Dr. Marx Akl stands as a distinguished physicist, holding a Ph.D. in Physics from the esteemed Rensselaer Polytechnic Institute, where his groundbreaking dissertation delved into "The Mechanical Response of Materials at the Nanoscale via Simulations." This academic prowess extends to master's degrees in Physics and Mechanical Engineering from RPI and the University of Southern California, underscoring a comprehensive and well-rounded educational journey.
With a rich tapestry of over a decade in research and professional experience, Dr. Akl occupies a unique intersection of Computational Physics, Material Science, and the avant-garde applications of machine learning and data science. His expertise is not confined to the theoretical realm; instead, it's a dynamic interplay with practical applications. Dr. Akl is renowned for employing sophisticated techniques such as density functional theory (DFT) and molecular dynamics (MD) modeling and simulations, unveiling new perspectives in solid-state
physics and materials. What sets Dr. Akl apart is his ability to seamlessly traverse diverse domains, where his work becomes a nexus of modern materials, theoretical and quantum physics, and the cutting edge of machine learning. This distinctive skill set positions him as a driving force in groundbreaking advancements at the confluence of these disciplines. Dr. Akl's journey is not just one of academic achievements but a testament to his capacity to merge theoretical insights with tangible, real-world applications, making him a transformative force in the realms of physics and data science.

Chris DeGrendele is a computation scientist who is working on his Ph.D. in Applied Mathematics at the University of California Santa Cruz. He is currently a researcher at NASA Ames Research Center in the Advanced Supercomputing Division - Computational Aerosciences Branch.

Pragati Dharmale has 14 years of academia / industry research experience and received her M. Eng in Digital electronics and M.S. in computer science from Southern New Hampshire University, NH.  Her research interest includes application of EEG analysis with machine learning (ML) and artificial intelligence (AI), as well as STEM based applications designed for Raspberry PI with Python programming. 

Prof. Downing has 40 years of industry research experience from 3COM and IBM and as a former adjunct professor. The Downing research group applies the tools of data mining and data science to astronomy and cryptography. Through applied computer science and data science, the group hopes to move towards deciphering the Voynich manuscript and also detecting near-earth objects using signal-to-noise detection mining of NASA datasets. He is also the director for the Astrophysics Research Institute at ASDRP.

Mr. Prabin Lamichhane received his MS in Mathematics and Statistics from South Dakota State University and comes to ASDRP with several years of experience in developing data models for applications in industry. statistical analysis, machine learning, and data visualization. During his academic journey, Prabin collaborated on impactful research projects, delving into topics such as predictive modeling, natural language processing, and forensic analysis as well. As a data analyst at CNA Insurance, I honed my skills in data manipulation and interpretation. Prabin is experienced in utilizing a diverse set of tools, including Python, R, and SQL, to analyze large datasets, identify patterns, and develop data-driven strategies. Outside of the professional sphere, Prabin is an advocate for and actively participates in data science communities, attends industry conferences, and contributes insights to open-source projects. 

Joseph Laurienzo is an ambitious interdisciplinary scientist specializing in latent pattern recognition and simulation of physical and biological systems. Joseph received his BS in math and physics and MS in applied math from Case Western Reserve University, along with a BA in Japanese, and has collaborated with the University of Tokyo in condensed matter physics. Joseph’s research interests include the application of novel mathematical techniques in the assessment of brain activity patterns to construct cognitive models, as well as game theory. Joseph’s personal interests include world literature, Jiu Jitsu, and competitive Esports.

Mr. Dennis Liu is a product of Georgia Tech (MS Computer Science / Human Computer Interaction) and UC San Diego (BS Mathematics - Computer Science; BS Cognitive Science / Human Computer Interaction). Prior to joining us this spring in his new role, Dennis has previously served on ASDRP's admissions team, and will be assuming the role of Director of IT in addition to leading research groups at ASDRP in the fields of computer and cognitive science. Dennis comes to ASDRP with 8 years of IT experience - from UC San Diego Information & Technology Services as a Service Desk Technician, IBM Quantum as both a client facing technical support developer and software engineer, and more recently at VIZIO as a software engineer - prior to rejoining ASDRP.

Dr. McMahan received his M.S. and Ph.D. from Rice University. His research group utilizes computer science modeling to understand phenomena at the quantum level and is interested in quantum computing applied to small molecule and single-atom perturbations, materials science and engineering, and chaos theory as it relates to chromodynamics and photophysical phenomena. Dr. McMahan oversees our quantum computing emulator.

Dr. Mui received his B.Sc., M. Eng, and PhD from the Massachusetts Institute of Technology (MIT) and an M.Phil from Oxford as a Marshall Scholar, and is currently a Senior Vice President of technology at SalesForce. The Mui group studies the impact of computer algorithms (particularly machine learning and artificial intelligence) on society at large.  His recent students are engaged in research on algorithmic bias, AI ethics, data analyses of impact of the pandemic and the justice system on different groups around the world.

Suresh is a seasoned executive and data scientist with experience in managing large operations and applying data science to solve business problems. His group works on data science and its various applications to society, policy, and organizations. 

Ana Simoes is a Ph.D. in Psychological Sciences from the University of California, Merced, where she specialized in Quantitative Methods, Measurement, and Statistics. Her research focused on advanced statistical methods in psychology, such as factor analysis and structural equation modeling for both continuous and categorical variables. Ana is currently a lecturer at UC Merced, teaching undergraduate courses in psychology, including Introduction to Psychology, Analysis of Psychological Data, and Research Methods. Originally from Brazil, Ana combines her diverse academic background with practical skills in programming and data science. At ASDRP, she aspires to continue her research in the field of applied sports analytics.

Dr. Huifang Qin received her PhD in EECS from UC Berkeley. Huifang brings over 20 years of experience solving technology and business problems with data science. She led Data Science teams in autonomous driving, social media, digital advertising and finance technology companies to conduct research and build impactful products. Her group at ASDRP conducts finance research through practicing data science skills including data mining, statistical analysis, predictive modeling and optimizations.