“If I have seen further it is by standing on the shoulders of giants.”— Letter to Robert Hooke (5 Feb 1675–6). In H. W. Turnbull (ed.), The Correspondence of Isaac Newton, 1661–1675 (1959), Vol. 1, p. 416.
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About
Short academic bio and background
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Suayb S. Arslan earned his M.Sc. and Ph.D. degrees in Electrical and Computer Engineering from University of California, San Diego, CA, USA, in 2009 and 2012, respectively. He completed his B.S. degree in Electrical and Electronics Engineering from Boğaziçi University in 2006. Dr. Arslan has a diverse industry background with experience in computer vision at Mitsubishi Electric Research Labs (Boston, MA) and data storage technologies at Quantum Corporation (Irvine, CA).
He has held invited professor and visiting researcher positions at the University of Nantes (France), Lawrence Berkeley National Laboratory at UC Berkeley (planned under a Fulbright grant but not undertaken due to extenuating circumstances), and the Department of Brain and Cognitive Sciences at MIT, where he continues to serve as a research affiliate (Take a look at the amazing work being undertaken at the Sinha Lab). He currently serves as a Professor in the Department of Computer Engineering and as the Director of the Institute for Data Science and Artificial Intelligence. He has actively participated in EU-supported projects such as CHIST-ERA under the Horizon 2020 framework.
Over the past two years, his research has focused on neural signals, brain–computer interfaces, vision models, and the interconnection between the brain and computational models. In the preceding five years, his work emphasized cloud storage applications, physical-layer communication theory, information and reliability theory, estimation theory, error detection and correction coding, source coding and data compression, modern scale-out storage technologies (including SAN and NAS), and networked and distributed systems. He has been particularly interested in the ultimate limitations of storage systems, the interplay between machine learning and information/coding theory, and the use of both hardware and software redundancy to mitigate diverse error mechanisms. He earned his Ph.D. from University of California, San Diego under the supervision of Prof. Laurence Milstein and Prof. Pamela Cosman.
Dr. Arslan has authored over 90 journal and conference publications and has been involved in more than 40 granted and application-stage patents. He has contributed to international standardization efforts, particularly the LTO Tape format in collaboration with IBM Research and the Storage Networking Industry Association (SNIA). He is the Executive Editor of Elsevier’s Internet of Things Journal and a member of the MDPI Biosignal Processing Topical Advisory Panel. He has served as a track chair at IEEE flagship conferences such as ICC and GLOBECOM and is a Senior Member of IEEE. His research interests span information theory, neuroscience, distributed systems, digital communication and storage systems, Internet of Things, cloud computing, reliability and system theory, and image/video processing.
Here is my CV.
Research & Projects
Selected national and international research projects
Research overview: My recent research lies broadly at the intersection of computational neuroscience, computer science, artificial intelligence with a special focus on the design, analysis, and optimization of learning and data communication/storage algorithms.
Current and recent research directions include the following projects including the project themes such as foundation models, bio-plausible learning and architectures; brain–computer interfaces; wireless and device-to-device communications; various data coding schemes for cloud storage; energy-efficient (“green”) storage architectures with an emphasis on tape-based and DNA-based systems; coded computation; reliability modeling of large-scale systems; clustering and learning in blockchain-based decentralized networks.
Below is a curated selection of national (TÜBİTAK, BAP) and international projects (ongoing, completed, or on hold) that reflect my current research directions at the intersection of artificial intelligence, neuroscience, distributed systems, and data-centric computing.
- YOKADP‑25 — Extensible dataset labeling and contrastive alignment for cross‑modal inference and multimodal LLM‑based data generation (PI, ongoing).
- T1001‑25 — Bio‑inspired deep neural networks and hybrid system design under degraded imaging conditions (PI, ongoing).
- BAP‑25 — Brain spatial‑frequency processing and frequency‑decoupled computational modeling (PI, ongoing).
- T2219‑22 — Evolution of brain–computer interfaces: temporal stimuli and guessing‑function–based brain channels (PI, completed; joint with MIT).
- IARPA‑22 (BRIAR) — Biometric recognition at altitude and range (Researcher, completed; joint with MIT, GE, and IARPA).
- FULBRIGHT‑22 — Multi‑nanopore sequencing and coding for practical DNA data storage (PI, on hold; joint with LBNL–UC Berkeley).
- T3501‑20 — Robust concurrent algorithms for distributed mixed‑integer optimization (Researcher, ongoing).
- T1001‑19 — DISCO‑Proc: Distributed storage, coding, and protocol design for cooperative cellular networks (PI, completed).
- T2523‑18 — C2B‑DecStor: Clustered and coded blockchain systems for decentralized storage (PI, completed; joint with KAIST).
- T2232‑17 — Cloud‑specialized systematic fountain codes for big‑data streams (PI, completed; resulted in Founsure 1.0).
- T2545‑16 — MOJCODE: Mojette‑transform‑based correction coding for data‑science applications (PI, completed; joint with University of Nantes).
I am actively seeking enthusiastic Master’s and Ph.D. students interested in AI, human‑inspired learning, multimodal systems, distributed intelligence, and neuro‑AI. Please reach out via email with a brief statement of interest and CV.
- Developing Vision Like a Human: A Biomimetic Approach to Training AI Models
- Theoretical Accounts for the Optimality of Biomimetic Training
- Signal Processing and Deep Learning for Brain Computer Interfaces
- Multi-Nanopore Sequencing for DNA Data Storage
- Iterative Product Decoding for DNA Data Storage
- Network Coding for Distributed Computing and Caching
Publications
Selected journal and conference papers · Full list on Google Scholar
Journal Articles
- Artificial Human Intelligence: The Role of Humans in the Development of Next Generation AI. S. S. Arslan. IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 10, no. 1, pp. 4–20, Feb. 2026. Journal
- Guessing Cost: Bounds and Applications to Data Repair in Distributed Storage. Suayb S. Arslan; Elif Haytaoglu. IEEE Transactions on Information Theory, 2024. DBLP · DOI
- A Trustworthy Framework for Multi-Cloud Service Management: Self-Sovereign Identity Integration. Engin Zeydan; Jorge Baranda; Josep Mangues-Bafalluy; Suayb S. Arslan; Yekta Turk. IEEE Transactions on Network Science and Engineering, 2024. DBLP
- Post-Quantum Blockchain-Based Decentralized Identity Management for Resource Sharing in Open Radio Access Networks. Engin Zeydan; Luis Blanco; Josep Mangues-Bafalluy; Suayb S. Arslan; Yekta Turk. IEEE Transactions on Green Communications and Networking, 2024. DBLP
- Advancements in distributed ledger technology for Internet of Things. Suayb S. Arslan; Raja Jurdak; Jens Jelitto; Bhaskar Krishnamachari. Internet of Things, 2020. DBLP
- A Reliability Model for Dependent and Distributed MDS Disk Array Units. Suayb S. Arslan. IEEE Transactions on Reliability, 2019. DBLP
Conference Papers
- Semantic Chunking and Chain-Of-Thought Reasoning for RAG-Based Document Processing. Y. Ateş, A. Sayar, İ. U. Bozlar, S. Ertuğrul, and S. S. Arslan. 2025 IEEE 35th International Workshop on Machine Learning for Signal Processing (MLSP), Istanbul, Türkiye, 2025. PDF · DOI
- Improved Bounds on the Moments of Guessing Cost. Suayb S. Arslan; Elif Haytaoglu. IEEE International Symposium on Information Theory (ISIT), 2022. DBLP
- Base Station-Assisted Cooperative Network Coding for Cellular Systems with Link Constraints. Suayb S. Arslan; Massoud Pourmandi; Elif Haytaoglu. IEEE International Symposium on Information Theory (ISIT), 2022. DBLP
- Asymptotically MDS Array BP-XOR Codes. Suayb S. Arslan. IEEE International Symposium on Information Theory (ISIT), 2018. DBLP
- Next-Generation data storage: Transistor and DNA. Reza A. Ashrafi; Ali Emre Pusane; Suayb S. Arslan. Signal Processing and Communications Applications Conference (SIU), 2018. DBLP
- Minimum distortion variance concatenated block codes for embedded source transmission. Suayb S. Arslan. International Conference on Computing, Networking and Communications (ICNC), 2014. DBLP
The list is not exhaustive. For the up-to-date full publication record and citation metrics, please visit Google Scholar.
Teaching
Undergraduate and graduate courses (click to expand)
CMPE362: Introduction to Signal Processing for Computer Engineering
Fundamentals of discrete-time and continuous-time signal processing for computer engineers: convolution, Fourier analysis, sampling, filtering, and practical frequency-domain reasoning.
CMPE140: Introduction to Computing
Core computing concepts with hands-on programming foundations, algorithmic thinking, and problem-solving skills for engineering students.
CMPE581: Human-Inspired Machine Intelligence
Advanced topics at the intersection of learning theory, neuroscience, and modern AI, including human-inspired curricula, robustness, and representation learning.
EE203: Digital Systems Design
Introduction to digital system design including combinational and sequential logic, finite state machines, timing analysis, and hardware description using Verilog/VHDL.
COMP206: Computer Architecture
Fundamental principles of computer organization and architecture including instruction sets, pipelining, memory hierarchy, caching, and performance evaluation.
MATH224: Probability and Statistics
Probability theory and statistical methods for engineers, including random variables, distributions, expectation, hypothesis testing, confidence intervals, and regression.
COMP472: Parallel and Distributed Systems
Concepts and design of parallel and distributed systems including concurrency models, synchronization, distributed algorithms, scalability, and fault tolerance.
Professional Activities
Academic, editorial, and professional service
- Executive Editor, Elsevier Internet of Things Journal (2025–today)
- Visiting Associate Professor, MIT (2022–2024)
- Academic Member, SNIA DNA Storage (2024–today)
- Vice-Chair, IEEE Communications Society Turkey Chapter (2021–2023)
- Treasurer, IEEE Data Storage Technical Committee (2021–2023)
- Associate Editor, Elsevier Internet of Things Journal (2018–2025)
- Committee Member, IEEE Communications Society Student Competition (2018–today)
- Committee Member, IEEE Data Storage Technical Committee (DSTC) (2018)
- Active Member, INSIC Consortium – Tape Technical Team (2013–today)
- Visiting Scholar, University of Nantes, France (2015, 2016)
- Visiting Researcher, Quantum Corporation, USA (Summer 2018)
- Referee & Panelist, TÜBİTAK TEYDEB and 1001, 1003 Panels
- Referee & Panelist, TÜBİTAK, TGV, and TÜSİAD Annual Technology Awards
- Industry Consultancy: Quantum (2015–2024), Huawei (2016), TAM Finans (2025)
- Technical Program Committee (TPC), IEEE GLOBECOM, IEEE ICC and IEEE ISITA (2020)
- TPC Member, IEEE PIMRC’18, ICWT TELKOMNIKA’18, CYBERNETICSCOM’16, ICRAMET’18, DISP’19, INAIT’18–’19, SES’19, ISIEA’12–’13, and many more
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