Meet the Experts

Peter Morales is an AI Research Scientist with a decade of experience at BAE Systems, MIT Lincoln Laboratory, and Code Metal AI Labs. His expertise spans reinforcement learning and computer vision, with notable publications in top-tier conferences and a best paper award at AAMAS. At MIT, Peter was a foundational member of the AI Technology group, spearheading automation and robotics projects for the Air Force. His contributions include devising and bringing to production algorithms that safeguard the F-35 joint strike fighter and the U.S. Capitol from UAS threats, and developing the fusion engine behind the U.S. Army Hololens' scene understanding platform. Additionally, Peter has successfully founded a VC backed company that was acquired in 2022.

Alex Showalter-Bucher spent a decade developing algorithms, modeling/simulation, and AI capabilities for national security at MIT Lincoln Laboratory. He has worked with OSD, Navy, Army, MDA, and DHS. Alex was affiliated with ALERT, a DHS Center of Excellence, and is Gordon Institute of Engineering Leadership Fellow. He holds advanced degrees in Electrical Engineering and Computer Science with a specialization in AI.

Dr. Octavian Udrea is a distinguished AI Research Scientist with 20 years of experience at IBM Research AI, Dataminr, and Code Metal. His expertise spans neuro-symbolic AI, large-scale machine learning, automated code generation, knowledge graphs, and distributed systems. At IBM, Dr. Udrea played a pivotal role in developing IBM Streams (formerly System S), the first commercial stream processing platform. He also led the creation of an auto-ML platform for streaming data tailored for defense applications, the award-winning IBM Scenario Planning Advisor, and co-invented a top-tier knowledge graph platform integrated into DB2. At Dataminr, he spearheaded the development of a knowledge platform that provides intelligent context for alerts from over a million sources around the clock. Dr. Udrea has authored over 70 peer-reviewed publications and patents and has received multiple best demonstration awards for his contributions to the field.

Niranjan Hasabnis is Principal Research Scientist at CodeMetal. Niranjan brings years of research and engineering experience in both academia as well as companies such as Intel. At Intel, he was exploring applications of AI, ML, and formal method techniques to solve problems in compilers, high-performance computing (HPC), software systems, and software engineering. He also implemented and open-sourced an autonomous system, named ControlFlag, that learns to detect programming errors in code. ControlFlag is has been covered by several news outlets such as Communications of ACM, Venturebeat, ZDNet, TechRepublic, etc. Previously, Niranjan obtained his PhD in Computer Science from Stony Brook University, where he conducted research in program analysis, ML, and compilers. Niranjan has published in top-tier computer science conferences such as CGO, ASPLOS, FSE, among others. He regularly serves on the program committees of various conferences such as ICSE, FSE, USENIX ATC, etc. He holds 11 patents in the areas of compilers, computer architecture, machine learning, and code optimizations.

Ellie Kitanidis is an AI researcher focused on generative and agentic AI. She previously worked on the core research team at Imbue, where she helped train a 70B-parameter LLM from scratch and co-authored papers on topics spanning LLM safety, multi-task reinforcement learning environments, and black box optimization. Prior to Imbue, Ellie completed a research fellowship at OpenAI. Before venturing into the world of AI, she received her Ph.D. in physics from UC Berkeley, where she developed methods to test cosmology models with galaxy surveys. During her Ph.D., Ellie was a core member of DESI, a $75M initiative to produce the largest ever 3D map of the Universe, and received its Builder Award for outstanding contributions. She also holds a bachelor's degree in physics from Stanford.

Dr. Samson Melamed served as the Director of Research at GLC Technologies, Inc. in Huntsville, AL and at Skydisc, Inc. in Fukuoka, Japan.  He was a Post-Doctoral Researcher and Invited Researcher with the National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan.  His current research interests include thermal simulation and modeling, heterogeneous integration, and security for microelectronics. Dr. Melamed is a member of the IEEE, has authored or co-authored over 30 conference and journal papers, and has been awarded one patent.  He has served on technical program committees, given keynotes, and chaired technical sessions at international conferences.

Education
Ph.D. Electrical Engineering; North Carolina State University, 2011M.S.
Electrical Engineering; North Carolina State University, 2007
B.S. Computer Engineering; University of Maryland Baltimore County, 2004

Laura Titolo is a principal research scientist at CodeMetal. She has over a decade of experience developing and applying formal methods to safety-critical systems.

She received her Ph.D. in Computer Science from the University of Udine (Italy) in May 2014. Before joining CodeMetal, Laura was a research scientist at NASA Langley for over 9 years working in the Safety-Critical Avionics Systems Branch. From 2014 to 2015, She worked as a postdoctoral researcher at the University of Malaga (Spain) in the MORSE research group.

Her research interests include every aspect of formal methods, including static analysis, abstract interpretation, model checking, and theorem proving. In particular, she worked on developing new tools for the formal verification and analysis of safety-critical avionics applications.

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Tzofi is a researcher in computer vision, computational imaging, and perception. His research focuses on AI-driven computational design, hardware-software co-design, and neural rendering/simulation. He brings years of research experience in both academia and companies, such as Amazon, NVIDIA, and Meta, and has published at top computer vision venues including CVPR, ICCV, ECCV, and ICCP. Tzofi is also a PhD candidate and Qualcomm Innovation Fellow at the Massachusetts Institute of Technology

Ben Rosenberg is a seasoned technology leader with over 20 years of experience in building and securing large-scale applications and services across the music, sports, gaming, magazine, and blockchain industries. He has worked with prominent clients such as Netflix, ESPN, Major League Baseball, the NFL, Sterling Sound, Condé Nast, and Hearst Corporation. As both a consultant and a director of large teams, Ben has led projects from initial concept to full deployment, implementing cutting-edge technologies and methodologies to meet client needs. He has also played a crucial role in growing startup companies and securing partnerships with other industry-leading firms. His extensive expertise spans software development, application security, project management, and strategic consulting. Ben has also appeared on panels and discussions about innovative blockchain and gaming technologies, including those hosted by Amazon

Armand is a Research Engineer with experience in shipping machine learning research code to large infrastructure. He has developed firmware and fleet communication systems for Aerospec during his time in SEAL at the University of Washington. He brings experience in building predictive pipelines as an engineer at Expedia Group focused on cancellation and metasearch bidding.

Sanjna is a research engineer with extensive experience in machine learning, particularly in robotics, computer vision, and hardware systems. She holds both her Master’s and Bachelor’s degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT). Prior to her current role, she worked as a software engineer at Google, building applications for managing hardware resources and payments for Google Cloud Platform (GCP). Her research experience includes work at MIT, NASA, JPL, and IBM Research, where she has contributed to advanced projects involving reinforcement learning for robotics hardware and simulation, perception models for large-scale datasets, and algorithms for control, navigation, and localization.

Rod Izadi is a Research Engineer with experience in developing and optimizing detection algorithms for infrared (IR) spectroscopy. During his time at Block Engineering, he played a key role in establishing and maintaining data quality standards, ensuring the integrity of datasets critical to algorithm development. Rod holds a Master’s in Electrical Engineering from Clarkson University, where he focused on Deep Learning and Machine Learning Applications. His research, combining face quality assessment with detection models, was presented at the 2023 International Workshop on Biometrics and Forensics. Rod has worked on a range of projects, from drone piloting using hand gestures to autonomous robotics, reflecting a broad interest in technology and problem-solving.

Tom is a Research Engineer with expertise in computer vision and autonomous systems. Prior to his current role, he was a Machine Learning Engineer at KLA, where he utilized synthetic data and machine learning models to address computer vision challenges at the nano-scale. He holds an M.Sc. in applied mathematics, with research on autonomous agents published in IEEE T-RO.

Matthew Freihofer is a Research Engineer at CodeMetal. Prior to joining, he worked at Qualcomm on the Machine Learning Group’s GPU team. At the Machine Learning Group, he focused on the development of the Qualcomm AI Engine Direct SDK. Matt has also contributed to the Galileo Project out of Harvard University, and has expertise in low-level development of machine learning applications targeting the utilization of GPU’s for AI inference and classification. Matt obtained a BSCS at Drexel University in 2019 and brings experience in developing AI applications for low-level GPU deployment.

Zander is a technical author and AI researcher at the University of Washington. His publication, Language Models: A Guide for the Perplexed, explores the current landscape, capabilities, and future of large language models with co-authors Prof. Noah Smith and Sofia Serrano. He is a multiple time best-selling textbook author, with works on programming and game development. Zander is part of Noah Smith's ARK lab where his research focuses on the improvement of language models for real-world settings.