Soheila Hosseinzadeh | Cognitive Neuroscience | Best Researcher Award

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Assoc. Prof. Dr. Soheila Hosseinzadeh | Cognitive Neuroscience | Best Researcher Award

Assist. Prof. Dr. Soheila Hosseinzadeh, Tehran University of Medical Sciences, Iran.

Dr. Soheila Hosseinzadeh is a distinguished Assistant Professor of Neuroscience at the Tehran University of Medical Sciences, with a rich academic background that spans nursing, physiology, and neuroscience. Over the years, she has made substantial contributions to neuroscience education and research, particularly in the fields of cognitive neurophysiology and addiction studies. Her expertise includes a wide range of advanced techniques such as event-related potential analysis, EEG-based neurofeedback, behavioral studies, and molecular tools like RT-PCR and ELISA. She has played a pivotal role in training students and developing neuroscience programs at multiple academic institutions, demonstrating a balanced commitment to both teaching and scientific innovation.

Academic Profile

Google Scholar

Early Academic Pursuits

Dr. Soheila Hosseinzadeh’s academic foundation is deeply rooted in an interdisciplinary understanding of human physiology and neurological sciences. Her early career began with a Bachelor of Science in Nursing in 2000, which was soon followed by a Master’s degree in Physiology in 2003. Demonstrating a keen interest in the mechanisms underlying brain function and behavior, she further advanced her expertise by earning a Ph.D. in Neuroscience in 2013. These academic milestones laid a solid groundwork for her future in teaching and cutting-edge neurophysiological research.

Professional Endeavors in Neuroscience

After completing her Ph.D., Dr. Hosseinzadeh embarked on an academic and research-oriented career that has spanned over a decade. From 2014 to April 2022, she served as a neurophysiology course instructor at Babol University of Medical Sciences, nurturing future scientists with her in-depth understanding of brain physiology. Since April 2022, she has continued her academic contributions at the Tehran University of Medical Sciences, where she teaches courses in Neuroscience and Addiction Studies. Her dual role as educator and researcher places her at the forefront of neuroscience education in Iran.

Contributions and Research Focus

Dr. Hosseinzadeh’s research is focused on the interface of cognitive neuroscience and addiction studies. Her technical proficiency includes advanced neurophysiological techniques such as event-related potential (ERP) recording and analysis, quantitative EEG (QEEG)-based neurofeedback, and behavioral assessments in animal models. She is also experienced in molecular biology tools including real-time RT-PCR and ELISA, alongside rodent stereotaxic surgeries and flow cytometry. Her work often explores neural mechanisms underlying cognitive functions, brain plasticity, and responses to addictive substances—bridging lab findings with clinical relevance.

Accolades and Recognition

Throughout her academic journey, Dr. Hosseinzadeh has earned recognition for her expertise in neurophysiological and behavioral science. Her dual roles at prestigious institutions such as Tehran University of Medical Sciences reflect her trusted authority in the field. While her accolades are more rooted in impact and mentorship than in public awards, her consistent engagement in neuroscience education and translational research is a clear indicator of peer acknowledgment and professional respect.

Impact and Influence

Dr. Hosseinzadeh’s influence extends beyond academic teaching. By integrating theoretical neuroscience with hands-on technical applications like neurofeedback and EEG-based cognitive training, she fosters a research culture that promotes both clinical innovation and scientific discovery. Her guidance has shaped students and young researchers in multiple universities, many of whom continue to advance the fields of neurophysiology and cognitive rehabilitation across the country.

Legacy in Neurotechnology and Cognitive Health

Her pioneering efforts in cognitive task design and ERP analysis have significantly contributed to Iran’s growing reputation in brain research. As one of the few experts integrating neurofeedback with behavioral science and electrophysiology, Dr. Hosseinzadeh has helped establish a platform for neurotechnological interventions in addiction and mental health studies. Her legacy lies in creating an interdisciplinary approach that merges neuroscientific inquiry with practical healthcare applications.

Future Contributions and Vision

Looking ahead, Dr. Soheila Hosseinzadeh is poised to make even greater strides in neuroscience, particularly in the domains of addiction neurobiology, cognitive rehabilitation, and neurofeedback therapy. With continuous advancements in brain-monitoring tools and behavioral modeling, she aims to lead research projects that offer deeper insights into brain-behavior relationships and provide innovative treatments for neuropsychiatric disorders. Her vision includes developing collaborative research networks that connect Iranian neuroscience to global scientific conversations.

Publication

Piperine restores streptozotocin-induced cognitive impairments: Insights into oxidative balance in cerebrospinal fluid and hippocampus
M Khalili-Fomeshi, MG Azizi, MR Esmaeili, M Gol, S Kazemi, …
2018

Plasma microparticles in Alzheimer’s disease: The role of vascular dysfunction
S Hosseinzadeh, M Noroozian, E Mortaz, K Mousavizadeh
2018

Elevated CSF and plasma microparticles in a rat model of streptozotocin-induced cognitive impairment
S Hosseinzadeh, M Zahmatkesh, MR Zarrindast, GR Hassanzadeh, …
2013

Effect of methamphetamine exposure on the plasma levels of endothelial-derived microparticles
A Nazari, M Zahmatkesh, E Mortaz, S Hosseinzadeh
2018

Hippocampal DHCR24 down regulation in a rat model of streptozotocin-induced cognitive decline
S Hosseinzadeh, M Zahmatkesh, M Heidari, GR Hassanzadeh, …
2015

Increment of CSF fractalkine-positive microvesicles preceded the spatial memory impairment in amyloid beta neurotoxicity
L Karimi-Zandi, M Zahmatkesh, G Hassanzadeh, S Hosseinzadeh
2022

Arbutin intervention ameliorates memory impairment in a rat model of lysolecethin induced demyelination: Neuroprotective and anti-inflammatory effects
S Ashrafpour, MJ Nasr-Taherabadi, A Sabouri-Rad, S Hosseinzadeh, …
2024

Conclusion

Dr. Hosseinzadeh’s career reflects an exemplary blend of academic excellence, technical expertise, and visionary research in neuroscience. Her efforts have significantly advanced the understanding of brain function, particularly in the context of addiction and cognitive health. As a leader in her field, she continues to inspire the next generation of neuroscientists while actively contributing to translational research that bridges laboratory findings with clinical solutions. With her ongoing work and future vision, Dr. Hosseinzadeh stands out as a key figure in shaping the future of neuroscience in Iran and beyond.

VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

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Mr. VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

Mr. VIKRAM SINGH KARDAM, DTU DELHI, India.

Vikram Singh Kardam is a dedicated researcher and academician specializing in signal processing, currently pursuing his Ph.D. at Delhi Technological University (DTU). With a strong educational foundation, including an M.Tech in Signal Processing and Digital Design, and a B.Tech in Electronics and Communication Engineering, he has consistently demonstrated academic excellence. Vikram has diverse professional experience, having worked both in industry and academia, including roles as a Project Engineer and Assistant Professor. His innovative M.Tech thesis on real-time iris recognition highlights his ability to apply advanced concepts to practical challenges in biometric security. Proficient in multiple programming languages and known for his problem-solving attitude, he blends technical skill with teaching acumen, influencing students and peers alike. His GATE rank and contributions to student development further underscore his commitment to excellence in engineering and education.

Profile

Scopus

 

🎓 Early Academic Pursuits

Vikram Singh Kardam’s academic journey began with a solid foundation in science and technology. He completed his 10th and 12th education from Government Inter College, Agra, achieving commendable marks that laid the groundwork for his future in engineering. His higher education commenced at the University Institute of Engineering and Technology, CSJM University, Kanpur, where he earned his Bachelor of Technology in Electronics and Communication Engineering in 2007 with a respectable score of 73.2%. Driven by a passion for advanced studies, he pursued a Master of Technology in Signal Processing and Digital Design from Delhi Technological University (DTU), securing a CGPA of 8.06 in 2017. His academic path reflects not only consistent effort but also a dedication to the field of signal processing.

🧑‍🏫 Professional Endeavors

Vikram embarked on his professional career with diverse roles that bridged academia and industry. He served as a Project Engineer at ITI Limited, Delhi, and as a Lab Engineer at Dayalbagh Engineering College, Agra, gaining hands-on experience in real-world engineering environments. His passion for teaching led him to academia, where he worked as an Assistant Professor in reputed institutions such as Galgotias College of Engineering and Technology, Greater Noida, and HMR Institute of Technology and Management, Delhi. With around three years of cumulative teaching experience, he has imparted theoretical knowledge and practical insights in Electronics and Communication Engineering, contributing to the academic development of numerous students.

🔬 Contributions and Research Focus

Currently pursuing his Ph.D. in Signal Processing at Delhi Technological University, Vikram Singh Kardam’s research delves into the intricacies of digital signal processing with real-world applications. His M.Tech thesis, titled “Real Time Iris Recognition”, showcases his innovation in biometric security systems. By integrating iris recognition with eye-blinking detection using a basic webcam, he proposed a novel, low-cost, and more secure method for identity verification. The system’s robustness and its resistance to hacking highlight his ability to merge theoretical concepts with practical utility. His fluency in programming languages such as MATLAB, C, C++, and Python3 supports his technical versatility in algorithm development and simulation.

🏅 Accolades and Recognition

A noteworthy milestone in Vikram’s academic journey is securing an All India Rank of 5334 in the GATE 2021 examination in Electronics and Communication Engineering. This national-level achievement is a testament to his strong grasp of core concepts and problem-solving acumen. Additionally, his academic performances during B.Tech and M.Tech reflect sustained excellence. His thesis project, recognized for its practical application and innovative approach, further enhances his academic reputation.

📚 Impact and Influence

In his role as an Assistant Professor, Vikram Singh Kardam has significantly influenced his students’ academic and professional growth. His commitment to regularly conducting lectures, his focus on ensuring student understanding, and his hands-on approach to lab sessions highlight his dedication to holistic teaching. Beyond knowledge delivery, his empathetic and analytical mindset enables him to mentor students, offer academic guidance, and solve problems effectively. His ability to integrate teaching with research creates an inspiring learning environment.

🌐 Legacy and Future Contributions

Looking forward, Vikram aspires to contribute to both academia and industry through innovative research in signal processing, embedded systems, and biometric technology. His current Ph.D. pursuits are expected to yield impactful contributions to the scientific community, particularly in the areas of real-time data analysis and secure identification systems. With a forward-thinking vision, he aims to blend educational excellence with technological advancement, fostering a new generation of engineers equipped with both critical thinking and creative problem-solving skills.

🧠 Vision and Intellect

At the core of Vikram Singh Kardam’s career is a mindset defined by curiosity, dedication, and the pursuit of knowledge. A quick learner and an effective communicator, he embodies the spirit of modern engineering – adaptive, analytical, and collaborative. His ability to learn and implement complex systems, along with his respect for students and colleagues, reflects not just technical competence but also emotional intelligence. As a lifelong learner and educator, he is poised to make enduring contributions in signal processing and beyond.

Publication

  • Title: BSPKTM-SIFE-WST: Bispectrum based channel selection using set-based-integer-coded fuzzy granular evolutionary algorithm and wavelet scattering transform for motor imagery EEG classification

  • Authors: V.S. Kardam, S. Taran, A. Pandey

  • Year: 2025

 

 

✅ Conclusion

Vikram Singh Kardam stands out as a promising scholar and educator in the field of signal processing. His journey reflects a balance of theoretical rigor, practical implementation, and a passion for continuous learning. With a future-oriented mindset, he is poised to make meaningful contributions to biometric systems, digital design, and the broader engineering community. As he advances through his doctoral research and professional engagements, Vikram’s legacy is one of innovation, dedication, and impactful mentorship in the evolving landscape of technology and education.

Koagne Longpa Tamo Silas | Neuroinformatics | Pioneer Researcher Award

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Mr. Koagne Longpa Tamo Silas | Neuroinformatics | Pioneer Researcher Award

Mr.  Koagne Longpa Tamo Silas, University of Dschang, Cameroon.

Koagne Longpa Tamo Silas is a dedicated researcher in the field of medical physics, specializing in automation, artificial intelligence, and electronic system design. His academic journey from Bamenda State University to Dschang State University reflects his continuous pursuit of knowledge and innovation. His contributions to circuit simulation, embedded systems, and artificial neural networks have established him as a promising figure in medical physics.

Profile

Google Scholar

🎓 Early Academic Pursuits

Born on July 12, 1998, in Mbouda, Cameroon, Koagne Longpa Tamo Silas displayed a keen interest in science and technology from a young age. His passion for physics and engineering led him to pursue higher education at Bamenda State University, where he embarked on an academic journey in Electrical and Power Engineering. His undergraduate studies, from November 2015 to August 2018, laid the foundation for his expertise in electrical systems, automation, and circuit design. Eager to expand his knowledge, he continued his postgraduate studies in the same field at Bamenda State University from September 2018 to July 2020, honing his skills in power engineering and applied electronics.

🚀 Professional Endeavors

Determined to deepen his expertise, Koagne Longpa Tamo Silas transitioned into the field of physics, enrolling as a Ph.D. student at Dschang State University in December 2022. His academic pursuits in the Department of Physics align with his interests in medical physics, where he integrates automation, applied computer science, and electronics to innovate in the field. As a dedicated researcher, he continues to engage with the Faculty of Science at Dschang State University, contributing to the academic and scientific community with his research in medical physics and embedded systems.

🤖 Contributions and Research Focus

Koagne Longpa Tamo Silas has dedicated his research efforts to the intersection of medical physics, automation, and artificial intelligence. His work encompasses Analog Artificial Neural Networks, Embedded Systems, Circuit Simulation, Digital and Analog Electronics, and Microcontroller Programming. His proficiency in tools like Spice Simulation, Cadence Virtuoso, and Electronic Design Automation allows him to design and optimize medical devices and automated systems. His research aims to enhance diagnostic and therapeutic tools in medical physics by leveraging artificial intelligence and embedded systems.

🏆 Accolades and Recognition

Throughout his academic and research career, Koagne Longpa Tamo Silas has garnered recognition for his contributions to medical physics and electronics. His innovative approach to circuit simulation and signal processing has positioned him as a promising researcher in his field. His dedication to advancing medical technologies has earned him the respect of his peers and mentors, as he continues to contribute valuable insights to the scientific community.

🌐 Impact and Influence

Through his academic journey and research, Koagne Longpa Tamo Silas has influenced the way automation and artificial intelligence are integrated into medical physics. His work in digital electronics and microcontroller programming is paving the way for innovative solutions in the medical field. His contributions extend beyond research, as he actively engages with students and researchers, fostering a culture of knowledge-sharing and scientific exploration.

 

Publication

  • A High-Resolution Non-Volatile Floating Gate Transistor Memory Cell for On-Chip Learning in Analog Artificial Neural Networks
    Authors: KLT Silas, DTA Bernard, FT Bernard, L Jean-Pierre, GW Ejuh
    Year: 2025

 

  • Breast Cancer Diagnosis with Machine Learning Using Feed-Forward Multilayer Perceptron Analog Artificial Neural Network
    Authors: B Djimeli-Tsajio Alain, KLT Silas, LT Jean-Pierre, N Thierry, GW Ejuh
    Year: 2024

 

  • Design and Implementation of a Digital Breath Alcohol Detection System with SMS Alert and Vehicle Tracking on Google Map
    Author: KLT Silas
    Year: 2020

 

  • Design and Realization of an Electronic Attendance System Based on RFID with an Automatic Door Unit
    Author: MK Jules
    Year: 2018

 

🎯 Conclusion

With a vision to transform medical physics through automation and AI-driven technologies, Koagne Longpa Tamo Silas is on a path to making significant contributions to healthcare innovation. His passion, dedication, and expertise ensure that his research will continue to shape the future of medical technology, leaving a lasting impact on both academia and practical applications in the field.

 

Xiaobing Yan | Neurotechnology | Best Researcher Award

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Prof. Xiaobing Yan | Neurotechnology | Best Researcher Award

Prof. Xiaobing Yan, Hebei University, China.

Professor Xiaobing Yan is a distinguished researcher specializing in novel memory devices and memristor-based brain-inspired chip technologies. As a Senior Member of IEEE and a reviewer for leading journals, he has made significant contributions to the field of neuromorphic engineering. His outstanding achievements include recognition as a Young Changjiang Scholar and a Young Top-notch Talent under China’s National Ten Thousand Talents Program. With over 120 high-impact publications, 5,600+ citations, and an H-index of 40, he is globally recognized among the top 2% of scientists. His research has been supported by several prestigious national and provincial funding programs.

Profile

Scopus

🎓 Early Academic Pursuits

Xiaobing Yan embarked on his academic journey with a deep passion for electronics and information engineering. His early years were marked by an unwavering dedication to understanding the complexities of memory devices and neuromorphic systems. As he progressed through his studies, his curiosity and drive led him to explore the intersection of artificial intelligence and hardware development. His rigorous academic training laid a solid foundation for his future contributions to next-generation computing technologies.

💪 Professional Endeavors

Currently serving as a Professor at the Institute of Life Science and Green Development, Hebei University, Xiaobing Yan has established himself as a distinguished leader in the field of electronic engineering. He is a Doctoral Supervisor and a Senior Member of IEEE, a testament to his vast expertise and influence in the scientific community. His role extends beyond academia, as he actively engages in national-level research programs and collaborates with top-tier research institutions. His professional journey is a testament to his commitment to pioneering advancements in neuromorphic computing and memristor-based brain-inspired chip technologies.

🤖 Contributions and Research Focus

Xiaobing Yan’s research primarily revolves around novel memory devices and brain-like computing systems. His work has been instrumental in the advancement of memristor-based chip technologies, which hold the potential to revolutionize artificial intelligence hardware. By bridging the gap between neuroscience and semiconductor innovation, he is contributing to the development of energy-efficient, high-performance computing architectures. His research projects, funded by prestigious national programs, aim to push the boundaries of nanoelectronics and intelligent systems.

🏆 Accolades and Recognition

Xiaobing Yan’s groundbreaking work has earned him widespread recognition. In 2019, he was honored as a Young Changjiang Scholar by the Ministry of Education and selected as a Young Top-notch Talent under the National Ten Thousand Talents Program. In 2024, he further cemented his legacy by winning the Excellence Award at the National Disruptive Innovation Technology Competition. His contributions are not only recognized in China but also on a global scale, as he has been listed among the top 2% of scientists worldwide by Stanford University.

🌟 Impact and Influence

With over 120 high-impact publications and more than 5,600 citations, Xiaobing Yan’s research has significantly shaped the field of electronics and artificial intelligence. His H-index of 40 reflects the depth and relevance of his contributions. As a reviewer for prestigious journals such as Nature Electronics, Advanced Materials, and ACS Nano, he plays a crucial role in shaping the direction of cutting-edge research. His influence extends beyond his publications, as he mentors young researchers and fosters collaborations that drive innovation in neuromorphic computing.

🚀 Legacy and Future Contributions

As a leader in disruptive technology and nanoelectronics, Xiaobing Yan is poised to continue pushing the boundaries of scientific discovery. His ongoing research projects, including multiple National Key R&D initiatives and collaborations with leading institutions, demonstrate his commitment to pioneering breakthroughs in brain-inspired computing. With his vision and expertise, he is set to leave a lasting legacy in the development of next-generation intelligent systems, shaping the future of artificial intelligence and semiconductor technology.

Publication

  1. In situ training of an in-sensor artificial neural network based on ferroelectric photosensors

    • Authors: H. Lin, Haipeng; J. Ou, Jiali; Z. Fan, Zhen; X. Gao, Xingsen; J. Liu, Junming
    • Year: 2025

 

  1. Ultra robust negative differential resistance memristor for hardware neuron circuit implementation

    • Authors: Y. Pei, Yifei; B. Yang, Biao; X. Zhang, Xumeng; S. Li, Shushen; X. Yan, Xiaobing
    • Year: 2025

 

  1. Physical unclonable in-memory computing for simultaneous protecting private data and deep learning models

    • Authors: W. Yue, Wenshuo; K. Wu, Kai; Z. Li, Zhiyuan; R. Huang, Ru; Y. Yang, Yuchao
    • Year: 2025

 

  1. Memristor-based feature learning for pattern classification

    • Authors: T. Shi, Tuo; L. Gao, Lili; Y. Tian, Yang; X. Yan, Xiaobing; Q. Liu, Qi
    • Year: 2025

 

  1. Harnessing spatiotemporal transformation in magnetic domains for nonvolatile physical reservoir computing

    • Authors: J. Zhou, Jing; J. Xu, Jikang; L. Huang, Lisen; X. Yan, Xiaobing; S.T. Lim, Sze Ter
    • Year: 2025

 

  1. Flexoelectric Effect in Thin Films: Theory and Applications

    • Authors: X. Jia, Xiaotong; R. Guo, Rui; J. Chen, Jingsheng; X. Yan, Xiaobing
    • Year: 2025

 

  1. Deoxyribonucleic acid brick crystals-based memristor as an artificial synapse for neuromorphic computing

    • Authors: Z. Wang, Zhongrong; X. Liu, Xinran; J. Li, Jiahang; J. Lou, Jianzhong; X. Yan, Xiaobing
    • Year: 2025

 

  1. Weighted Echo State Graph Neural Networks Based on Robust and Epitaxial Film Memristors

    • Authors: Z. Guo, Zhenqiang; G. Duan, Guojun; Y. Zhang, Yinxing; Y. Faraj, Yousef; X. Yan, Xiaobing
    • Year: 2025

 

  1. Achieving over 10 % efficiency in kesterite solar cells via selenium-free annealing

    • Authors: Q. Zhou, Qing; Y. Cong, Yijia; H. Li, Hao; Y. Sun, Yali; W. Yu, Wei
    • Year: 2024

 

  1. Hardware implementation of memristor-based artificial neural networks

  • Authors: F.L. Aguirre, Fernando L.; A. Sebastian, Abu; M. Le Gallo, Manuel; S. Matias Pazos, Sebastian; M. Lanza, Mario
  • Year: 2024

 

Conclusion

Professor Yan’s work plays a pivotal role in advancing memory technology and brain-inspired computing. His extensive research contributions and leadership in high-impact projects underscore his expertise in developing next-generation computing technologies. His global recognition and numerous accolades highlight his influence in the field, positioning him as a key figure in neuromorphic engineering and memory device innovation.

 

 

Saba Hesaraki | Neurotechnology | Best Researcher Award

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Ms. Saba Hesaraki | Neurotechnology | Best Researcher Award

Ms. Saba Hesaraki,  Islamic Azad University science and research branch, Iran.

Saba Hesaraki is a computer engineer specializing in artificial intelligence (AI), particularly in medical imaging and generative AI. She holds a Master’s degree in Computer Engineering from Islamic Azad University, Science and Research Branch, Tehran, where her thesis focused on breast cancer image segmentation using an improved 3D U-Net++ model. She has a strong academic background with high GPAs in both her bachelor’s and master’s programs.

Profile

Google Scholar

🌱 Early Academic Pursuits

Saba Hesaraki embarked on her academic journey with a deep passion for computer engineering, earning her Bachelor of Science in Software Engineering from Islamic Azad University, West Tehran Branch. With an outstanding GPA of 17.22 out of 20.0, she demonstrated an early inclination toward problem-solving and artificial intelligence. Her intellectual curiosity and commitment to innovation led her to pursue a Master’s degree in the same domain at Islamic Azad University, Science and Research Branch, Tehran. Her thesis, titled “Segmentation of Breast Cancer Images Using Improved 3D U-Net++ Model,” under the supervision of Dr. Maryam Rastgarpour, showcases her dedication to advancing medical imaging technologies through AI-driven solutions. With an exceptional GPA of 18.12 out of 20.0, her academic excellence laid the foundation for a remarkable research career.

💼 Professional Endeavors

Saba’s professional journey reflects her deep expertise in artificial intelligence, particularly in the realms of generative AI and medical imaging. She has worked remotely in various esteemed organizations, contributing her skills to groundbreaking AI projects. Her role as a Generative AI Engineer at Care Vox in Mountain View, California, and Nexus in San Jose, California, enabled her to develop innovative AI-driven solutions. Prior to this, she made significant contributions as a Computer Vision Engineer at Koga Studio and the Quantitative MR Imaging and Spectroscopy Group in Tehran. Her engagement as an NLP Researcher at Asr Gooyesh Pardaz further showcases her versatility in the field of AI. Through these roles, she has gained profound experience in AI-based medical diagnostics, image segmentation, and sustainable AI development, paving the way for impactful innovations.

📚 Contributions and Research Focus

As a dedicated researcher, Saba’s work has revolved around the intersection of AI and healthcare, particularly medical image segmentation and generative AI applications. Her research interests extend to AI-driven personalized medicine and sustainable AI solutions. She has co-authored multiple research papers, including “Capsule Fusion for Extracting Psychiatric Stressors for Suicide from Twitter” and “UNet++ and LSTM Combined Approach for Breast Ultrasound Image Segmentation.” Her work reflects a keen interest in leveraging AI to solve complex medical challenges, from cancer detection to mental health analysis. Her research on classifying 3D point cloud objects using hybrid neural networks also highlights her multidisciplinary expertise.

🏆 Accolades and Recognition

Saba’s dedication to AI research has been recognized through her academic achievements and professional contributions. Her IELTS score of 7.5 and GRE score of 332 underscore her strong analytical and communication skills, essential for global collaboration in AI research. Her research papers have been under review and submission in reputable scientific journals, further solidifying her presence in the AI and medical imaging research community. The recognition she has garnered through collaborations and innovative contributions establishes her as an influential figure in AI-driven healthcare solutions.

🌍 Impact and Influence

Saba’s work extends beyond research, as she actively contributes to the global AI community by developing cutting-edge AI applications for real-world problems. Her role in AI for sustainable development and AI-driven personalized medicine signifies her commitment to leveraging technology for societal benefit. Her experience in deep learning frameworks like PyTorch and Keras, along with her expertise in machine learning algorithms, has allowed her to shape AI-driven healthcare innovations that have the potential to save lives and enhance medical diagnostics. Through collaborations and mentorship, she inspires the next generation of AI researchers to push the boundaries of technological advancements.

🚀 Legacy and Future Contributions

As an AI researcher and engineer, Saba continues to drive innovation in medical imaging and generative AI. Her aspirations include advancing AI methodologies for early disease detection, improving healthcare accessibility through AI-driven solutions, and fostering AI applications in sustainable development. Her ability to blend technical expertise with a deep understanding of healthcare challenges positions her as a leader in the field. With a promising future ahead, she remains dedicated to exploring new AI frontiers that will revolutionize medical imaging, AI ethics, and beyond.

Publication

Title: A Comprehensive Analysis on Machine Learning based Methods for Lung Cancer Level Classification
Authors: S. Farshchiha, S. Asoudeh, M.S. Kuhshuri, M. Eisaeid, M. Azadie, S. Hesaraki
Year: 2025

Title: Breast Cancer Ultrasound Image Segmentation Using Improved 3D Unet++
Authors: S. Hesaraki, A.S. Mohammed, M. Eisaei, R. Mousa
Year: 2025

Title: BERTCaps: BERT Capsule for Persian Multi-Domain Sentiment Analysis
Authors: M. Memari, S.M. Nejad, A.P. Rabiei, M. Eisaei, S. Hesaraki
Year: 2024

Title: UNet++ and LSTM Combined Approach for Breast Ultrasound Image Segmentation
Authors: S. Hesaraki, M. Akbari, R. Mousa
Year: 2024

Title: Classifying Objects in 3D Point Clouds Using Recurrent Neural Network: A GRU LSTM Hybrid Approach
Authors: R. Mousa, M. Khezli, M. Azadi, V. Nikoofard, S. Hesaraki
Year: 2024

Title: CapsF: Capsule Fusion for Extracting Psychiatric Stressors for Suicide from Twitter
Authors: M.A. Dadgostarnia, R. Mousa, S. Hesaraki
Year: 2024

Conclusion

Saba Hesaraki is a highly skilled and motivated AI engineer with a strong academic and research background in medical imaging and generative AI. Her experience across various AI-driven projects, coupled with technical expertise in deep learning and computer vision, positions her as a valuable contributor to the field. With multiple publications and collaborations in AI and machine learning, she continues to make significant advancements in healthcare applications using AI.