Haining Wang — Molecular Research Atlas

01 / RESEARCH INPUTS

A career built across disciplines.

Each stage added a new way to ask questions, solve problems, and move research forward.

Haining Wang wearing personal protective equipment at a work site

Hands-on science. Real-world execution.CHEMISTRY / EXECUTION

A laboratory separation column with colored bands — 1-Material · Separation-system development
An experimental record from separation-system development at 1-Material (2017–2020).

Haining Wang's POSS/PMMA undergraduate thesis in the 2005 outstanding graduation thesis collection — 2005 · The research starting point
POSS/PMMA nanocomposite particles through RAFT and ATRP. Included in Hefei University of Technology's outstanding graduation thesis collection.

MY PERSPECTIVE / AI & DRUG DISCOVERY

Stronger AI. Deeper scientific judgment.

AI expands what we can explore. People make that exploration scientifically meaningful.

Drug discovery brings slow experimental feedback, heterogeneous data and interconnected objectives. Progress depends on connecting models with chemical reasoning, experiments and human curiosity.

Feedback takes time

Synthesis, testing and interpretation have a real time and resource cost. Iteration needs well-chosen experiments.

Data needs context

Assay conditions, endpoints and biological systems matter. Similar-looking values can answer different questions.

Objectives interact

Activity, selectivity, exposure, safety and synthetic feasibility must be considered together.

People connect the loop

Curious, thoughtful and committed scientists define the problem, interpret uncertainty and choose the next step.

02 — 03 / FEATURES & FUSION

The value is in the connections.

Models propose possibilities. Chemical judgment and experimental evidence determine the next move.

I connect AI-generated ideas with molecules that can be made, tested, and meaningfully evaluated.

AIDD · CADD · MEDICINAL CHEMISTRY · SCIENTIFIC LEADERSHIP

04 / SELECTED OUTPUTS

Ideas, decisions, and outcomes.

Five examples of research innovation, technical problem-solving, and AI-enabled project work.

RESEARCH / PUBLICATIONS

The published research behind the journey.

Explore papers across catalysis, synthesis, materials and oncology, with a short introduction and a direct link for every article.

Public author-attributed papers, checked October 2026. Addenda and corrections appear with the original article.

RECOGNITION / PUBLIC CONTRIBUTIONS

Recognition, conversations, and public work.

Awards, conference presentations and authored scientific resources, with direct access to their public records.

Explore all publications

05 / DISCOVERY ECOSYSTEM

A connected discovery ecosystem.

Explore how data, tools, chemistry, and experimental feedback work together across a discovery program.

Across every stage: data provenance, uncertainty, expert review, and experimental feedback.

Nextflow

TOOLS / OPEN PROJECTS / UPDATES

A growing research toolbox.

Useful tools and open-source projects for AI, chemistry and drug discovery, organized by the research question they help address.

My GitHub & projects

Research-station updates

EXPLORATION / ALGORITHMS / MECHANISMS

Ideas you can explore.

Explore how algorithms process information and how structures support scientific questions. This modular laboratory grows alongside the research archive.

INTERACTIVE / LEARNING LAB

Watch a network learn.

A tiny CNN learns to distinguish horizontal and vertical lines. Change the learning rate and see how its features and predictions evolve.

Synthetic-pattern teaching demo. Runs on your device. These metrics describe this example dataset.

12 × 12CONV 3 × 3ReLU + GAP2 CLASSES

EPOCH 00 / 40

Learning rateNoiseSpeed

Input pattern12 × 12

Feature maps4 × 10 × 10

PredictionSOFTMAX

Horizontal—

Vertical—

Training lossValidation loss

—Current loss

—Example validation accuracy

64 training examples · 16 validation examples · fixed seeds. Predictions update from the same held-out pattern.

LET'S CONNECT

Good science starts with a conversation.

For conversations about AI and drug discovery, chemistry, open-source tools, and research collaboration.

Email me sealking.wang@gmail.comPrivacy · 隐私 · Confidentialité ↗

Choose your next discovery

Research

Connecting AI
with drug discovery.