Machine Learning R D

Nevine M. El-leithy, PhD

Phone: 202-***-****

Address: **** ********* ***

College Park, MD 20740

Website: deepbrain.umd.edu

Email: ad5wjp@r.postjobfree.com

ad5wjp@r.postjobfree.com

Summary

Multidisciplinary scientific researcher, academician, educator, biomedical engineer, and neuroscientist with over 20 years experience. Expertise in basic, translational, clinical, and computational neuroscience research. Pioneer of blending molecular and cellular aspects of neuroscience with electrical/computer engineering concepts to address and unravel dysfunctional transduction pathways in neurodegenerative, neuropsychological, and neurodevelopmental disorders. Vast experience in the conception and oversight of the first stages of product development (proof of concept, cross functional prototyping), in addition to running small to medium sized, highly motivated R&D teams under tight constraints of time and budget. Proven track record mentoring and supervising teams of undergraduate, graduate, and post-doc individuals while managing and implementing complex projects through all phases from concept to completion. Skilled in the curation of grant proposals that span integrated circuit design, neural networks, embedded systems, biosensors, VLSI implementation of biologically realistic neural components, neuromorphic systems, mathematical modeling of biological phenomena, machine learning, computational, cognitive, and clinical neuroscience. Special investment in multifaceted research aspects, from the molecular to the systemic level, of Parkinson’s Disease, Alzheimer’s Disease, and related cognitive, motor, and neuropsychiatric disorders. Extensive research in bipolar disorders, as they pertain to early diagnostic processes and clinical treatments. Incessantly searching for clinical and digital biomarkers for early interventions and precision therapeutics. Over 10 years of experience in medical device design, computational modeling for design and safety testing of microelectronic systems hosted in biological tissue, finite element modeling (Comsol, Ansys, Sim4Life), and application of machine learning and AI to human datasets for diagnostics and prognostics of outstanding clinical research problems in neurology and psychiatry. Creative, innovative thinker and designer of closed-loop invasive and noninvasive neuromodulation systems with precision targeting of neural structures. An avid, inquisitive researcher in clinical translational neuroscience with extensive experience in brain-computer interfaces, and rehabilitative systems for motor and other drug-resistant neurological disorders. Quite familiar with the emerging regulatory sciences in pharmaceutical and medical device industries, and especially in the neuromodulatory field. Effective, proactive communicator with experience working in multinational environments and presenting research results in international conferences. Vast academic, industry, and nonprofit experience covering theoretical and practical R&D phases, in traditional analog/digital microelectronic systems, in biochemical pathways of neural circuitry, and in bioelectronics and neurotechnologies. Experienced in different aspects of intellectual property regulations and procedures. Very active in the multifaceted field of Neuroengineering and AI applications to health data. A passionate learner with a wide bandwidth of academic and professional experience in both the US and abroad. Dedicated to fostering generations of

“integrative” scientists. Eager involvement in the non-profit sector that is engaged in neurological disorders and health policy changes to ensure equity, diversity, and inclusion. To revel in the mysteries that hide in-between known spaces is my modus operandi. Work Experience

Chief Scientific Officer for NeuroLight, Inc. (New York City, NY) April 2023 - Present. Leading NeuroLight's R&D focused on developing a non-pharmaceutical treatment for insomnia and other sleep disorders through brain entrainment. Multi-disciplinary consultant for Raven/Aerostar (Crystal City, VA) September 2022 – March 2023. ASIC, VHDL design, radar applications in healthcare. Principal Investigator for Spire Bioventures (San Francisco) in collaboration with Ecole Polytechnique Federale de Lausanne (EPFL) (Switzerland) April 2020 – August 2022. My role involves investigating the basic science and the application of magnetic steering concepts to the design of neural interface technologies such as wearable head devices with the ability to precisely and non-invasively target deep brain nuclei. Additionally, exploring the effects of magnetic fields on the bidirectional interaction between the Central Nervous System (CNS) and the immune system to develop technology that can be applied to COVID patients exhibiting persistent neurological symptoms. I spend 50% of my time on business development writing the technical sections of proposals for external funding. Research Director for Deep Brain Neurotechnology, ECE Department, University of Maryland

May 2014 – August 2022.

• Created the pilot research-driven education program of Deep Brain Neurotechnologies involving the integration of tractography, microscopic neural anatomy and neural activity dynamics into the macroscopic structures of the FDA’s MIDA head and neck virtual phantom to produce a biologically realistic and accessible computer model of the human brain using macro/micro computational neuroscience. Initial research was conducted collaboratively with the CDRH/FDA. The ultimate goal of such work is twofold: (1) the production of the first fully functional biologically realistic computer model of the human head and neck and (2) a 3D bio-printed physical phantom of the head and neck for proof of concept. Such work products would serve as a testbed upon which various brain implants and brain-computer interface (BCI) technologies can be evaluated before engaging in clinical human trials.

• Worked on an FDA CERSI grant to include anisotropy/tractography through DTI processing into the MIDA isotropic model and to run simulations of different lead configurations of Deep Brain Stimulation (DBS) devices using Sim4Life Multiphysics software platform with computable human phantoms, Ansys, MATLAB, and COMSOL.

• The program has been supported financially and intellectually by an international alliance of scientists at ETH Zurich, Zurich MedTech, FDA, UMD and UMD School of Medicine.

• A private company {IGC} donated funds for the development of a novel noninvasive magnetic steering helmet targeting Parkinson’s & Alzheimer’s diseases.

• I laid the groundwork for NeuroBeam which is a multipurpose noninvasive helmet device undergoing an iterative design process.

• Worked on combined tractography and functional connectivity models for subtyping Parkinson’s Disease (PD).

• Experimented with electroglottography (EGG) as a feedback signal in closed-loop DBS.

• Designed coupled-oscillator system using PSPICE to model the brain dynamics of tremors.

• Supervision of graduate and undergraduate members of the team.

• Planning and researching two clinical trials at UMD School of Medicine for evaluation of early motor deficits in young autistic children and testing the effect of Vagal Nerve Stimulation in combination with brain-computer interface technologies on the improvement of psycho-socio-cognitive performance in autistic preteens under the sponsorship of a private non-profit Autism Foundation.

• The program’s research agenda stands at the intersections of fundamental neuroscience, translational neuroscience, clinical medicine, neurocomputation/engineering, and AI-based embedded system design, targeting refractory neurological and psychiatric disorders.

• Part of my administrative success was the procurement of funding from industry and government through ambitious research proposals.

Assistant Clinical Professor for FIRE, University of Maryland June 2017 – June 2019.

• The “Deep Brain Neurotech” (DBN) research & education platform adopted and funded by the “First-Year Innovation & Research Experience” – SVAAP-First-Year-Research Program Unit.

• Authored 20 detailed research guides/modules for Neurotechnologies’ educational/training purposes including EEG/MEG, Signal analysis & processing, Brain-Computer Interface design, Multiphysics Computational Modeling, Regulatory Sciences, Electromagnetism, Multimodal Imaging, Diseases of the basal ganglia, Neuromodulation technologies, Bioresorbable Electronic Systems, 3D-printing, Clinical Research Design, Medical Device design principles, Machine Learning, Computational Neuroscience in Python & Hoc

• Created synergistic & integrative lecture sets resulting in very high student retention.

• Administrative responsibilities for creating, maintaining, and supervision of lab activities.

• Purchased lab equipment for specially designed experiments detailed in 25 accompanying tutorials authored to elaborate different methodologies.

• Procured the donation of 45 Sim4life software licenses (early versions) to the program equivalent to $2.5 million.

• At least 10 projects were accepted for publication in prestigious international conferences where we received excellent feedback from audience in academia, government, and industry. The DBN program I created has always had the endorsement of the FDA, ZMT, ETH & EPFL, as well as the UMD School of Medicine as a comprehensive resource for future neurogenerations in diverse areas of robotics, affective computing, rehabilitation, biosensors, or replacing/augmenting some cognitive functions.

• Using computable biologically accurate human phantoms hosted by the Sim4Life Multiphysics platform, my team tested the effectiveness and safety of both invasive and noninvasive neuromodulation technologies.

• Several presentations at many Brain Consortia in the DC-Maryland-Virginia area leading to create internship opportunities for students in both government and private sectors.

• Headed two clinical studies: one trial using tVNS for ADHD participants as a treatment, the other longitudinal study for finding EEG diagnostic biomarkers in ADHD. Research Scientist in Medical Electroceuticals at the Neuroengineering Lab

(Neuromodulation Division) at ETH, Zurich, Switzerland January 2012 – January 2014. Worked on the computational modeling for various configurations of transcranial magnetic stimulation (TMS) devices and the resulting current distribution in the brain. The results were then evaluated to determine the ability of the various configurations to recalibrate neural activity in specific brain circuits. I developed algorithms to account for the tradeoff between focality and depths of stimulation by using different numerical coil optimization techniques and accordingly producing multi-focal micro-scale stimulation coils. Another research project I led involved selective stimulation of neurons in the hippocampus using temporally interfering electric fields. Medical Science Liaison at Futuristic Studies, United Nations University January 2011 – January 2012. I investigated the role of Next Technologies on the human condition and future societies, especially aspects of AI (artificial narrow intelligence and artificial general intelligence), synthetic biology, nanotechnologies, IoTs, global regulatory strategies, and innovations in patent laws. Worked extensively over the years with the non-profit Millennium Project in DC.

It was recognized that with the rise of algorithms in medical treatment, wearables and diagnostics, and the cloud in health data storage, regulators and researchers are struggling to keep pace. I wrote several reports on the emerging model in precision medicine necessitating the employment of a disease detection-intervention tool within an integrated closed-loop disease management system that relies on biosensing, signal analysis, computational modeling, and machine learning. Other reports focused on the complexity of finding qualified biomarkers in medical neuroscience due to the heterogeneity of neurological disease symptoms. Director of NeuroNascence, Academy of Scientific Research and Technology in Cairo, Egypt

January 2009 – January 2011. I led the creation of a Middle-Eastern brain initiative to outline the impending paradigm shifts in neuroscience. Raised funding for brain science research and social awareness of generally underfunded aspects of neuropsychiatry and neurology in the countries of the middle east. Designed advocacy and clinical trial recruiting pamphlets for relevant research in connectomics and functional MRI. Managed the Board of Directors. Acted as medical science liaison (MSL) to governmental intiatives. Visiting Professor at Ain Shams University in Egypt January 2007 – January 2011. Designed and taught courses on: Computational Modeling in Molecular & Cellular Neurobiology, Bioelectricity, Fundamentals of MRI, Neuromodulation & Brain Stimulation Devices, Bioinstrumentation and Signal Processing, and Bioelectronics. Headed two committees in the medical school: one for the inclusion of bioengineering syllabi, the other for reforming the neuroscience program.

Principal Investigator, UNESCO Neurodiversity Program Grant, Egypt January 2007 – January 2011. I led teams of scholars to collect multimodal human brain data from urban cities and rural villages. Along with my team of graduate students, I built algorithms analyzing the resulting brain data from electrocorticography/EEG. The results obtained seem to be in close agreement with the more recent findings of the US-based Sapien Labs’ Human Brain Diversity Project, which had gathered EEG data from various parts of India. Brain scans and rhythms varied in a statically significant manner depending on environment, education, and socioeconomic level. Interestingly, the alpha oscillations were virtually undetectable in remote villages. By creating this databank, many local researchers contributed to gleaning the conceptual framework and guidelines I submitted in the final reports. Research Fellow at Stanford’s Medical School & BIO-X June 2000 – July 2005. During my time at Stanford, I participated in funded projects and led research driven teaching seminars. One such project, had to do with targeting beta-amyloid plaques in Alzheimer’s disease. The goal was to translate to human patients the findings that gamma oscillations (40-60 Hz) introduced through optimal fibers into genetically altered

(Alzheimer’s) mice brains caused reduction of plaques in said mice. I supervised teams of students to experiments with a variety of optimal strategies adapted to human application. I was involved in extensive clinical research studies on the relationship between creativity and certain types of mental illness. I proposed a multi-level model of the interactive process engaging key elements of the hypothalamus-pituitary-adrenal axis (HPA-axis) and hippocampal neurogenesis, which won special attention. This was pursuant to analyzing diverse data collected during a clinical trial using Lamotrigine as treatment for manic depressive and schizoaffective disorders. I also integrated data from rudimentary BCI technology into the development of the model. I also received clinical training during the Lamotrigine clinical trials. As part of my contract, I was a lecturer in finite element modeling (FEM) in the Electrical Engineering Department and lecturer of psychopharmacology in the Psychology Department. Doctoral Student at Stanford University.

August 2001 – May 2007. With the aid of facilities at Stanford’s medical school, among other collaborations, I used deep learning algorithms to determine brain default mode network abnormalities in bipolar disorders. I also helped identify potential targets for neurostimulation to alleviate specific symptoms.

Thesis: “Brain Default Mode Network Abnormalities and Potential Stimulation Targets in Bipolar Disorders”

Postdoc at Max Planck Society, University of Heidelberg, Germany January 1997 – January 1999. This work focused on the design of portable bioinstrumentation to be used in Trauma Departments. I worked on the theory and development of functional near- infrared (fNIR) spectroscopy devices. I also worked on experiments involving low intensity focused ultrasound (LiFUS) stimulation for targeting the blood-brain barrier in order to enhance the effective delivery of chemotherapy to brain tumors. Junior Science Fellow at the Max Plank Institute for Brain Research (Theories of Neural Dynamics), Frankfurt, Germany

January 1995 – January 1997. I explored the mutual dialogue between electrophysiological experiments and computational neuroscience-based predictions through detailed examination of the neurophysiology of memory in nonhuman primates. Experimenting with the biophysics of memory laid the groundwork for the microelectronic model of cellular mechanisms of long-term potentiation (LTP) in the hippocampus, presented in my first dissertation, “Silicon Implementation of Long-Term Potentiation Signaling Pathways.” Principal Investigator at the Microsytems Lab, University of Maryland 1990 – 1993. I worked on neuromorphic analog/digital microelectronic design of the crustacean

(lobster) stomatogastric ganglion inspired by biophysics-based modeling of neural circuitry. Co-Principal Investigator on ONR Grant No. N00014-90-J-1114: Pulse-Coded Biologically Motivated Neural-Type MOS Circuits at Microsystems Lab, University of Maryland 1991 – 1993. I modeled the role of NMDA receptors and second messenger signaling pathways in the induction of hippocampal long-term potentiation, both mathematically and in integrated circuitry.

Expert Witness/Consultant at Patent Law Firms Cushman, Darby, & Cushman and Leidig, Voigt, & Meyer

1988 – 1992. I worked on the prosecution and litigation of electronic and medical device inventions as well as served as an expert witness for major semiconductor companies. Lecturer at George Washington University

1985 – 1988. I taught microelectronics, neural networks, EEG, and Evoked Potentials. I also volunteered to teach computer technologies to disadvantaged inner city adult students at

“HummRRO Tech” affiliated with GWU.

Siemens Electrical Engineering Award-Winning Intern, Munich, Germany 1982 – 1983. I studied the basic principles of integrated circuit design. Education

• PhD in Neuroscience, Stanford University, 2007

• PhD in Electrical Engineering, focus: Biomedical Engineering, George Washington University, 1997

• MSc in Medical Sciences (equiv. Public Health), University of Munich, 1989

• MSc in Electrical Engineering with Distinction, focus: Medical Engineering, George Washington University, 1986

• BSc in Electrical Engineering with a year in Imperial College (London), Cairo University, 1984

Select Awards:

Teaching & Research Award in Neuroscience & Bioengineering, Ain Shams University, Egypt, 2009, 2010

Outstanding Futurist Award, UNU, 2012

Outstanding Researcher Award, Arab Women in Engineering, 1991 Outstanding Volunteer Award, HumRRO Tech, 1990

Teacher of the Year Award, George Washington University, 1986 Professional Societies:

Institute of Electrical & Electronic Engineers (IEEE) Biomedical Engineering Society (BMES)

Society for Neuroscience (SfN)

European Neural Network Society (ENNS)

Languages:

Bilingual in English and Arabic; Intermediate level in German and French Select Publications: (not exhaustive)

1. El-leithy, N. Toward targeted non-invasive closed-loop brain stimulation. Invited manuscript for Deep Brain Stimulation from Cells to Circuits: Recent Advances in Neural Engineering and Neuroimaging, Frontiers in Human Neuroscience

2. Lundegard, G., Kazi, A., El-leithy, N. Variational Analysis of a Magnetic Steering Helmet Design. BMES/FDA Frontiers in Medical Devices, 2019. 3. Javaheri, H., Jakopin, N., El-leithy, N., Angelone, L.M., Iacono, M.I., Fujimoto, K. Image coregistration of diffusion tensor imaging and structural MRI data of the MIDA model. BMES/FDA Frontiers in Medical Devices, 2019.

4. Lundegard, G., Kazi, A., El-leithy, N. NeuroBeam: A Magnetic Steering Helmet for Deep Brain Pathology. NeuroCAS/BioCAS, 2018.

5. Roudnitsky, D., El-leithy, N. Using Machine Learning to Evaluate Handwriting Patterns for the Diagnosis of Parkinson's Disease. Machine Learning in Science & Engineering, 2018. 6. Bharadwaj, R., El-leithy, N. Towards the Development of a Diagnostic EEG Protocol for ADHD. Machine Learning in Science & Engineering, 2018. 7. El-leithy, N. New Hope for Autism, The Journal of The Egyptian Public Health Association, 2011.

8. El-leithy, N. Optogenetics: Where We Stand. The Journal of the Egyptian Medical Association, 2009.

9. El-leithy, N., Helmy, M., Ketter, T. Hippocampal Volume, Neurogenesis, and Manic- Depression. The Journal of the Egyptian Medical Association, 2008 10. El-leithy, N. Default-Mode Network Abnormalities in Bipolar Disorders. Neuroscience Institute, Medical School, Ain Shams University, 2007 11. Newcomb, R.W., Sanchez-Sinencio, E., El-leithy, N. Special Issue on Hardware Implementations – Preface. IEEE Transactions on Neural Networks, 14(5):973, 2003. 12. He, Xinhua, El-leithy, N., Sellami, L., Newcomb, R.W. An Adjustable CMOS load line for nonlinear circuits. Circuits and Systems, 2000. Proceedings of the 43 rd

IEEE Midwest

Symposium on Circuits & Systems.

13. Tsay, S. W., El-leithy, N., Newcomb, R.W. An all MOS neural-type cell. Circuits and Systems. Proceedings of the 34

th

Midwest Symposium on Circuits & Systems, 1991.

14. Newcomb, R.W., El-leithy, N. Perspectives on realizations of neural networks. IEEE International Symposium on Circuits & Systems, 1989. 15. El-leithy, N., Zaghloul, M.E., Newcomb, R.W. CMOS circuit for MOS transistor threshold adjustment: a means for neural network weight adjustment. Proceedings of the 1989 International Symposium on Circuits and Systems.

16. Newcomb, R.W., El-leithy, N., Rodellar, V., Gomez, P., Cordoba, M. Computable Minimum Lattice-Like ARMA Synthesis. IEEE Transactions on Circuits and Systems. Vol. CAS-35, No. 5, 1988, pp. 577-583

17. El-leithy, N. & Newcomb, R.W. Hysteresis in Neural-Type Circuits. Proceedings of the 1988 IEEE International Symposium on Circuits & Systems, Vol.2, Helsinki, Finland, pp.993-996.

18. El-leithy, N., Zaghloul, M., Newcomb, R.W. Silicon Implementation of Pulse Coded Neural Networks. Proceedings of the 27th IEEE Conference on Decision and Control, 1988. 19. El-leithy, N., Newcomb, R.W., Aldave, T., Rodellar, V., Gomez, P. Multilevel Neural-Type Lattices. Proceedings of the 1986 IEEE Workshop on Languages for Automation, funded by US-Spain Joint Commission and National Science Foundation, pp.237-241 20. Newcomb, R.W., El-leithy, N. Chaos Generation using binary hysteresis. Circuits Systems and Signal Processing, 5(3):321-341, 1986.

21. El-leithy, N., Newcomb, R.W., Zaghloul, M. A Basic MOS Neural-Type Junction/A Perspective on Neural-Type Microsystems. Proceeding of the International Conference on Neural Networks, San Diego, CA, 1986.

22. Newcomb, R.W., El-leithy, N. Chaos Using Hysteretic Circuits. Proceedings of the 1986 International Symposium on Circuits & Systems, San Jose, CA, pp. 55 23. El-leithy, N., Newcomb, R.W. Overview of Neural-Type Electronics. Proceedings of the 28th Midwest Symposium on Circuits & Systems, Lousiville, KY, 1985, pp. 199-202

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