Prof. Dr. Sinem Solak

Dr. Sinem Solak is an academic and researcher with a strong foundation in Electronics and Communication Engineering, specializing in signal processing, machine learning, and intelligent systems. Her doctoral research at the University of Sussex focused on nanoscale sensor networks and statistical signal processing for abnormality detection, resulting in multiple peer-reviewed publications. With experience across higher education institutions in the UK, Dr. Solak has designed and delivered innovative, student-centred curricula in computing and engineering. In addition to her academic work, she has held leadership and consultancy roles in deep tech startups, contributing to the development of AI-powered healthcare technologies and securing over £800,000 in competitive research and innovation funding. She brings a transdisciplinary and applied perspective to her teaching, blending academic rigor with practical impact.

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Previously worked for:

Regent College London, Hirehoot, Stealth Mode Biotechnology Company, Study Group, University of Sussex, Conception X, Bogazici University, AIR Telekmünikasyon Çözümleri, Yıldız Teknik Üniversitesi and Turkcell

Skills you can learn

Foundation Computing

Foundation Mathematics

Human Computer Interaction Web Technologies

Machine Fundamentals

Electronic Circuits and Components

Creative Engineering

Programming Lab

Electrical Circuits and Devices

Core Physics

Physics Lab

Electromagnetism and Introduction to Electrical Machines

Research Profile

Key research areas and highlights.

Dr. Sinem Solak’s research focuses on the intersection of signal processing, machine learning, and intelligent systems, with applications in healthcare technologies and nanoscale communication networks. Her doctoral work contributed to early abnormality detection algorithms using statistical models and neural networks within nano-sensor environments. More recently, her research has extended to the development of AI-powered diagnostic and drug delivery systems.

Papers

S. Solak and M. Öner, "Sequential Decision Fusion for Abnormality Detection via Diffusive Molecular Communications," in IEEE Communications Letters, vol. 25, no. 3, pp. 825-829, March 2021, doi: 10.1109/LCOMM.2020.3040146.
keywords: {Sensors;Delays;Nanoscale devices;Task analysis;Sensor fusion;Receivers;Sensor phenomena and characterization;Molecular communications;distributed detection;nanoscale sensor networks},

S. N. Solak and M. Oner, "Neural Network Based Decision Fusion for Abnormality Detection via Molecular Communications," 2020 IEEE Workshop on Signal Processing Systems (SiPS), Coimbra, Portugal, 2020, pp. 1-5, doi: 10.1109/SiPS50750.2020.9195212. keywords: {Channel models;Task analysis;Sensor phenomena and characterization;Training;Artificial neural networks;Nanoscale devices;deep learning;molecular communication;distributed detection;sensor networks},

RNN based abnormality detection with nanoscale sensor networks using molecular communications

Split-ring resonator-based sensors on flexible substrates for glaucoma monitoring

SAR imaging techniques for ground penetrating impulse radar

Professional Community Services

Membership

Reviewing

Program committee memberships and chairing

Judging & mentoring in competitions

Other

Prizes

Talks

Consulting / Entrepreneurship projects

Program Director BSc AI & Sustainable Technologies, Professor of AI & Technology

Prof. Dr. Sinem Solak

Sinem combines academic research and startup experience to explore ethical, real-world applications of AI—particularly in healthtech and inclusive innovation. At Tomorrow University, she inspires learners to build purposeful, impact-driven technologies.

Biography

Dr. Sinem Solak is Professor of Technology & AI at Tomorrow University of Applied Sciences. With a PhD in Electronics and Communication Engineering, she brings a unique blend of academic research, startup leadership, and applied AI experience across healthcare, hiring, and social impact sectors. Sinem is passionate about empowering learners to develop ethical, inclusive, and purpose-driven technologies. Her work at Tomorrow University focuses on inspiring critical thinking and real-world innovation through technology.
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Previously Worked At
Regent College London, Hirehoot, Stealth Mode Biotechnology Company, Study Group, University of Sussex, Conception X, Bogazici University, AIR Telekmünikasyon Çözümleri, Yıldız Teknik Üniversitesi and Turkcell
Logo Impact MBA - Tomorrow University of Applied Sciences
Logo Impact MBA - Tomorrow University of Applied Sciences
Logo Impact MBA - Tomorrow University of Applied Sciences
Logo Impact MBA - Tomorrow University of Applied Sciences

Research Profile

Sinem’s research explores the intersection of intelligent systems, signal processing, and applied AI. Her doctoral work focused on nano-sensor networks, and she has since led interdisciplinary projects involving AI-powered drug delivery systems and inclusive technology solutions. She has contributed to deep-tech startups and secured competitive research funding to support ethical innovation in healthtech and education. Sinem’s research aims to make technology more impactful, human-centered, and accessible across diverse communities.

Papers

S. Solak and M. Öner, "Sequential Decision Fusion for Abnormality Detection via Diffusive Molecular Communications," in IEEE Communications Letters, vol. 25, no. 3, pp. 825-829, March 2021, doi: 10.1109/LCOMM.2020.3040146.
keywords: {Sensors;Delays;Nanoscale devices;Task analysis;Sensor fusion;Receivers;Sensor phenomena and characterization;Molecular communications;distributed detection;nanoscale sensor networks},

S. N. Solak and M. Oner, "Neural Network Based Decision Fusion for Abnormality Detection via Molecular Communications," 2020 IEEE Workshop on Signal Processing Systems (SiPS), Coimbra, Portugal, 2020, pp. 1-5, doi: 10.1109/SiPS50750.2020.9195212. keywords: {Channel models;Task analysis;Sensor phenomena and characterization;Training;Artificial neural networks;Nanoscale devices;deep learning;molecular communication;distributed detection;sensor networks},

RNN based abnormality detection with nanoscale sensor networks using molecular communications

Split-ring resonator-based sensors on flexible substrates for glaucoma monitoring

SAR imaging techniques for ground penetrating impulse radar

Professional Community Services

Membership

Reviewing

Program committee memberships and chairing

Judging & mentoring in competitions

Thesis Supervised

Cover of a thesis.

Title of the Thesis

First & Last Name
Impact Master of Science
Konrad joined Tomorrow University to pivot from corporate leadership into purpose-driven impact. Through the MBA, he deepened his expertise in tech and sustainability while gaining the confidence to embrace a new mission: amplifying change through strategy and storytelling. His journey includes launching the SDG Ambition Guide and producing films that inspire climate action.
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Teaching at Tomorrow University

Programs

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Skills You Can Learn

Foundation Computing

Foundation Mathematics

Human Computer Interaction Web Technologies

Machine Fundamentals

Electronic Circuits and Components

Creative Engineering

Programming Lab

Electrical Circuits and Devices

Core Physics

Physics Lab

Electromagnetism and Introduction to Electrical Machines

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