Floating-Point Arithmetic Professors and Supervisors

Тетяна Сергіївна ДьячукView profile

Senior Lecturer

Transilvania University of BrasovRomania

Тетяна Сергіївна Дьячук є старшим викладачем кафедри комп'ютерних систем та мереж Факультету комп'ютерних наук і технологій Запорізької національної технічної політехніки, де працює з 2006 року після закінчення університету з відзнакою. Вона є активним членом академічної спільноти, зосереджуючись на сучасних напрямках комп'ютерних наук та технологій. Освіта: Запорізька національна технічна політехніка, 2006 рік, спеціальність "Комп'ютерні системи та мережі", кваліфікація "Магістр комп'ютерних систем та мереж" (з відзнакою) Запорізька національна технічна політехніка, 2006 рік, кваліфікація "Менеджер-економіст" Наукові інтереси Тетяни Сергіївни охоплюють ключові напрями сучасних комп'ютерних технологій, зокрема розподілені та паралельні обчислення, блокчейн-технології, децентралізовані платформи та оптимізацію обчислень. Вона також активно займається дослідженнями в галузі Android-програмування та розробки мобільних додатків. Її наукова робота характеризується практичною спрямованістю, що знаходить відображення в численних публікаціях та конференціях. Аналіз наукових публікацій Тетяни Сергіївни показує чітку еволюцію її наукових інтересів від фундаментальних досліджень розподілених систем та алгоритмів планування ресурсів до сучасних технологій блокчейну, штучного інтелекту та автоматизації процесів програмування. Особливо вражає її здатність поєднувати теоретичні дослідження з практичними застосуваннями в різних галузях, від медичної діагностики до розробки мов високого рівня. Наукові досягнення: Понад 15 наукових публікацій в провідних наукових виданнях Активна участь у міжнародних наукових конференціях Реєстрація в наукометричних базах: Scopus, Web of Science, Google Scholar, ORCID Тетяна Сергіївна активно бере участь у науково-педагогічній діяльності, викладаючи курси, що відповідають сучасним тенденціям в комп'ютерних науках. Вона також займається науковою роботою зі студентами, сприяючи їх інтеграції в наукову спільноту через участь у наукових конференціях та проєктах. Незважаючи на те, що конкретні науково-дослідні гранти не зазначені в доступних джерелах, її публікаційна активність та участь у конференціях свідчать про продуктивну наукову діяльність. Хоча конкретні лабораторії або наукові групи, якими керує Тетяна Сергіївна, не зазначені в доступних джерелах, її наукова робота тісно пов'язана з розвитком сучасних технологій розподілених систем та обчислень, що ймовірно відбувається в рамках кафедри комп'ютерних систем та мереж Запорізької політехніки.

Official University Profile

Зеленьова Ірина ЯківнаView profile

Associate Professor

Transilvania University of BrasovRomania

Dr. Irina Zeleneva is an Associate Professor at the Department of Computer Systems and Networks, Faculty of Computer Science and Technologies, Zaporizhzhia Polytechnic National University. With a Ph.D. in Computers, Systems, and Networks, she has 15+ years of academic experience since joining the university in 2003. Specializes in FPGA-based digital system design Focuses on hardware acceleration and reliability optimization Teaches advanced topics in microprocessor architecture Her research includes: Development of energy-efficient FPGA systems Hardware-software co-design Neural network text classification accelerators Reliable embedded control architectures Recent publications analyze FPGA implementation of floating-point multipliers, finite state machines with elementary state chains, and AI-enhanced educational frameworks . Her work frequently appears in international conferences like IDAACS and PIC S&T, with multiple Scopus/WoS indexed articles. Dr. Zeleneva's contributions: Co-author of two monographs on FPGA acceleration PI in multiple university research projects Active participant in annual "Week of Science" conferences

Official University Profile

Голуб Тетяна ВасилівнаView profile

Associate Professor

Transilvania University of BrasovRomania

Голуб Тетяна Василівна serves as an Associate Professor in the Department of Computer Systems and Networks at Zaporizhzhia National Technical University's Faculty of Computer Science and Technologies. With over 12 years of academic experience since joining the university in 2011, she specializes in computer electronics, computer circuitry, signal and image processing, and reliability of computer systems. Dr. Golub's research focuses on text processing algorithms, text classification, and data processing with particular emphasis on hardware acceleration using FPGA technologies. Her work bridges theoretical computer science with practical engineering applications, developing efficient methods for natural language processing tasks through specialized hardware implementations. She has pioneered approaches to optimize text classification speed while maintaining accuracy through innovative vector space modeling and stemming algorithms. Her publication record shows a strong trajectory from foundational work on text classification methods (2019) through hardware acceleration techniques (2020-2021) to current research on AI applications in education and neural network-based classification systems (2023-2025). The research demonstrates consistent focus on improving computational efficiency of text processing systems while expanding into educational technology applications. Dr. Golub maintains active scholarly presence with verified profiles on Scopus (ID: 57189328111), Web of Science (Researcher ID: G-9688-2019), Google Scholar, and ORCID (0000-0001-6024-008X), reflecting her commitment to academic transparency and international scholarly communication. She teaches core computer engineering subjects while conducting research that combines theoretical computer science with practical hardware implementation. Her laboratory work in computer electronics provides students with hands-on experience in circuit design and digital systems. Fluent in English, Ukrainian, and Russian, Dr. Golub operates from room 53b at the university's Zaporizhzhia campus (69063, Ukraine, Zhukovsky Street, 64).

Official University Profile

Ali GÜLBAĞView profile

Associate Professor

Sakarya UniversityTurkey

Assoc. Prof. Dr. Ali GÜLBAĞ is an academic at the Faculty of Computer and Information Sciences , Sakarya University , specializing in Computer Engineering . His career spans over two decades, focusing on FPGA-based hardware design, machine learning applications, and educational methodologies in computer architecture. Doctorate (2003-2006): Quantitative determination of volatile organic compounds using artificial neural network and fuzzy logic-based algorithms MSc (1998-2000): Building automation using telephone lines BSc (1994-1998): Electrical-Electronics Engineering His research interests include Artificial Neural Networks , FPGA Design , and Water Resource Management , with applications in seismic event differentiation, environmental modeling, and educational technologies. Recent work emphasizes water consumption prediction using machine learning. Key projects: BZK.SAU.FPGA microcomputer architecture , Remote FPGA laboratories Publications demonstrate expertise in combining machine learning techniques (ANNs, gradient boosting, random forests) with hardware implementations for real-world problem-solving.

Official University Profile

Eric ReinerView profile

Adjunct Professor

University of California, Los AngelesUnited States

Eric Reiner serves as an Adjunct Professor of Finance and Faculty Director of the Master of Financial Engineering program at UCLA Anderson School of Management. His unique academic profile bridges finance and formal methods, combining financial engineering expertise with advanced computational verification techniques. Dr. Reiner's research spans two distinct domains: traditional finance and formal methods in computer science. His work in formal methods focuses on satisfiability modulo theories (SMT), bit-precise reasoning, and model checking, with publications appearing in leading formal methods venues. This unusual interdisciplinary approach suggests innovative applications of verification techniques to financial systems, potentially addressing challenges in algorithmic trading verification, risk model validation, and financial protocol security. Analysis of his recent publications (2022-2024) reveals a strong focus on improving SMT solver capabilities, particularly for bit-vector reasoning and user extensibility. His work shows progression from theoretical foundations toward practical industrial applications, with increasing attention to proof generation, solver performance optimization, and machine learning techniques for algorithm selection. The consistent publication record in formal methods venues indicates deep technical expertise that complements his finance role. As Faculty Director of the Master of Financial Engineering program, Dr. Reiner oversees curriculum development that likely integrates both traditional finance knowledge and cutting-edge computational verification methods. This distinctive combination prepares students to develop and validate complex financial algorithms with mathematical rigor, addressing growing industry needs for verified financial technologies.

Official University Profile

Magnus O. MyreenView profile

Professor

National and Kapodistrian University of AthensGreece

Magnus O. Myreen is a Professor in the Department of Computer Science and Engineering at Chalmers University of Technology, Sweden. He has been with Chalmers since 2014, becoming a tenured Associate Professor in 2015 and being promoted to full Professor in June 2023. Myreen has an extensive record of service to the programming languages and formal methods communities, including serving on program committees for major conferences like PLDI, POPL, ICFP, and CPP, and chairing the steering committee for the ITP conference series since November 2023. Myreen received his academic training at prestigious institutions: B.A. in Computer Science at the University of Oxford, tutored by Dr. Jeff Sanders Ph.D. on program verification in 2009 at the University of Cambridge, supervised by Prof. Mike Gordon Myreen's research focuses on program verification, interactive theorem proving, and compiler verification. He is best known for his work on the CakeML project, which is an ML-style language with a formal semantics and a growing ecosystem of proofs and tools that support construction of verified applications. As he states on his website, "My most recent work has focused on CakeML, which is an ML-style language with a formal semantics and a growing ecosystem of proofs and tools that support construction of verified applications. As far as I know, the CakeML compiler is the first verified compiler to have been bootstrapped." His research spans several key areas: Decompilation into logic — verification of machine code Proof-producing synthesis from logic Verified Lisp and ML runtimes Connecting things up: verified stacks Myreen's publication record shows a strong focus on verified compilation and theorem proving, particularly through the CakeML ecosystem. His work consistently bridges the gap between theoretical foundations and practical implementation, with numerous papers on verified compilers, program verification, and theorem proving. A significant trend in his recent work (2021-2024) has been extending CakeML's capabilities to handle more complex language features, improve performance, and verify increasingly sophisticated compilation techniques including bootstrapping and dynamic computation. Myreen has received several prestigious awards and recognitions: Winner of the BCS Distinguished Dissertation Competition 2010 for his PhD work Royal Society Research Fellow (UK) since 2012 ACM SIGPLAN Most Influential POPL Paper Award for the 2014 CakeML paper Amazon Research Award for his proposal "Compiling Dafny to CakeML" Myreen has advised several PhD students to completion, including Alejandro Gomez (Sep 2017 – Jun 2023), Oskar Abrahamsson (Aug 2017 – Dec 2022), and Andreas Loow (Sept 2016 – Sep 2021). He also collaborated with postdocs including Hira Syeda, Thomas Sewell, and Johannes Aman Pohjola. His research has been supported by various funding sources, though specific grants aren't detailed in the provided text. Notably, he received an Amazon Research Award for his work on compiling Dafny to CakeML, and his CakeML project has clearly attracted significant attention in the programming languages and formal methods communities. Myreen leads research on the CakeML project, which has grown into a substantial ecosystem for verified compilation. The project involves a team of researchers working on various aspects including compiler verification, program synthesis, and theorem proving. Myreen also collaborates with researchers at other institutions, as evidenced by his visits to EPFL (meeting Viktor Kuncak, Martin Odersky, and James Larus) and NUS (visiting Ilya Sergey's group). In October 2023, he began a ten-month sabbatical at Cambridge UK, where he worked part-time for Arm Ltd., indicating ongoing industrial collaboration.

Official University Profile

Mariusz WęgrzynView profile

Lecturer

Cracow University of TechnologyPoland

Mariusz Węgrzyn is a Lecturer in the Department of Automation and Computer Science at the Faculty of Electrical and Computer Engineering, Cracow University of Technology. His research focuses on algorithm design, embedded systems, and FPGA applications, with recent publications on square root computation, IoT-based fire detection, and test vector optimization for soft processors. University: Cracow University of Technology School: Faculty of Electrical and Computer Engineering Department: Department of Automation and Computer Science Academic Rank: Lecturer Research Trends: Mariusz Węgrzyn’s work spans hardware acceleration, numerical algorithms, and IoT systems. His 2025 publications emphasize FPGA efficiency and floating-point approximation, while 2021 studies explore energy optimization in safety systems and test vector reduction. Contact: Email: mariusz.wegrzyn@pk.edu.pl

Official University Profile

Panagiotis ManoliosView profile

Professor

Northeastern UniversityUnited States

Panagiotis (Pete) Manolios is a Professor in the Department of Computer Science within Northeastern University's College of Engineering in Boston. He leads the Northeastern University Formal Methods (NUFM) research group and maintains an active research program with multiple current PhD students. His primary affiliation is with the College of Computer Science (CCS) at Northeastern University, where he holds a tenured faculty position. Manolios' research focuses on formal methods with particular emphasis on program verification, theorem proving, and safety analysis of systems. His work spans several key areas including floating-point program analysis, resource-aware program verification, protocol verification, and safety-critical systems. He has developed significant tools and methodologies such as ACL2s (a powerful theorem prover) and pioneered approaches for analyzing numeric stability in compiler optimizations. His recent publications demonstrate substantial activity in formal verification, with particular focus on numeric stability analysis, invariant discovery through gamification, and model-based safety analysis of complex system architectures. These works reflect a consistent research trajectory toward making formal verification more practical and applicable to real-world systems, especially those with safety-critical requirements. Manolios has received recognition through multiple NSF grants including the SaTC: CORE: Medium collaborative project on bridging the gap between protocol design and implementation. His work on confidentiality and integrity of deep neural networks represents cutting-edge research at the intersection of formal methods and AI security. He has successfully mentored numerous PhD students who have gone on to positions at major technology companies including Google, Facebook, Intel, and MathWorks. His students' dissertations cover diverse topics within formal methods, from rank-polymorphic programming languages to resource-aware program analysis. Manolios directs several significant research projects including ACL2s (a powerful theorem prover), CID: Confidentiality and Integrity of Deep Neural Networks, Compilation-Dependent Security Properties of Software, and Platform Dependencies of Floating-Point Programs. These projects address fundamental challenges in making formal verification more practical and applicable to real-world systems.

Official University Profile