Learning and Instrument Autonomy Group at JPL. Dr. Granat's contributions to the fields of machine learning, geophysics, and climate science have been recognized with numerous awards and publications. He is a member of several professional organizations, including the Institute of Electrical and Electronics Engineers (IEEE) and the American Geophysical Union (AGU). In addition to his professional achievements, Dr. Granat is also dedicated to sharing his knowledge and expertise with the next generation of engineers and scientists.